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ASSESSMENT OF THE RISK OF CONSUMING MILK/ MILK

PRODUCTS CONTAMINATED WITH LISTERIA MONOCYTOGENES

FROM THE INFORMAL MARKETS

BY

JOY APPIAH

(10023038)

THIS THESIS/ DISSERTATION IS SUBMITTED TO THE UNIVERSITY OF

GHANA, LEGON, IN PARTIAL FULFILLMENT OF THE REQUIREMENT FOR

THE AWARD OF MASTER OF PHILOSOPHY DEGREE IN FOOD SCIENCE

JUNE/ 2012

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DECLARATION

The work described in this report was done by me at the Nutrition and Food Science

Department of the University of Ghana (U.G), Legon, Accra, Ghana, under the supervision

of Prof Kwaku Tano- Debrah, Dr. Betty Bediako- Amoah and Dr. Mohammed .M. Alfa.

…………………………………

JOY APPIAH

STUDENT

…………………………………………

PROF. K. TANO- DEBRAH

PRINCIPAL SUPERVISOR

…………………………….. ………………………….

DR. BETTY BEDIAKO-AMOAH DR. M. M. ALFA

SUPERVISOR SUPERVISOR

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DEDICATION

I dedicate this thesis to the Lord God, who it is, that has enabled me to accomplish this feat

and others. I dedicate it also to my loved ones of blessed memory: my mother (Mrs. Rose

Appiah), brother (Frederick .P. Appiah (Jnr.)) and sister (Georgette Afia Sarpong Appiah).

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ACKNOWLEDGEMENTS

This work was facilitated by financial support from the German Federal Ministry for

Economic Cooperation and Development (BMZ) through GIZ. It was done in

collaboration with the International Livestock Research Institute (ILRI). My profound

thanks to these organizations.

For their invaluable help which contributed immensely to the successful completion of this

work I am also grateful to my supervisors Prof. Kwaku Tano- Debrah and Dr. Betty

Amoah of Nutrition and Food Science, University of .Ghana (N.F.S- U.G) and Dr.

Mohammed Musheibu Alfa: Head – Animal Products and Biosafety, Ghana Food and

Drugs Board (FDB).

Also to Drs. Delia Grace and Kohei Makita of ILRI, Dr. F. K. Saalia (N.F.S- U.G), Mrs.

Bernice Kaulton- Senaye of the Food Research Institute (FRI), Dr. George Nipah of the

Veterinary Services Directorate (VSD), Mr. Paapa Blankson of the Epidemiology

Division, (MoH), Mr. S. Doe of the Tema General Hospital and all others who in one way

or the other contributed to this work, know you also are greatly appreciated.

Finally, many thanks go also to my family including Col Frederick Appiah (Rtd), Freda

Appiah, Judith Dickson, Anita Appiah, Philip Appiah and Joycelyn Appiah. Your support

and prayers I could not have done without. Thank you once again.

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ABSTRACT

Listeria monocytogenes is the causative organism of listeriosis, a debilitating and often

fatal infection, which occurs mostly via food consumption. However, some foods such as

dairy, probably due to their nutritious nature and handling characteristics, are more prone

to contamination and thus are relatively more culpable. To prevent L. monocytogenes

contamination of such products, it is critical to be insightful of listerial contamination

routes in food processing environments. This study investigated L. monocytogenes

contamination routes along the informal milk value chain from production to consumption.

Microbiological methods according to the US/ FDA protocol (Hitchins, 1998) including

chromogenic Listeria agar (ISO) OCLA use and biochemical methods including the Gram,

Catalase and the Beta- haemolysis were employed to isolate L. monocytogenes from 304

samples of milk/ milk products. Results indicated that prevalence generally increased with

repeated handling though it decreased with boiling (p<0.05). Prevalence in samples at

production, retail (i.e. raw milk on the market), after boiling and fermentation were 42.1,

78.9, 18.4 and 59.2 percent respectively. Also 14.8, 57.9, 6.6 and 46.1 percent of samples

had mean counts ≥100 CFU/ mL at production, at retail, after boiling and fermentation

respectively (p<0.05). A Quantitative Risk Assessment indicated a higher exposure and

probability of illness when raw milk at retail was consumed and the least when boiled milk

was consumed. Crude Sensitivity Analysis also predicted the most effective mitigation

strategy for exposure to be boiling. Hence boiling of raw milk was crucial to its safe

consumption. However, with contamination at all stages of the value chain, it was

important to emphasize on the hygiene regimen along the whole continuum as safety at

one stage could very easily be undone by the lack of proper procedures at another.

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TABLE OF CONTENTS

DECLARATION ................................................................................................................... i

DEDICATION ..................................................................................................................... iii

ACKNOWLEDGEMENTS ................................................................................................. iv

ABSTRACT .......................................................................................................................... v

TABLE OF CONTENTS ..................................................................................................... vi

LIST OF TABLES ............................................................................................................... xi

LIST OF FIGURES ............................................................................................................ xiii

LIST OF EQUATIONS ...................................................................................................... xv

LIST OF ABREVIATIONS ............................................................................................... xvi

CHAPTER ONE ................................................................................................................... 1

INTRODUCTION ................................................................................................................. 1

1.1 General Background .................................................................................................... 1

1.2 Risk Profile of L. monocytogenes ................................................................................ 7

1.3 Statement of Problem ................................................................................................ 10

1.4 Scope ...................................................................................................................... 13

1.4.1 Specific Objectives ............................................................................................. 13

CHAPTER TWO ................................................................................................................. 14

LITERATURE REVIEW .................................................................................................... 14

2.1 Agriculture Sector in Ghana ...................................................................................... 14

2.1.1 Livestock sub-Sector in Ghana ........................................................................... 15

2.1.2 Production and Consumption of ASFs in Ghana ................................................ 15

2.1.3 Meat and Meat Product Consumption in Ghana ................................................. 15

2.1.4 Milk and Milk Product Consumption in Ghana .................................................. 16

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2.2 Informal Milk Marketing in Ghana ........................................................................ 17

2.2.1 Handling of Milk/ Milk Products in Ghana ........................................................ 19

2.3 Microbial Ecology of Raw Cow‘s Milk .................................................................... 19

2.3.1 Milk Pasteurization (Low-Heat Treatment) ........................................................ 20

2.4 Foodborne Zoonoses in Ghana .................................................................................. 20

2.4.1 Anthrax ............................................................................................................... 20

2.4.2 Tuberculosis (TB) ............................................................................................... 21

2.4.3 Brucellosis ........................................................................................................... 21

2.4.4 Other Emerging Foodborne Zoonoses in Ghana ................................................ 22

2.5 Rapid Rural Appraisal (RRA)/ Participatory Rural Appraisal (PRA) ....................... 23

2.5.1 Participatory Approach ....................................................................................... 23

2.6 Microbial Risk Assessment ....................................................................................... 24

2.6.1 Risk Assessment of L. monocytogenes-- a Foodborne Pathogen ....................... 26

2.6.1.1 Hazard Identification (H.I) ............................................................................... 26

2.6.1.1.1 Characteristics of Listeriae ........................................................................... 26

2.6.1.1.2 Isolation and Detection of Listeriae .............................................................. 27

2.6.1.1.3 Morphology of Listeriae ............................................................................... 29

2.6.1.1.4 Prevalence of L. monocytogenes in Cow‘s Milk .......................................... 29

2.6.1.2 Hazard Characterization ................................................................................... 30

2.6.1.2.1 Pathogenicity of L. monocytogenes .............................................................. 30

2.6.1.2.2 Infectious Dose and Incubation Period ......................................................... 32

2.6.1.2.3 Virulence of L. monocytogenes and Environmental Stresses ....................... 33

2.6.1.2.4 Acid Tolerance of L. monocytogenes ............................................................ 34

2.6.1.2.5 Temperature Tolerance ................................................................................. 35

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CHAPTER THREE ............................................................................................................. 36

MATERIALS AND METHODS ........................................................................................ 36

3.1 Study Site and Population ...................................................................................... 36

3.2 Study Design .............................................................................................................. 37

3.2.1 Risk Assessment ................................................................................................. 37

3.3 Sampling .................................................................................................................... 38

3.4 PRA Survey ............................................................................................................ 39

3.4.1 Mapping .............................................................................................................. 40

3.4.2 Seasonal Calendars ............................................................................................. 40

3.4.3 Disease Ranking (Proportional Piling) ............................................................... 40

3.4.4 Matrix Scoring .................................................................................................... 41

3.5 Questionnaire Survey ............................................................................................. 41

3.5.1 Criteria for Inclusion of Respondents ................................................................. 41

3.6 Chemical Analysis of Milk Samples ...................................................................... 41

3.6.1 PH Determination ............................................................................................... 41

3.7 Microbial Analysis ................................................................................................. 42

3.7.1 Detection, Isolation and Enumeration of Listeriae ............................................. 42

3.8 Statistical Analyses of Data ................................................................................... 43

CHAPTER FOUR ............................................................................................................... 44

RESULTS AND DISCUSSION ......................................................................................... 44

4.2 PRA Survey ................................................................................................................ 45

4.2.1 Farmers PRA ....................................................................................................... 45

4.2.1.1 Demographic Information on Farmers at PRA ................................................ 45

4.2.1.2 Mapping ........................................................................................................... 46

4.2.1.3 Analysis of Seasonal Calendar ......................................................................... 47

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4.2.1.3.1 Seasonal Occurrence of Rainfall ................................................................... 48

4.2.1.3.2 Milk Production ............................................................................................ 49

4.2.1.3.3 Seasonal Occurrence of Diseases .................................................................. 49

4.2.1.4 Preference Ranking on Livelihood Indices of Farmers ................................... 50

4.2.1.5 Proportional Piling of Disease Symptoms of Animals .................................... 51

4.2.2 Assembler‘s PRA ................................................................................................ 55

4.2.2.1 Mapping ........................................................................................................... 55

4.2.2.2 Milk Handling by Assemblers ......................................................................... 55

4.2.3 PRA with Milk/ Milk Product Retailers .............................................................. 56

4.2.3.1 Mapping ........................................................................................................... 56

4.2.3.2 Quality Control at Retail .................................................................................. 57

4.2.3.2 Marketing of Milk/ Milk Products at Old Tulaku, Ashaiman .......................... 58

4.2.3.3 Matrix Scoring for Retailers ............................................................................ 60

.. .4.2.3.4 Milk Distribution from Production to Consumption and Evolution of Hazards 62

4.3 Questionnaire Survey ............................................................................................. 66

4.3.1Retailers Questionnaire Survey ............................................................................ 66

4.3.1.1 Demographic Characteristics of Retailers ....................................................... 66

4.3.2.1 Demographic Characteristics of Consumers .................................................... 74

4.3.2.2 Knowledge on Milk/ Milk Product Consumption Trends ............................... 75

4.4 Results- Laboratory Analyses ....................................................................................... 85

4.4.1 Detection and Isolation of Listeria spp. and L. monocytogenes ......................... 85

4.5 Risk Assessment ............................................................................................................ 97

4.5.1 Exposure Assessment .......................................................................................... 97

4.5.1.1Need for Simulation in Assessing Risk ............................................................ 97

4.5.1.2 Simulated L. monocytogenes Contaminated Dairy Products at Consumption .... 98

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4.5.2 Dose- Response Relationship ............................................................................... 113

4.5.3. Risk Characterization Results ................................................................................. 116

4.5.4 Determining Critical Points for Intervention ........................................................... 119

CHAPTER FIVE ............................................................................................................... 120

CONCLUSIONS AND RECOMMENDATIONS ............................................................ 120

5.1 Conclusions ............................................................................................................. 120

5.2 Recommendations ................................................................................................... 121

REFERENCES .................................................................................................................. 123

APPENDICES ................................................................................................................... 138

APPENDIX A ................................................................................................................... 138

APPENDIX B (I) .............................................................................................................. 138

APPENDIX B (II) ............................................................................................................. 139

APPENDIX C (I) .............................................................................................................. 139

APPENDIX C (II) ............................................................................................................. 144

APPENDIX C (III) ............................................................................................................ 144

APPENDIX D (I) .............................................................................................................. 145

APPENDIX D (II) ............................................................................................................. 145

APPENDIX E .................................................................................................................... 146

APPENDIX F (I): CASE STUDY QUESTIONNAIRE- RETAILERS ........................... 147

APPENDIX F (II): CASE STUDY QUESTIONNAIRES- CONSUMERS ..................... 151

APPENDIX G (I) .............................................................................................................. 154

APPENDIX G (II) ............................................................................................................. 155

APPENDIX G (III) ............................................................................................................ 155

APPENDIX H (I) .............................................................................................................. 156

APPENDIX H (II) ............................................................................................................. 157

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APPENDIX H (III) ............................................................................................................ 157

LIST OF TABLES

Table 1.1: Livestock populations in Ghana (‗000) ................................................................ 2

Table 1.2: Annual domestic meat production (1000 Metric) 2001-2006 .............................. 3

Table 1.3: Top 5 causes of morbidity in Ghana 1995-2007 .................................................. 4

Table 1.4: Top 5 causes of morbidity in Ghana 1995-2007 .................................................. 5

Table 1.5: Bacterial diseases transmissible to man through milk consumption .................... 6

Table 2.6: A comparison of domestic production and imports (000) MT (2000/07) .......... 16

Table 2.7: Informal milk market agents in Ghana .............................................................. 18

Table 2.8: Human Tuberculosis reported in Ghana, 1995-2007 ......................................... 21

Table 2. 9: Characteristics of the Genus Listeria ................................................................ 27

Table 2. 10: Illness caused by L. monocytogenes ............................................................... 33

Table 4.11: Background Information on milk producing farmers ...................................... 46

Table 4.12: Lexicon of local terms for diseases and symptoms farmer‘s language ............ 51

Table 4.13: Demographic characteristics of consumer respondents ................................... 66

Table 4.14: Traditions of the milk retail trade .................................................................... 67

Table 4.15: Supply of raw milk to retailers ........................................................................ 69

Table 4.16: Quantities of milk supplied by Assembler ....................................................... 70

Table 4.17: Milk/ milk product handling during sale ......................................................... 70

Table 4.18 Association of milk with probable diseases ...................................................... 71

Table 4.19: Suspected symptoms associated with listeriosis in Retailers .......................... 72

Table 4.20: Handling practices of milk after receipt from Assembler ................................ 73

Table 4.21: Demographic characteristics of consumer respondents ................................... 74

Table 4.22 Milk consumption habit of consumers ............................................................. 76

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Table 4.23 Consumer attitudes to food hygiene on the informal market ............................ 77

Table 4.24 Fresh milk handling practices of consumers ..................................................... 78

Table 4.25: Qualitative Exposure Assessment for the risk of exposure to L. monocytogenes

from the consumption of dairy product from the informal market ..................................... 81

Table 4.26: Occurrence of probable initial symptoms of human listeriosis ........................ 82

Table 4.27 Occurrence of pregnancy related abnormalities in female consumers .............. 83

Table 4. 28: Summary of the biochemical characteristics of Listeriae/ L. monocytogenes 88

Table 4.29: Morphological characteristics of Listeriae/ L. monocytogenes* ..................... 88

Table 4.30 Descriptive statistics on pH changes from production to fermentation ............ 89

Table 4.31: Detection and isolation of Listeriae/ L. monocytogenes in samples ................ 91

Table 4.32: Descriptive statistics on L. monocytogenes counts from production to

fermentation ........................................................................................................................ 94

Table 4.33: Amounts of milk/ milk products consumed per day at Ashaiman ................... 97

Table 4.34: Summary of main indicator parameters per ml of milk/ milk products ......... 102

Table 4.35 Summary of main indicator parameters per serving of milk/ milk products .. 106

Table 4.36: Summary of main indicator parameters for total daily consumption of milk/

milk products ..................................................................................................................... 110

Table 4.37: Selected Quantiles from Simulated Distributions of log10 Number of L.

monocytogenes Organisms in Contaminated Milk/ Milk Product Servings at Point of

Consumption ..................................................................................................................... 112

Table 4.38: Probability of illness for consumers at Ashaiman estimated for different levels

of L. monocytogenes at the time of consumption with milk/ milk products contaminated at

those levels. ....................................................................................................................... 114

Table 4.39: Probability of illness for consumers at Ashaiman estimated for different levels

of L. monocytogenes at the time of consumption with milk/ milk products contaminated at

those levels. ....................................................................................................................... 117

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LIST OF FIGURES

Figure 2.1: Comparism of various sectorial GDP‘s with the national economic growth ... 14

Figure 2.2: Protocol for microbial risk assessment (CAC, 1999) ....................................... 24

Figure 4.3: Participatory map of resources important to farmers‘ livelihood ..................... 47

Figure 4.4: Seasonal calendar session at farmers‘ PRA ...................................................... 48

Figure 4.5: Seasonality of events on the calendar .............................................................. 48

Figure 4.6: Farmer milking Figure 4.7: Filtering of milk on retail market .. 49

Figure 4.8: Constraints to the livelihood indices of farmers ............................................... 50

Figure 4.9: Piling of stone at session followed by their distribution by symptom .............. 52

Figure 4.10: Comparison of the impact of disease on various livelihood indices .............. 52

Figure 4.11: Comparison of the impact of disease on various livelihood indices ............. 53

Figure 4.12: Map of Electoral Areass (EA) with informal retailing of dairy products at

Ashaiman. (EAs and dairy marketing were represented with the red and yellow cola nuts

respectively) ........................................................................................................................ 56

Figure 4.13: Clot-on-boil Quality Test (a) Water used in washing bowls (b) ................. 57

Figure 4.14: Pathway for milk transformation and sale at Ashaiman ................................. 59

Figure 4.15: Plot of livelihood constraints against retailers‘ livelihoods indices ............... 60

Figure 4.16: Quantitative milk distribution model; production to retail, for Ashaiman ..... 63

Figure 4.17: Quantitative milk distribution model; production to retail, for Ashaiman ..... 64

Figure 4.18: Schematic presentation of food exposure pathway modeled using the MPRM

............................................................................................................................................. 65

Figure 4.19: Percent average quantities of type(s) of dairy product sold at retail .............. 68

Figure 4.20: Disease symptoms associated identified by retailers ...................................... 71

Figure 4.21: Color changes after enrichment in UVM, LEB and Fraser broths respectively

............................................................................................................................................. 85

Figure 4.22: Color changes after enrichment in Fraser broth for retailed, production and

boiled samples consecutively from left to right .................................................................. 86

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Figure 4.23: Colonies of Listeriae on OCLA. (a) Green without halo (b) Green with halo

............................................................................................................................................. 86

Figure 4.24: Colonies of Listeria species on (a) PALCAM Agar (b) Oxford (OXA) Agar 87

Figure 4.25: Blood hemolysis results: (a) S. aureus; (b) Isolate; (c) Reference strain ....... 87

Figure 4.26: Pot of milk on coal fire (a) Vessel for dishing out milk (b) ................. 93

Figure 4.27: Quantitative milk distribution model: production to retail ............................. 96

Figure 4.28: A graph of probability density against Log10CFU of L. monocytogenes in a ml

of milk at production ........................................................................................................... 99


of milk at retail .................................................................................................................. 100


of boiled milk .................................................................................................................... 101


of fermented milk .............................................................................................................. 102

Figure 4.32: A graph of probability density against Log10CFU of L. monocytogenes in a

serving of milk at production ............................................................................................ 103

Figure 4. 33: A graph of probability density against Log10CFU of L. monocytogenes in a

serving of milk at retail ..................................................................................................... 104


serving of boiled milk ....................................................................................................... 105


serving of fermented milk ................................................................................................. 106

Figure 4.36: A graph of probability density against Log10CFU of L. monocytogenes in total

daily servings of milk at production .................................................................................. 107


daily servings of milk at retail ........................................................................................... 108


daily servings of boiled milk ............................................................................................. 109


daily servings of fermented milk ....................................................................................... 110

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Figure 4.40: Exponential dose- response model for ingested dose of L. monocytogenes

associated with milk at production .................................................................................... 114


associated with milk at retail ............................................................................................. 115


associated with boiled milk ............................................................................................... 115


associated with fermented milk ......................................................................................... 116

Figure 4.44: Fault tree of the events that could have led to the exposure of L.

monocytogenes to consumers of informally marketed milk/ milk product at Ashaiman .. 118

Figure 4.45: Spearman rank correlation between the estimated probabilities of L.

monocytogenes contamination for the various processes involve in milk/ milk products

production according to the PRM. .................................................................................... 119

LIST OF EQUATIONS

Equation 1: Sample Size Determination ............................................................................. 38

Equation 2: Cochran (1963) Formula for Adjusting Sample Size ...................................... 38

Equation 3: Expression of Counts in CFU/ mL .................................................................. 42

Equation 4: Process of Decrease in pH of milk with Heating ............................................. 90

Equation 5: Exponential Model for Dose-Response ......................................................... 113

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LIST OF ABREVIATIONS

AFNOR Assoçiation Francaise de Normalisation

ASF Animal Sourced Foods

AZC Ashaiman Zonal Council

BoG Bank of Ghana

CAADP Comprehensive Accelerated Agriculture Dev. Program

CAC Codex Alimentarius Commission

CAMP Christy Atkins Munch-Petersen

CDC Centre for Diseases Control

CFARE Council for Food Agriculture and Resource Economics

CFSAN Center for Food Safety and Applied Nutrition

CFSPH Center for Food Security and Public Health

CFU Colony-forming unit

CNS Central Nervous System

FAO Food and Agriculture Organization

FDA Food and Drug Administration

GDP Gross Domestic Product

GH¢ Ghana cedi

GHS Ghana Health Service

GSS Ghana Statistical Services

ILRI International Livestock Research Institute

ILSI International Life Sciences Institute

ISO International Organization for Standards

LME Liquid Milk Equivalent

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MoFA Ministry of Food and Agriculture

MoH Ministry of Health

NePAD New Partnership for African Development

OIE World Organization for Animal Health

PRA Participatory Rural Appraisal

RCP Recommended International Code of Practice

SRID Statistical Research and Information Directorate

STEC Shiga-Toxin producing E. coli

TMA Tema Municipal Assembly

US United States

US$ United States Dollar

USDA United States Department of Agriculture

VSD Veterinary Services Directorate

WASH West African Short Horn

WB World Bank

WHO World Health Organization

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CHAPTER ONE

INTRODUCTION

1.1 General Background

The WHO has described foodborne diseases (FBD‘s) as illnesses of an infectious or toxic

nature caused by, or thought to have been caused by the consumption of food and water

(Adams and Motarjemi, 1999), which conceivably represents the most common health

problem of recent times, thus reducing significantly economic productivity (Mukhola,

2000). It estimates that up to a third of people in developed countries are affected by

FBD‘s (WHO, 2009). According to the Ghana Health Service (GHS) the total number of

sick persons related to foodborne illnesses during 2003 in Ghana was 2.3 million whiles

the associated losses for 2002, based on the premise that foodborne illnesses were diarrheal

diseases, was GH¢15.2 million [approximately US$10.9 million at a rate of $1 to GH¢1.4

(Antweiler, 2009)]. This figure accrues from healthcare costs to the Government,

individuals and the loss of about 3.4 million working days (Ghana: FAO/WB CP, 2005).

FBD‘s are caused by the consumption of foods exposed to hazards that may be biological

or pathogenic (e.g. viruses, bacteria, parasites), chemical (e.g. heavy metals and toxins),

and others physical (e.g. glass fragments, bone chips) (Schmidt et al., 2003). Etiological

information suggests that the frequency of occurrence from microbial or pathogenic origin

is by far higher (Hall, 1971). According to the WHO 62% of all human pathogens are

zoonotic (Taylor et al., 2001). This agrees with the OIE that 75% of all emerging human

diseases originate from animal reservoirs (Vallat, 2007). Consequently, animal sourced

foods (ASF) have been found guilty for the majority of FBD‘s (De Buyser et al, 2001) and

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incidences increase with increasing access to such foods especially without adequate

hygiene, inspection for safety or satisfactory heating to kill pathogens (McCrindle, 2008).

Nevertheless, there is a steady shift to ASF across developing countries (DC‘s) (Popkin,

2001). In this vein, Ghana has seen a gradual increase in animal populations (Table 1.1),

and therefore their products (Table 1.2) in response to an almost exclusive domestic

demand (Ghana: FAO/WB CP, 2005). Unfortunately, as low-income groups dominate

(GPN, 2004), akin to what pertains in most DC‘s, the larger share of the growing demand

for ASF‘s is expected to be satisfied through informal marketing channels where Rehber

and Ulusoy, (1998) have reported of premium being placed on affordability even to the

detriment of safety.

Table 1.1: Livestock populations in Ghana (‘000)

Types of

Livestock

1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

Poultry 17,302 18,810 20,472 22,032 24,251 26,395 28,727 28,386 34,030 37,038

Sheep 2,576 2,658 2,743 2,771 2,922 3,015 3,112 3,211 3,314 3,420

Goats 2,792 2,931 3,077 3,199 3,230 3,560 3,925 3,923 3,997 4,196

Cattle 1,288 1,288 1,302 1,315 1,330 1,344 1,359 1,373 1,392 1407

Pigs 339 332 324 312 310 303 297 290 477 491

Source Veterinary Services Directorate, (2007) MoFA, Accra

3

Table 1.2: Annual domestic meat production (1000 Metric) 2001-2006

Type of

Livestock

2001 2002 2003 2004 2005 2006

Cattle 19.1 18.3 18.5 18.5 18.9 19.1

Sheep 12.8 13.2 13.6 14.0 14.5 14.9

Goat 12.0 12.6 13.9 15.3 15.3 15.6

Pig 9.7 10.4 10.2 10.0 9.7 10.6

Poultry 14.6 19.4 21.1 23.0 22.7 27.2

Milk* 34.2 34.6 35.1 35.5 36.0 36.5

Egg* 22.3 23.3 24.4 25.2 25.2 25.7

Source SRID, (2006) and computations from Livestock Production data *Source:

FAOSTAT, accessed December 2007

Comfort though may be drawn from the awareness which seems to be growing among

consumers, who increasingly demand quality and safety when they can afford; but the

discomforting truth lies in the fact that such maladies as diarrheal diseases, the prevalence

of which according to Kennedy (2003) is indicative of a poor food safety state of affairs,

continue to be one of the most excessive causes of morbidity in Ghana (Tables 1.3 & 1.4),

resulting quite often in deaths.

4

Table 1.3: Top 5 causes of morbidity in Ghana 1995-2007

Year Top Five Causes of Morbidity in Ghana

1995 1.Malaria

2.Upper respiratory tract infection

3.Diseases of skin & ulcers

4.Diarrheal diseases

5Accidents (Fractures and Burns)

1996 1.Malaria





1997 1.Malaria





1998 1.Malaria





1999 1.Malaria





2000 1. Malaria





2001 1.Malaria





Source: Epidemiological Department (1995- 2007), MoH, Ghana. 2004 not available*

5

Table 1.4: Top 5 causes of morbidity in Ghana 1995-2007

Year Top Five Causes of Morbidity in Ghana

2002 1. Malaria

2. Acute Respiratory Infection

3. Skin Diseases and Ulcers

4. Diarrheal Diseases

5. Hypertension

2003 1.Malaria

2.Acute respiratory

3.Skin Diseases & Ulcers


5.Hypertension

2005 1.Malaria

2. Acute Respiratory Tract Infection

3. Diarrheal Diseases

4. Skin Diseases and Ulcers

5. Hypertension

2006 1.Malaria

2.Acute Respiratory infection


4.Skin Diseases and Ulcers

5.Hypertension

2007 1.Malaria

2.Acute respiratory infection

3.Skin Diseases and Ulcers

4.Hypertyension

5.Diarrheal disease

Source: Epidemiological Department (1995- 2007), MoH, Ghana. 2004 not available*

One ASF of concern is raw cow‘s milk. Its functions though are several including growth,

supply of energy, reproduction, maintenance and repairs, and appetite satisfaction

(O‘Connor, 1994). It has also been referred to as the most nearly faultless food elaborated

by nature because of its exceptional nutritional qualities (Forster et al, 1958). However,

apart from having the potential to cause FBD‘s just like all other foods (CAC/RCP 57-

2004), it has been found to be solely responsible for a lot more sicknesses than all other

6

foods taken together, a fact hardly surprising as it is just about the sole ASF consumed raw

(Hattie, 1927). It presents an excellent medium for bacterial growth and thus is an

important source of several significant zoonotic/ bacterial infections when consumed

without pasteurization (Donkor et al., 2007). Among the numerous bacterial diseases

frequently associated with its consumption is Listeriosis (WHO, 1962) caused by Listeria

monocytogenes. Other bacterial diseases also catalogued by the WHO can be found on

Table 1.5.

Table 1.5: Bacterial diseases transmissible to man through milk consumption

Diseases Principal sources of infection

Man Animal Environment

Cholera X

Diphtheria X

Shigellosis X

Typhoid fever X

Patho. E. coli Infection X X

Paratyphoid fever X X

Salmonellosis X X

Staph. Entero. Gastroenteritis X X

Streptococcal Infections X X

Tuberculosis X X

Anthrax X

Brucellosis X

Leptospirosis X

Listeriosis X

Botulism (toxin) X

Clostridium perfringens

Infection

X

Enteritis (non-specific) X

Rat-bite fever X

Source WHO, 1962

7

1.2 Risk Profile of L. monocytogenes

Listeriosis, in humans, is a group of disorders caused by a small, short Gram-positive, non-

spore-forming, non-acid fast, rod-shaped bacterium, Listeria monocytogenes (Winter et al.,

2004) with an annual incidence of 1.6 - 6 cases per million people (Rocourt et al., 2000). It

has been found in at least 37 mammalian species, 17 bird species, and both fish and

shellfish; and is also believed to be present in up to 10 percent of humans (CFSAN, 1992)

of which 3-10% present no signs of illness (Santiago et al., 1999).

Being recalcitrant to several environmental stresses, it is widely distributed in nature and

has been isolated from as many sources including mud (Weis and Seeligeri, 1975), water

(Dijkstra, 1982), decaying vegetation (Welshimeri, 1968) and silage (Gronstol, 1979). It

resists the deleterious effects of freezing, drying and heat to remarkable extents (CFSPH,

2005). It has a temperature growth range of -0.5 to 45 °C (Petron and Zottola, 1989), with

an optimum at 30°C- 37°C (Juntilla et al., 1988). It therefore defies decades old

conventional wisdom which held that food stored under refrigerated temperatures (< 7°C)

would remain safe as pathogenic bacteria could not grow under such conditions (Marth,

1998). Likewise, to the other temperature extreme, a study by Fleming et al., (1985) also

suggests that the efficiency of pasteurization could be directly correlated with the level of

contamination. L. monocytogenes is also capable of growth in 10% NaCl solution (aw =

0.94) and survive in 20% NaCl solution (aw = 0.88). It could grow in acidic media, with pH

as low as 4.3 (George et al., 1996) and can tolerate a pH as low as 3.6 (CFSPH, 2005).

8

Thus, the ingestion of improperly fermented or moldy silage has become recognized as a

primary source of listerial infection in sheep, goats and cattle (Felon, 1986) where it

presents such symptoms as abortions, septicemia, and with central nervous system (CNS)

involvement facial paralysis with profuse salivation, circling, in-coordination, and head

pressing or turning of the head to one side (CFSPH, 2005). Consequently, the relation

between ingestion of listeriae-contaminated silage, mastitis in dairy cattle and subsequent

asymptomatic shedding of listeriae in milk destined for human consumption has been

noted (Arimi et al., 1997). This organism can also establish itself in food processing

environments by forming biofilm making sanitation difficult (Blackman and Frank, 1996)

and thus contamination could occur where hygienic regimen is inadequate.

L. monocytogenes is an emerging food-borne pathogen (WHO, 2002). However, it was not

until the 1980‘s that its significance as a foodborne pathogen was recognized when

evidence of outbreaks were traced to food though it had long been known as an animal

pathogen (Schlech et al., 1983). Ironically, its contamination of food soon became a major

cause of food recalls. According to Wong et al., (2000) between 1994- 1998 contamination

with L. monocytogenes was the leading cause of food recalls by the FDA.

Listeriosis, the group of disorders caused by this organism, may be non-invasive and take

the form of gastroenteritis characterized with such symptoms as chills, headaches,

diarrhea, abdominal pain and cramps, nausea, vomiting, fatigue, and myalgia. However, it

prefers to occur in the invasive form with severe, potentially fatal symptoms (Doyle,

2005). Predominant clinical manifestations of human listeriosis are meningoencephalitis,

9

septicaemia and abortions. The mortality rates for healthy humans could be 20-30% but

could reach as high as 80-99% in immunocompromised individuals (Gray and Killinger,

1966). Fetal infection can also result in premature births, spontaneous births, still births, or

early-onset neonatal listeriosis with a mortality rate of 20-30% (Lober, 1997). The baby

may also be born asymptomatic but may develop fatal form of meningitis after several

weeks due to infection at delivery (Gellin et al., 1991). Other conditions reported include

septic arthritis, osteomyelitis and pneumonia (CFSPH, 2005).

L. monocytogenes accounts for just about 2,500 illnesses (<1%) of an estimated 76 million

annual cases of FBD‘s in the United States of America, yet it is responsible for about 500

(27.6%) of related deaths per year (Mead et al., 1999). Also, with an increase from 90.5%

in 2000 (USDA, 2005) to 97.0% (CDC, 2006), it easily still continues to be culpable for

the highest rates of hospitalizations among the foodborne diseases tracked by the FoodNet,

only followed remotely by Shiga-toxin producing Escherichia coli (STEC 0157) at 42%.

Almost all cases (i.e. about 99%) of listeriosis are associated with food consumption

(Mead, et al., 1999) and as reason would have it the organism has been isolated from

various foods of both plant and animal origin (Farber and Peterkin, 1991) with high-risk

foods having the potential for contamination, supporting its growth in high numbers, being

stored under refrigeration for extended periods and do not require further preparation

before consumption (ILSI, 2004). Thus, L. monocytogenes has been associated with raw

vegetables, fermented raw-meat sausages, raw and cooked poultry, raw meats, raw smoked

fish and dairy products (Farber and Peterkin, 1991). Flemming et al., (1985) further

10

emphasized the rather special link between dairy products and Listeriosis. Probably its

worst outbreaks in the US, resulting in 28.3% and 33.8% mortality rates, were linked to the

consumption of dairy. In the first, Mexican self-styled cheese was responsible for nearly

300 cases, including 85 deaths (Ryser, 1999). Also in the second, out of 142 cases, 48 died

(Linnan et al, 1988). Illegally manufactured cheese from a mixture of raw and pasteurized

milk in an environment contaminated with listeriae was the culprit.

1.3 Statement of Problem

Whilst a rapidly growing population (2.7%), increasing urbanization (43.8% in 2000)

(Asante, 2004) and rising income levels suggests a high demand for livestock products

(WHO, 2003), indications are that the per capita consumption of these products continue to

be stagnated in Ghana (FAO STATS, 2009). This could suggest an unsatisfied demand as

estimates are that Ghana is not self-sufficient in animal products (NMTIP, 2005), having to

rely on imports to partially make up for shortfalls (Ghana FAO/ WB CP, 2005). To the

country, this could imply an ever increasing cost of food importation bill dependent on the

foreign exchange earnings (Asante, 2004) and to the consumer, could be contingent on the

availability of disposable income (Omore et al, 2003). As per the exposé, consumption of

dairy in Ghana has been low; it was 6kg LME (Liquid Milk Equivalent) which is far below

the 120kg for sub-Saharan Africa (Omore, et al., 2003).

Ironically, local production does not meet demand (Ghana: FAO/ WB CP, 2005).

Nevertheless, as part of the Agriculture sector, it contributes immensely to food security in

the country (Asuming- Brempong, 2003) and its production in Ghana is mostly pastoral

11

and agro-pastoral (Tonah, 2003) requiring no complementary feed (Ghana: FAO/ WB CP,

2005). Though this could imply that associated costs are quite low as it is down to the

availability of grass on open pasture, such free-range feeding makes it difficult to apply

conservative measures to ensure production of wholesome milk devoid of zoonotic and

other contaminating microorganisms to guarantee consumer safety (Grimaud et al., 2005).

Ensuing milk handling practices also greatly influence the proliferation of these pathogens.

Abraham and Laryea (1968) reported an approximate mean count of 1.97 x 104 per ml for

milk produced by the University of Ghana Agricultural Research Station in comparison to

3.0 x 106

per ml to that produced by the Fulani Kraals, also on the Accra plains. The latter

however is anticipated to produce the bulk of milk in the country (Omore et al., 2002) of

which over 80% ends up on the informal markets (Omore et al. 1999) where Omore et al.,

(2003) have described how hygienic practices could be both poor and expensive. Besides,

one can neither refute the likelihood of post-pasteurization contamination (Omore et al.,

2003) nor the lack of pasteurization (Donkor et al., 2007) in such market channels. On the

other hand, as or when heating of the milk was done, it may not be adequate since this

practice has not been standardized and heat-injured L. monocytogenes have been shown to

be able to grow during latter storage as reported by Garayzabel et al, (1987).

Furthermore, consumers do not receive instructions on safe handling of dairy products sold

on such markets as required by the Code of Hygienic Practice for Milk and Milk Products

(CAC/RCP 57-2004). This does not disparage the difficulty such an endeavor would have

as Omore et al., (2003) observed the lack of formal education among agents on such

12

markets. Yet generally, except for psychrotrophs, proliferation of bacteria could be

suppressed if milk is kept properly chilled (LeJeune and Raja, 2009); but alas it is not

(Ghana: FAO/ WB CP, 2005).

Therefore, rising concerns on issues of safety and quality of such dairy products has

adversely affected patronage (Donkor et al., 2007). In the two major cities in Ghana (Accra

and Kumasi), Donkor et al (2007) found that these dairy products could carry pathogenic

bacteria after isolating Yersinia sp. (19.8%), Klebsiella sp. (16.7%), Proteus sp. (7.3%),

Enterobacter sp. (6.3%), Escherichia coli (2.1%), Staphylococcus sp. (14.6%) Bacillus sp.

(11.5%) and Mycobacterium sp. (1%) among others from 96 samples analyzed.

Notwithstanding this, consumption has increased, and consumers, while expecting better

safety relative to other food channels, have shown good faith by paying more for fresh

local products as compared to that from imported processed milk powder (Ghana: FAO/

WB CP, 2005). Hence, it is submitted that efforts should be made to enhance the safety

and quality of domestic milk production. Ultimately, this could contribute to achieving the

broader objectives of poverty reduction, development of sustainable use of natural

resources, and food security, which are key to NePAD of which Ghana is a signatory.

This work is all the more vital not only because of the anticipated lack of pasteurization

(Sampane-Donkor, 2002) and the potential for post-pasteurization contamination (Donkor

et al., 2007) but also the lack of adequate refrigeration along informal milk marketing

channels which could promote the growth of psychrotrophs. Hence the essence of

13

establishing the significance of this pathogen as part of efforts to ensure food safety and

safeguard public health, especially in a country where any impact could easily assume

other dimensions, and resources it seems do not nearly abound as do their dearth.

1.4 Scope

This study quantitatively assessed the risk of consuming dairy products contaminated with

L. monocytogenes from the informal markets at Ashaiman using a stochastic model and

determined the best control option to reduce the risk by simulation with the risk model.

1.4.1 Specific Objectives

i. Estimation of the prevalence and level of L. monocytogenes in informally marketed

milk/ milk product

ii. Estimation of the level of the risk of consuming informally marketed milk

contaminated with L. monocytogenes

iii. Identification of the potential sources of contamination of informally marketed

milk

iv. Determination of possible recommendations for intervention/ mitigation strategies

14

CHAPTER TWO

LITERATURE REVIEW

2.1 Agriculture Sector in Ghana

Annual GDP comparison of the various sectors of the economy rendering the WB

Development Data, Ghana Data Profile and Details of the Agriculture sector from the BoG

Annual Report (2006) reveals that this sector directs the country‘s economy (Fig 2.1).

Furthermore, over 90% of food needs of the country are provided for by it (Oppong-

Anane, 2001) either directly (by making food available by supplying food commodities in

full or in part, and contributing to foreign exchange incomes used for importing shortfalls)

or indirectly (by creating avenues for earning income, and contributing considerably to

food prices critical to household food security) (Asuming- Brempong, 2003).

Unfortunately, it is still rudimentary and dominated by smallholder food crop/ livestock

farmers (SRID, 2001) who represent the group with the highest poverty incidence at 59%.

Figure 2.1: Comparism of various sectorial GDP’s with the national economic growth

15

2.1.1 Livestock sub-Sector in Ghana

Livestock is an important part of the livelihoods of most Africans. Its socio-economic and

cultural significance in the lives and livelihoods of smallholder farmers, processors and

traders cannot be derided. In farming communities ruminant livestock is a partial display

of wealth, used for payment of dowry, and acts as a bank and insurance in times of

difficulty. Sheep and goats are often killed for various ceremonies such as births, funeral

and marriages (MoFA, 1990). In Ghana, estimates are that about 1.5 million households in

1999 had livestock (Asante, 2004).

2.1.2 Production and Consumption of ASFs in Ghana

The increased ASFs production in Ghana is an indication of a commensurate increase in

demand as she barely exports such products. However, production has not caught onto

consumption and hence the need for importation (Ghana: FAO/ WB CP, 2005), a trend

seemingly limited only by access to foreign exchange. Some indications are that demand is

so high that not even the hide of animals is spared as food material (Hogarh, et al., 2008).

2.1.3 Meat and Meat Product Consumption in Ghana

According to SRID (2001) Ghana produced an estimated 66,283 MT of meat and meat

products in the year 2000 of which beef contributed about 27%, mutton about 18%, goat

and pig meat about 17% each, and poultry meat about 21%. With milk production

however, they represented only about 30% of the national animal protein requirement.

Further rendering the VSD Annual Report (2007) domestic production of meat of

18,875MT in 2005 was more than double the quantity imported to make up for short falls

16

(at 8,588.8MT). The following year though imports due to shortfalls almost doubled to

15,302.8MT whiles domestic production managed only a marginal increment of less than

2% to 19,140 MT. Subsequently, the year 2007 imports now stood at 24,359.4MT in

comparison to 19,346 MT for local production (Table 2.6). This was an indication of the

nation‘s ever-growing demand for ASFs and also its dependency on foreign imports.

Table 2.6: A comparison of domestic production and imports (000) MT (2000/07) 2000 2001 2002 2003 2004 2005 2006 2007

Domestic

production

18,570

19,053

18,288

18,486

18,686

18,874

19,140

19,346

Imports 869.5 154.2 1,063.5 1,362.1 3,756.0 8,588.8 15,302.8 24,359.4

Total 19,439.5 19,207.2 19,351.5 19,848.1 22,442.0 27,462.8 34,442.8 43,705.4

Source VSD Annual Report, 2007

2.1.4 Milk and Milk Product Consumption in Ghana

In Africa, the development of dairy has been hindered by marketing constraints

(International Development Research Center (IDRC), 1984). Efforts aimed at addressing

these obstacles have historically focused on the establishment of large scale centralized

processing plants to meet the liquid milk demand of urban dwellers (von Marsow, 1985).

Yet, the failure of collection systems and unattractive prices offered for locally produced

fresh milk have made them dependent on imported butter oil and skim milk powder.

Ghana‘s case was no exception (Ghana: FAO/WB-CP, 2005). This has been coupled with

milk surplus and deficit areas that according to Omore et al., (2003) presented a difficult

situation for its marketing. This was attributed to an inefficient transportation of milk

which led to deterioration. Flow of milk and milk products to consumers along the formal

17

food sector was based on the importation of milk powder, butter and cream (Ghana: FAO/

WB CP, 2005). The other conduit depended on local production based mainly on

indigenous breed cows with low yield (1-2L/day) during 100- 150 days per annum.

However, substantial quantities of milk were able to be collected by adding milk from

several thousands of low-yielding cows (Okantah, 1992). Most of this milk was consumed

by the family locally or processed for sale on the informal markets.

These local markets traditionally have targeted the Fulani communities, but increasingly

too other unconventional consumers who have developed the taste for the dairy products.

Hitherto, populations in the coastal and southern parts of the country had not been known

for dairy consumption as Trypanosomiasis and other diseases made cattle keeping costly.

But as northerners migrated down south and Western-style dairy products were introduced

dairy product consumption also grew countrywide (Omore et al., 2004).

2.2 Informal Milk Marketing in Ghana

According to Omore et al., (2004), traditional dairy product markets characteristically

differed in several key ways. This depended on the types of product(s) handled, number of

intermediaries involved, and the role each plays. In Ghana, such markets are characterized

by an enormous array of market intermediaries, playing somewhat different but often

overlapping functions distinguished by scale of operation and clientele (Omore et al.,

2004). Some main types of milk marketing agents in Ghana are found on Table 2.7.

18

Table 2.7: Informal milk market agents in Ghana

Types of sellers Description

Producer-seller Producers who also sell their milk. In Ghana,

herdsmen or their wives who sell their own milk at

the Kraal or in the village, rural town or road-side.

Private Wholesalers/ Assemblers These buy milk in bulk from producers or from rural

Assemblers and sell it to Retailers. No chilling is

used. They are bulkers in the marketing chain

Retailers Retailers present milk to consumers in the smallest

desirable quantity, and in a convenient form and

location. These are largely open-air road-side sellers

Fura sellers These food-drink sellers are mainly in urban centers

of Ghana. They buy milk from the kraal, Assemblers

or from wholesalers and retail it combined with balls

of cooked cereal, Fura, as a snack or meal.

Source Omore et al., 2003 (Abridged version)

Significantly, most milk collected was sold directly to individual consumers at the farm

gate/ Kraal and any excess was often taken to other sale points to sell. House delivery is

mainly to local processors (referred to as makers of traditional cheese ―wagashi”, who

operated from their residences), milk Assemblers and Consumers who had a supply

contract with the milk seller. Stockmen deliver fresh milk daily to these buyers. Stockmen

who do not have established buyers or who could not hawk their milk often assembled at a

place in the center of town to sell their produce. An example is at Tulaku, Ashaiman

(Omore et al., 2003) where Omore et al., (2004) have noted the sale of raw fresh milk,

boiled milk, naturally fermented milk products (i.e. Nunu and Nyarmie), wagashi and ghee.

19

2.2.1 Handling of Milk/ Milk Products in Ghana

Producer-herdsmen mostly used plastic buckets to receive milk during milking though

calabashes or aluminum bowls were also used. Milk procuring agents also used various

vessels yet plastic gallons and jerry cans were the most preferred. These are prone to

bacterial contamination. Less than one per cent used the recommended aluminum milk

cans/ churns (Omore et al., 2003). Reports by Abraham and Laryea, (1968) and Donkor et

al., (2007) among others indicated poor hygienic handling of raw milk in the country.

2.3 Microbial Ecology of Raw Cow’s Milk

Milk is virtually sterile when secreted into the alveoli of the udder from specialized cells of

the mammary gland where it is synthesized (Tolle, 1980). Hereafter, milk produced is

vulnerable to microbial contamination from three main sources (Bramley and McKinnon,

1990); from within the udder, from the exterior of the udder and from the surface of milk

handling and storage equipment. Also, during storage, microbial contaminants could

multiply and increase in numbers (Murphy and Boor, 2008). These and other factors such

as seasonality (Psoni et al., 2003) and geographic locality (Poznanski et al., 2004) affect

the microbial composition of raw milk and consequently of raw milk products.

Bacteria are the most encountered group of microorganisms in milk where they play

various functions, some of which are beneficial and others harmful. These include

spoilage, processing (e.g. fermentation) and causing of FBD‘s (O‘Conner, 1994).

However, it is rather their infamous role of the latter that has gained them much popularity

and notoriety as far as public health safety is concerned. About 90% of all dairy-related

20

illnesses reported are of bacterial origin (Headrick et al., 1998). Fortunately, most of these

disease causing bacteria can be eliminated from milk by pasteurization (USDA, 1981).

2.3.1 Milk Pasteurization (Low-Heat Treatment)

Pasteurization is the application of heat to food at temperatures that would destroy non-

spore forming pathogenic micro-organisms (Jay et al., 2005). All portions of the food is

heated to at least the minimum required temperature and held there for at least the

minimum required time. In Ghana a large part of milk processed is correctly pasteurized as

directed by the Ghana Standards Board (GSB) (i.e. 85ºC for 30minutes) (Ghana FAO/ WB

CP, 2005). Unfortunately, this excludes local dairy products sold on the informal markets

from whom the risk of zoonoses exists as Donkor et al., (2007) concluded.

2.4 Foodborne Zoonoses in Ghana

2.4.1 Anthrax

Anthrax is a zoonotic disease both of mammals and humans caused by Bacillus anthracis.

In Africa, outbreaks involving both domestic and feral animals are quite common

(Turnbull et al., 1991). Frequent outbreaks have occurred in livestock in Ghana especially

in the northern regions (Opare et al., 2000) despite the long history of local anthrax spores

vaccine production by the VSD (VSD Annual Report, 2003). These outbreaks are often

strongly associated with outbreaks in humans claiming more than thousand lives (Opare et

al., 2000). The WHO (2009) has indicated a possible link with animal tissue consumption.

21

2.4.2 Tuberculosis (TB)

Though infection with other members of the Mycobacterium tuberculosis complex and

several variants could cause Tuberculosis (TB), Mycobacterium tuberculosis accounts for

most human TB cases (de la Rua- Domenech, 2006). In Africa bovine tuberculosis has

been a major cause for concern (Benkirane, 1998). Limited data available suggests that at

least 10% and in some villages up to 50%, of Human TB was caused by M. bovis

infection, yet rarely has the disease been associated with infection in cattle (Wastling et al.,

1999). In 2002, the OIE declared 692 human cases of bovine TB in Ghana (Ghana: FAO/

WB CP, 2005). Compared to the annual incidences of human TB that year, its worth is

startling considering a potential contribution of >10% to the human cases (Table 2.8).

Table 2.8: Human Tuberculosis reported in Ghana, 1995-2007

Year Number of human disease of TB

1995 8388

1996 7254

1997 7930

1998 7890

1999 7191

2000 6905

2001 8412

2002 7564

2003 7487

2004 6458

2005 7592

2006 6067

2007 8391

Source: Morbidity Data, Epidemiological Department, MoH, 1995- 2007, Ghana.

2.4.3 Brucellosis

Brucellosis is a disease caused by organisms of the genus Brucella, and frequently enough

the species abortus has been implicate in bovine brucellosis (Berman, 1981). Infection was

22

usually occupational in humans, and for those that did not frequently come into contact

with animals, tissues and bacteria, another recognized route of infection was by ingestion

of unpasteurized dairy products (CFSPH, 2005). According to Omore et al., (2002) as

long as the practice of consuming fresh unpasteurized milk or unboiled milk continues to

be widespread in Ghana, the risk of acquiring zoonotic diseases such as brucellosis through

milk consumption was still considerable. This was concluded finding that overall 30.5%

and 25.0% of milk samples tested by the Milk Ring Test (MRT) and ELISA, respectively

had brucella antibodies.

2.4.4 Other Emerging Foodborne Zoonoses in Ghana

There are however other zoonoses that increasingly also demand attention. These include

the threats of Toxoplasmosis caused by Toxoplasma gondii, and Listeriosis caused by L.

monocytogenes. Wastling et al., (1999) has documented that quite a number of recent

studies indicated a high seroprevalance of T. gondii in pigs and goats in Ghana (up to 40%)

whiles Osei-Somuah et al., (2000) have also isolated Listeria sp. from sheep (which were

food animals), on the Accra plains. The ill-fated anticipation was for the significance of the

latter to increase even more as refrigeration becomes ever more the major means of food

storage.

23

2.5 Rapid Rural Appraisal (RRA)/ Participatory Rural Appraisal (PRA)

2.5.1 Participatory Approach

There has been a lot of scientific effort aimed at improving animal health and ultimately

safeguarding public health. These researches in the recent past have been quantitative in

nature and often time consuming and expensive requiring extensive physical or social

sampling at high costs. Moreover, these are seldom flexible: once designed and initiated,

leaves little room for adjustments, and inappropriate or ineffective enquiries cannot be

deleted. The research team was thus stuck with the process until its completion (Chambers,

1983). Thus the importance of its result was not guaranteed. To address this situation

alternative systems of inquiry have since been developed which include Rapid Rural

Appraisal (RRA) and Participatory Rural Appraisal (PRA) which, to varying extents, enable

local people to assume more active roles in defining, analyzing and solving their own

problems. From RRA to PRA, the researcher‘s role modifies from being predominantly an

‗extractor‘ of information to a facilitator of community development. Key among the

principles of PRA were that of rapid cumulative learning, direct contact, reversals, optimal

ignorance and appropriate imprecision, and triangulation. These have led to the

development and use of methods that are uniquely user friendly. Examples include

analytical games, workshops (e.g. with key informant), diagrams (e.g. mapping), semi-

structured questionnaires (e.g. checklist) and direct and participants observations (or do-it-

yourself activities). Analysis of collected data depended on its nature. Qualitative data

could be categorized into mutually exclusive groups and analyzed whiles simple statistical

analysis may be done for quantitative data (Bhandari, 2003). Donkor et al., (2007), which

assessed the bacterial contamination of informally marketed raw milk in Ghana, was

facilitated by application of PRA methods.

24

2.6 Microbial Risk Assessment

Microbiological Risk Analysis (MRA) is a process consisting of three components: Risk

Assessment, Risk Management, and Risk Communication, with the overall objective to

guaranteeing public health protection. The Codex Alimentarius Commission document

CAC/GL-30 (CAC, 1999) defined risk assessment for microbiological hazards in foods as

a scientifically based process with four components: hazard identification, exposure

assessment, hazard characterization, and risk characterization (Figure 2.2) (CAC, 1999).

Figure 2.2: Protocol for microbial risk assessment (CAC, 1999)

However, a very important first step relevant to risk assessment is the risk profile, the

purpose of which is to inform the decision on what further scrutiny is needed and whether

Risk profile

Hazard Identification

Hazard

characterization

Exposure assessment

Risk characterization

25

resources should be allocated to a more detailed scientific assessment (FAO/WHO, 2002).

Information included here are facts on the microbiological hazards of concern, their source

or pathway of entry to the food chain, and the difficulties faced in controlling them; an

indication of the available data on prevalence and numbers of the microbial hazard of

concern in the food chain; disease incidence data and the type and severity of adverse

effects; at-risk populations; and possible control options available (CAC, 2007).

The hazard Identification (H.I) qualitatively evaluates microbial hazards of concern in

food. These include infectious agents and toxins produced. For emerging microbial hazards

H.I must be fully developed. Yet, as the food-pathogen combination for most are

established this could be direct and simple if a comprehensive risk profile has been

developed as part of the management process (WHO/ FAO, 2008) as done in section 1.2.

Hazard characterization (H.C) quantitatively and qualitatively evaluates the severity and

consequences of the adverse effects that may result from ingestion of a microorganism and

a dose-response relationship. It also gives information on the pathogenicity of the organism

and the food matrix and its predisposition to contamination. Exposure Assessment (E.A)

provides an estimate of the probability that an individual or a population would be exposed

to a microbial hazard and the numbers of organisms that are likely to be ingested

(Lammerding and Fazil, 2000). Risk Characterization (R.C) is the assimilation of the

Hazard Identification, Hazard Characterization and Exposure Assessment to estimate risk

(i.e. an estimate of the likelihood and severity of the adverse effects that occur in a given

population, with associated uncertainties).

26

2.6.1 Risk Assessment of L. monocytogenes-- a Foodborne Pathogen

2.6.1.1 Hazard Identification (H.I)

In March 1910, Gustaf Hülphers, a veterinarian, described a bacterium that caused necrosis

of the liver after performing autopsies on two rabbits. He named the bacterium bacillus

hepatis because of its affinity to the liver, from where he had isolated it (Hülphers, 1911).

It was non-spore- forming, non-acid-fast short rod with optimum growth temperature of

37°C- 38°C and was a facultative anaerobic. It was provided with a cilium and had a

distinguishing motility pattern. Murray et al., (1926) isolated the same organism from

laboratory rabbits after autopsies. They named it Bacterium monocytogenes. Pirie (1927)

isolated the same organism from gerbilles. The disease caused was termed ‗Tiger River

Disease‘ as it was discovered near the Tiger River in South Africa. The causative Gram-

positive organism was named Listerella hepatolytic. The two species were identical. Pirie

(1940) named it Listeria monocytogenes. Its first isolation in humans was in 1929 (Nyfeldt,

1929). Other species of the Listeriae (Table 2.9) were discovered after 1961.

2.6.1.1.1 Characteristics of Listeriae

All species of Listeria produce catalase though some catalase-negative strains of L.

monocytogenes have been isolated (Hogan et al., 1998). L. monocytogenes, L. seeligeri and

L. ivanovii hemolyse red blood cells on blood agar; L. monocytogenes and L. seeligeri

produce a narrow zone of hemolysis while a wider zone surround colonies of L. ivanovii.

Sugar fermentation tests are also important in differentiating between them (Table 2.9). L.

monocytogenes is the main human pathogen (Jones et al., 2008) even though L .ivanovii

and L. seeligeri has at least once been associated with listeriosis (Cummins et al., 1994).

27

Table 2. 9: Characteristics of the Genus Listeria

L.

monocyt

ogenes

L.

innocua

L.

seelige

ri

L.

welshi

-meri

L.

grayi

L.

ivanovii

subsp.

ivanovi

L.

ivanovii

subsp.

londoniensis

Tumbling

Motility

+ + + + + + +

Catalase

production

+ + + + + + +

Haemolysis + - + - - + +

CAMP-test

(Staph.

Aureus)

+ - + - - - -

CAMP-test

(Rhodococcus

equi)

- - - - - + +

L-rhamnose + D - d - - -

D-xylose - - + + - + +

Hippurate + + - + +

Ribose - + -

Source: Seeliger and Jones (1986).

2.6.1.1.2 Isolation and Detection of Listeriae

A definitive diagnosis of listeriosis is when the organism is isolated from a normally sterile

site (usually blood, placenta or cerebrospinal fluid) from a patient with a compatible illness

(Anon, 1997). However, the identification of L. monocytogenes as having caused it via

food is made complex due to the high carrier rate in humans. Thus, the organism must be

isolated from food for confirmation (FDA/CFSAN, 2003). This is very difficult as food

could be heavily contaminated with other bacteria as well. Therefore standard

identification relies on selective enrichments and biochemical identification (Almeida and

Almeida, 2000). Selective enrichment restrains numbers of contaminating organisms

whiles encouraging the multiplication of Listeriae to allow for detection (OIE, 2008).

28

To this end, selective enrichment agents which allow for growth of the organism at normal

incubation temperatures (OIE, 2008) are employed. Examples are cycloheximide, lithium

chloride, nalidixic acid and acriflavine (AFNOR, AOAC, 2000; Hitchins, 1998). This has

led to the development of a variety of conventional methods whose major differences

appear to be how which type(s) of selective enrichment agent(s) are applied (Donnelly,

1999). Selective enrichment, either one- or two-step, is performed at 30–37°C. Enrichment

media used include Listeria Enrichment Broth (LEB) [Lovett et al. (1987); McClain and

Lee (1988)] and Fraser Broth (Fraser and Sperber, 1988). They contain the inhibitory

agents nalidixate and acriflavine but the latter contain also lithium chloride for selectivity

and ammonium citrate for detecting hydrolysis of Esculein leading to blackening of the

broth.

Subsequently, broth is spread on solid media plates also containing Esculein. Commonly

used are Oxford (Curtis et al. 1989) and PALCAM (van Netten et al. 1989) though there

are others such as the Listeria selective agar (LA) (Curtis et al., 1989). On PALCAM

Listeriae colonies are approximately 2 mm grey-green with a black sunken center and a

black halo on a cherry-red background. Depending on the numbers, the entire media may

turn black. On the OXA L. monocytogenes forms 1 mm diameter black colonies

surrounded by black haloes after 24 hrs. At 48 hrs colonies are 2-3 mm in diameter, black

with a black halo and are also sunken at the center (Pagotto et al., 2002)

Further tests have been developed that can even differentiate between Listeriae. These do

not only include L. monocytogenes blood agar, LMBA, (Johansson 1998) which employs

29

the hemolytic activity of listeria to distinguish between Listeriae and other organisms and

also between the Listeria sp. but also chromogenic media such as BCM, and ALOA/

OCLA. Under this category are two groups: the first utilizes the cleavage by PI-PLC of L-

α-phosphatidyl-inositol, forming a white precipitation zone around the colony, combined

with the chromogenic substrate 5-bromo-4-chloro-3-indoxyl-β-glucopyranoside for

detection of β-glucosidase, which occurs in all Listeria sp. All Listeriae produce turquoise

colonies on these media which include ALOA™, CHROMagar™ Listeria, BBL™

CHROMagar™ Listeria, and OCLA (Reissbrodt, 2004)

2.6.1.1.3 Morphology of Listeriae

Listeriae could appear coccoidal or filamentous (Rocourt, 1999). Cells may be found

singly or in short chains. Rods range between 0.4-0.5 μm in diameter and 0.5-2.0 μm in

length. On nutrient agar (after 24 hrs incubation) colonies appear round, 0.5-1.5 mm in

diameter, translucent and with a smooth shiny surface. It appears rough and increases to 3-

5 mm in diameter after 3-7 days. On dextrose, it is grey-white with a sour milk odor (Gray,

1956). On blood agar, it is enclosed by a hemolysis zone (Parihar, 2008).

2.6.1.1.4 Prevalence of L. monocytogenes in Cow’s Milk

Generally prevalence of Listeriae show wide variations in several foods. van Kessel et al.,

(2004), ascribed this as possibly reflecting differences among regions or because of

among-studies sample type or analytical methods. In a more recent study, Rodriguez-Otero

et al., (2007) detected Listeria spp. in 16.3% of bulk-tank milk samples, a much higher

prevalence than that previously reported in other related studies including 12.4% in Canada

http://jds.fass.org/cgi/content/full/90/11/5083#VAN-KESSEL-ETAL-2004


30

(Farber et al., 1988), 4.1% in Finland (Husu, 1990), 8.3% in Ireland (Rea et al., 1992) and

10.4% in the United States (van Kessel et al., 2004). They found L. monocytogenes in

6.1% of tanks, which had exceeded the previously reported 3.6% (Gaya et al., 1998) in

Spain, 1.3% in Canada (Farber et al., 1988), 2.2% in Finland (Husu, 1990),

4.1% in the

United States (Rohrbach et al., 1992), 4.6% in the United States (Jarayao and Henning,

2001), 1.5% (Deutz et al., 1999) in Australia, and 1.7% (Adesinyun et al., 1996) in India,

albeit analogous to 6.5% in a recent study in the United States (van Kessel et al., 2004).

2.6.1.2 Hazard Characterization

Illness due to an exposure to a foodborne pathogen is dependent on the integration of

pathogen, host and food matrix effects (i.e. the infectious disease triangle). These factors

also affect the nature and consequence of the disease (i.e. invasive/ non- invasive illness).

2.6.1.2.1 Pathogenicity of L. monocytogenes

Usually, a typical infection begins with ingestion of L. monocytogenes via contaminated

foods which is able to endure the exposure to the host's proteolytic enzymes in the

stomach, a highly acidic environment (pH 2.0), bile salts and non-specific inflammatory

attacks. Its ability to survive and go pass this stage relies on a protein subunit of RNA

polymerase (RNAP) — alternative sigma factor σB (encoded by sigB) — that controls

stress-response genes (opuCA, lmo1421 and bsh) and linked proteins (Sleator et al., 2003).

Subsequent to the ingestion, L. monocytogenes adheres to and enters host cells both

passively through phagocytosis and actively through actions of listerial surface proteins

http://jds.fass.org/cgi/content/full/90/11/5083#FARBER-ETAL-1988

http://jds.fass.org/cgi/content/full/90/11/5083#HUSU-1990

http://jds.fass.org/cgi/content/full/90/11/5083#ROHRBACH-ETAL-1992

http://jds.fass.org/cgi/content/full/90/11/5083#JARAYAO-AND-HENNING-2001

http://jds.fass.org/cgi/content/full/90/11/5083#JARAYAO-AND-HENNING-2001


31

called internalins (Lecuit, 2005). Found on the listerial surface, Inl A binds itself onto the

surface protein E-cadherin on the surface of the host‘s epithelial cells. This interaction

apparently stimulates the phagocytosis of the organism (Kuhn and Goebel, 1999). As

listeriae are engulfed, they are enclosed within a single membrane layered vacuole.

Professional phagocytic cells begin almost immediately to kill the listeriae within the

vacuoles. Their survival depends on escaping from the vacuole. This is where another

protein Listeriolysin O (LLO) aids in its pathogenesis. It is a bacterial pore-forming toxin,

essential for lysing the vacuolar membrane and allowing L. monocytogenes to escape into

the cytoplasm (Beauregard et al., 1997) aided by both phosphatidylinositol- anchored

proteins phosphatidylinositol (PI-PLC) and Phosphatidylcholine (PC-PLC) (Vazquez-

Boland et al., 2001). Once escaped into the cytoplasm, replication where L. monocytogenes

replicates and spreads to new host cells for fresh nourishment (Auerbuch et al., 2001). A

surface protein, ActA induces polymerization of globular actin molecules to form polarized

actin filaments along which cells move to the cell membrane and cause portions of the

membrane to bulge outwards, forming listeriopods (Lopez et al., 1999) which are engulfed

by adjacent cells allowing dissemination of L. monocytogenes whiles evading the host‘s

immune system. Bacteria are then carried from the intestine to the liver and spleen where

most are killed by neutrophils acting with Küpffer cells (Doyle, 2005). If the host‘s T cell–

mediated immune response is inadequate, Listeriae soon multiply in hepatocytes and

macrophages and are carried via the blood to various organs, particularly the brain and/or

uterus where they penetrate the blood–brain barrier and the placental barrier (Doyle, 2005).

Individuals with inadequate immune response include the elderly, pregnant, unborn and

newly delivered infants, dialysis and diabetes mellitus patients and HIV infected persons.

32

2.6.1.2.2 Infectious Dose and Incubation Period

The development of listeriosis after ingestion of contaminated food depends on other

factors such as the size of the inoculum, virulence of the strain, and the susceptibility of the

individual (Peris, 2005). In documented outbreaks, contamination levels as low as 102-10

4

CFU/g have caused severe clinical disease (Linnan et al., 1988). In a cancer patient, >1100

L. monocytogenes CFU/g were found in implicated food (Wenger et al., 1990). Also, out

of 12 reported listeriosis outbreak linked with the G.I symptoms, the lowest level found in

food was 1.9 x 105CFU/g (Miettinen et al., 1999).

However, dose-response data from human volunteer studies with L. monocytogenes or

from volunteer studies with a surrogate pathogen was non- existent. Instead, dose-response

relations have been generated and appraised based on expert elicitations, epidemiological

or animal data, or combinations of these (Martins et al, 1995). For example Buchanan et

al., (1997) used data on the incidence and level of L.momocytogenes contamination in a

single food product in Germany, and compared it with the incidence of listeriosis in

Germany. Two approaches widely applied to dose- response models were the beta-Poisson

and the Exponential models (Haas, 1983). According to the Exponential model bacterial

cells acted independently and each could potentially cause disease. Hence some regulatory

bodies such as the US/ FDA have a zero-tolerance policy to even its presence in RTE food;

1CFU in 25mL or 25g of food is not satisfactory legally. Incubation periods for outbreaks

run from days into months (Table 2.10).

33

Table 2. 10: Illness caused by L. monocytogenes

Type of

Listeriosis

Nature of Infection Severity Time to Onset

Infection during

pregnancy

(Listeriosis)

Acquired following the

consumption of

contaminated food

Mild flu-like illness or

asymptomatic in the

mother but serious

implications for unborn

infant including

spontaneous abortion,

fetal death, stillbirth and

Meningitis. Infection

more common in third

trimester

Varies from 1

day to several

months

Neonatal

infection

(Listeriosis)

Infection of new-born

babies from infected

mother during birth or

due

to cross-infection from

one

neonate in the hospital

to

other babies

Can be extremely severe,

resulting in meningitis

and death

1-2 days

usually from

congenital

infection prior

to

birth

Infection of non-

pregnant

adults

and children >1

month

(Listeriosis)

Acquired following the

consumption of

contaminated food

Asymptomatic or mild

illness, which may

progress to central

nervous system

infections such as

Meningitis. Most

common in

immunocompromised or

elderly

Illness may

occur within 1

day or up to

several

months

Source: Bell and Kyriakides, 1998 (Modified)

2.6.1.2.3 Virulence of L. monocytogenes and Environmental Stresses

The pathogenicity of this organism varies with various environmental conditions. Such

knowledge is key in understanding and solving its threat to our safeties. As an example,

Leimeister- Wachter et al., (1992) noted the significance of some virulence-associated

genes being differentially regulated at changing temperatures (e.g. at 20°C or 37°C) that

34

accompany with L. monocytogenes' switch ―from environment to host, or vice versa‖

though it is remarkably stress tolerant (Sleator et al., 2003).

2.6.1.2.4 Acid Tolerance of L. monocytogenes

L. monocytogenes exposed to mildly acidic conditions develops acid tolerance and become

better able to invade and proliferate in cultured cells than non-acid-tolerant bacteria (Conte

et al., 2000). However, studies generally show a decline of levels of organisms with acidity

and lowered pH (Ryser et al., 1985). Indications are that exposure to low pH (4.5–4.9)

reduces production of LLO (Datta and Kothary, 1993) and diminishes invasion of Caco-2

cells in culture (Galdiero et al., 1997). Skim milk and yogurt mix containing S. lactis, S.

cremoris, S. thermophilus, L. bulgaricus, or a combination of S. thermophilus and L.

bulgaricus (at initial inoculum of 0.1 to 5.0%) and L. monocytogenes were stored at 4°C

after a 15-hr. fermentation at 21, 30, 37, or 42°C. Survival of the pathogen in skim milk

ranged from 12 hrs. (fermented with 1% L. bulgaricus and S. thermophilus at 42°C) to 37

weeks (fermented with 1% S. thermophilus at 37°C). Overall, higher fermentation

temperatures for both mesophilic (30°C) and thermophilic (42°C) starter cultures resulted

in shorter survival times for the pathogen. Yet, when the yogurt mix fermented at 45°C

contained 103- 10

4 L. monocytogenes strain V7, Scott A, OH, or CAJ ml, the pathogen was

detected even after storage up to 12 days at 4°C. Hence fermented dairy products could not

automatically be considered Listeria-free (Schaack and Marth, 1988).

35

2.6.1.2.5 Temperature Tolerance

L. monocytogenes is generally considered to be mesophilic; yet, it also is a psychotroph.

According to numerous reports, Listeriae can survive and grow at low temperatures (4–

25°C), but under such conditions LLO production is greatly diminished or even abolished.

However, it takes only 2 hrs at 37°C for levels to return back to normal (Buncic et al.,

1996). Thus, temperature and lag relate inversely; at 4°C the lag phase lasts 5 to 10 d

(Anon, 1988). Hence foods must be kept at accurate temperatures.

L. monocytogenes was isolated by Garayzabel et al., (1987) from pasteurized milk samples

with cold enrichment. This though never occurred with plating immediately following

thermal treatment. As a facultative intracellular parasite, L. monocytogenes could exist

within polymorphonucleocyte leukocytes (PMNL) and be shed in milk (Doyle et al.,

1987). Doyle et al., (1987) isolated intracellular L. monocytogenes that had survived HTST

pasteurization at 72.2°C for 16.4 s. However, Bradshaw et al. (1987) established that

pasteurization guidelines for whole and skim milk, heavy cream, and ice cream mix were

enough to ensure its inactivation (D71.7°C values ranged from 0.9 to 2.7 s).

36

CHAPTER THREE

MATERIALS AND METHODS

3.1 Study Site and Population

The study was conducted at Ashaiman, the capital of the Ashaiman Municipality, in the

Greater Accra Region. It is about 4km from Tema and 30km from Accra (GNA, 2008), the

industrial capital and the capital city respectively, of Ghana. Relief of Ashaiman area is

generally flat and forms part of the Accra-Togo. Rainfall in this area ranges from 730mm-

790mm. The rainy season starts from April to July (the major season) and September to

November (the minor season).

At a growth rate of 4.6%, which is the highest in the country over, it is the fastest growing

urban area in Ghana. The 2000 population census report estimated the population of

Ashaiman to be 150,312 with females forming close to 60%, which is far higher than the

national average of 52%.

The main occupations in the area are farming, manufacturing and processing, quarrying

and construction, commerce, and financial and tourism services (IBIS, 2003). The formal

sector, which is made up of salaried workers including teachers, security personnel, nurses,

doctors, civil servants and bank workers accounted for less than 10% of the workforce at

Ashaiman. The other 90% are found in the informal sector. Ashaiman has 14 private

clinics, one private maternity home and one health centre. However, the Doctor-Patient

ratio for the then AZC under the TMA was estimated at 1:96,479 in comparison to the

Municipal average of 1:17, 255. Epidemiologic data of the top 10 diseases for the AZC and

37

the TMA suggests that more than two out of every three cases of diarrhoea reported for the

entire TMA come from the AZC (Appendix A), an indication of poor environmental and

food safety situation in the AZC.

3.2 Study Design

3.2.1 Risk Assessment

This study was designed to quantitatively access the risk of consuming dairy products from

the informal market contaminated with L. monocytogenes in the Ashaiman municipality

using the Modular Process Risk Model (MPRM), and to determine the best options to

reduce such risks. The risk assessment was according to the Microbial Risk Assessment

protocol of Codex Alimentarius Commission, 1999.

Three risk inputs were required for the exposure assessment: a quantitative dairy market

chain model, information on handling of milk and contamination rates and concentrations

of milk/ milk products with L. monocytogenes on each risk pathways. For data collection,

the study was done in three parts: A PRA was done followed by surveys using

questionnaires and the milk sampling and laboratory analysis. Identification of dairy farms,

markets and retail milk shops was achieved by a participatory rural appraisal (PRA) in the

communities and interviews in the informal market centers. Quantitative dairy market

chains were modeled using data obtained by interviews with informal milk market agents.

The contamination rates and concentrations were obtained by laboratory tests. Handling of

milk was understood by the combination of the PRA and milk market agent interviews.

38

3.3 Sampling

The PRA survey was used to find areas (i.e. towns/ villages and peri-urban sites, etc.) from

which milk produced and collected was sent to Ashaiman for sale and consumption. The

sample size of farming areas was determined using Equation1:

Equation 1: Sample Size Determination

……………………………………………………………….. (1)

Where:

n˳ = minimum sample size,

z = 1.96 for 95% confidence interval,

p = Prevalence [(i.e. 2.4%: Meyer-Broseta, (2001)]

d = Margin of error/ Level of difference.

However, with a total production area size which was small in number (i.e. 29) and the

time on hand, the minimum size was adjusted using Equation 2 according to Cochran,

(1963).

Equation 2: Cochran, (1963) Formula for Adjusting Sample Size

…………………………….………………………………. (2)

Where:

n = Adjusted sample size

n˳= Minimum sample size

N= Total number of farming areas producing milk for the market

The identified areas were stratified using a map of the area into geographic locations and

distances from Ashaiman. Quantities of milk supplied daily from these strata to Ashaiman

39

were compared and used as the basis for proportional sampling to select the farm locations

for the study. Nineteen (19) farming areas were used for the study. From each of these a

farm was selected randomly. Raw milk samples were then purchased into sterile stomacher

bags. An assembler from each farm was followed to the point where milk was delivered to

the retailer and samples were taken before and after boiling. Retailers were however nine 9

in number as some collected milk from more than one Assembler.

All samples were kept under cold storage in an ice chest packed with ice and while

awaiting the boiling process at the retail shops, in refrigerators at nearby shops. The

samples were quickly conveyed to the NFS department for analysis. The next day,

fermented milk samples were purchased from same retailers for analysis. Samples were

collected in duplicates in two batches (i.e. 1& 2) totaling 304. Sampling and laboratory

work were done for January- March, 2010, which was in the dry season. Appendix B is a

list of the areas which supplied the informal market at Ashaiman with raw milk.

3.4 PRA Survey

The PRA was conducted for various agent groups along the milk market chains within the

Ashaiman municipality by a multidisciplinary PRA team consisting of a student researcher,

an expert food microbiologist and also, a specialist veterinary professional. The build-up

included several prior trips by the PRA team with the aim of recruiting participants, getting

acquainted with the prospective participants, their general way of life and their

environment. Contacts were also maintained with the participants by means of phone calls.

40

3.4.1 Mapping

This was done as described by Hussain et al., (2005) by aiding the participants to draw an

outlay of their village/ town, indicating landmarks, and starting from a common reference

point. Maps were drawn on the ground or on white cloth. These were scrutinized and

confirmed with them and then translated onto plain white cardboard papers. A copy was

kept by both parties at each mapping session.

3.4.2 Seasonal Calendars

Seasonal calendars were used to describe the seasonal incidence of cattle movement,

milking practices and cattle diseases similar to Hussain et al., (2005). As was found

familiar to participants, the months according to the Christian calendar were used and each

season was represented using an object placed along the lower x-axis of the diagram.

3.4.3 Disease Ranking (Proportional Piling)

With necessary modifications, this was done similar to the method used by Hussain et al.,

(2005). Informants were asked to mention all symptoms associated with cattle diseases in

their area. A list was developed from the responses and validated through discussions with

informants. Informants were asked to rank the list of the diseases symptoms according to

their prevalence using 100 stones for the proportional piling. The exercise was repeated to

rank the disease symptom according to importance or impact on livelihoods.

41

3.4.4 Matrix Scoring

This was done for farmers and retailers according to Cramb, and Purcell, (2001).

Constraints to livelihood were ranked against livelihood indices. Informants were asked to

rank these constraints, and also determine the extent to which these influenced their lives.

3.5 Questionnaire Survey

Questionnaires surveys were done for retailers and consumers. Samples of questionnaires

administered are presented in Appendices. They were pre-testing during the PRA phase

and modified to meet the objectives.

3.5.1 Criteria for Inclusion of Respondents

The inclusion criteria were that respondents should be consumers or retailers and should be

capable of giving legal consents on their own.

3.6 Chemical Analysis of Milk Samples

3.6.1 PH Determination

The pH was determined using a pH meter (530 pH meter, Corning Pinnacle pH meter,

Woburn, MA US) calibrated to take readings of samples at 25°C. A small conical flask of

50mL was filled with agitated sample. The electrode was immediately dipped into it to

take measurements. Measurements were taken in triplicates and averaged.

42

3.7 Microbial Analysis

3.7.1 Detection, Isolation and Enumeration of Listeriae

Detection and enumeration were done using the US/ FDA protocol (Hitchins, 1998) with

some modifications (i.e. the omission of the pre- enrichment step). Approximately 3 ml of

milk samples were directly inoculated into 27 ml of Fraser and Listeria Enrichment broths

(LEB) and homogenized for 1min 30secs using a Seward Stomacher 400 Creator machine

with a breaking capacity of 35A. Aliquots of 0.1mL were plated onto chromogenic Listeria

agar (ISO) OCLA supplemented plates and incubated at 37°C for up to 48hrs. For the

chromogenic Listeria agar (ISO) OCLA supplemented plates counting was direct but for

PALCAM/ OXA three (3) typical Listeriae colonies per plate were confirmed for L.

monocytogenes. Counts were expressed as CFU/ mL by using the Equation (3) with 95%

confidence limits:

Equation 3: Expression of Counts in CFU/ mL

CFU/ mL = Number of colonies confirmed x Number of colonies counted ………… (3)

Number of colonies tested Volume tested x dilution

The remaining sample was incubated for 24-48hrs at 30-37°C and spread plated unto

chromogenic Listeria (ISO) OCLA supplemented agar plates (both selective and

differentiates for Listeria spp.) and PALCAM/ OXA plates (selective for Listeria spp.) at

dilutions of 10-1

and 10-2

for isolation.

For pure colonies, nutrient agar was streaked as a mandatory step in accordance with the

protocol in application. Presumed colonies morphologically typical to Listeriae were

43

further confirmed using the other biochemical test including Gram‘s staining, catalase

reaction, tumbling motility at 20–25°C, and the β- hemolysis test. They were then

compared with biochemical, growth and morphological characteristics of L.

monocytogenes designated NCTC 11994.

3.8 Statistical Analyses of Data

The surveys data were analyzed using the statistical package SPSS 16.0 for windows.

Laboratory data was analyzed with Stats Graphics plus 3.0 and Minitab 16 for windows.

Monte Carlo simulation of the model was performed using the uncertain factors described

by probability distributions. Thirty-two thousand iterations were performed for each

exposure simulation using Latin Hypercube sampling, with the @RiskTM

software package

version 5.5 [Palisade, Newfield, NY] and Microsoft ExcelTM

[Microsoft Corp., CA],

running on an Intel Pentium Dual-Core processor T2390 based Personal Computers (PC).

The number of iterations provided adequate convergence of the simulation statistics. For

the dose- response model ten thousand iterations were performed for each simulation.

44

CHAPTER FOUR

RESULTS AND DISCUSSION

4.1 General Overview

A PRA was done with key informants and milk/ milk product marketing agents to identify

prevalent disease symptoms in cows that produced raw milk destined for human

consumption at Ashaiman, the supply routes and handling characteristics, and the

quantities of the various milk/ milk product along the value chain consumed. PRA

activities with farmers included key informants interviews, mapping, seasonal calendar,

matrix scoring and disease proportional piling which yielded information on the herding

practices, milking and milk handling practices, and disease prevalence in herds and its

significance on farmers‘ livelihoods. Key informants interviews with Assemblers furnished

information on how they handled and transported milk after production onto the retail

markets. Key informant interviews, mapping and matrix scoring with Retailers ceded

information on the availability, distribution and handling of milk sold on the informal

market at Ashaiman to consumers. It also yielded estimates of the quantities of milk/ milk

product purchased by consumers. Such information was important in identifying the

quantitative milk distribution model, structuring of questionnaires for describing handling

of milk/ milk product along the milk value chain, and collecting milk samples for

laboratory analysis. Ultimately, these helped in determining the public health significance

of milk/ milk products and therefore possible intervention.

45

4.2 PRA Survey

4.2.1 Farmers PRA

4.2.1.1 Demographic Information on Farmers at PRA

Presented in Table 4.11 are the demographic data of the farmer-respondents in the PRA

survey. Similar to Hussain et al., (2005) cattle farmers were all adult-Muslim males

(n=15). Also, except for one, all were Fulanis, which was consistent with cattle rearing in

the south of the country according to Oppong- Anane, (2001). Ages of farmers were wide

spread: 6 (40.0%) were between 23-29years, 6 (40.0%) from 30-40years and 3 (20.0%)

above 40years. Young adults thus formed about half of the farmers. Majority 8 (53.3%) of

them had no formal education. The majority of the farmers (8 or 53.3%) had other jobs

apart from the cattle rearing. Most were food crop farmers which were consistent with the

agropastoralist practice (Tonah, 2003) whiles others did jobs other than crop planting.

These farmers unanimously or generally sought for medical care from the Tema General

Hospital (TGM).

46

Table 4.11: Background Information on milk producing farmers

Parameters Category Frequency (n) Percentage (%)

Gender Female

Male

0

15

0.0

100.0

Age (years) 24-30

30-40

>40

6

6

3

40.0

40.0

20.0

Religion Christian

Muslim

Traditionalist

0

15

0

0.0

100

0.0

Level of formal

education

None

Primary

Secondary

Tertiary

8

4

3

0

53.3

26.7

20.0

0.0

Additional

occupation

None

Crop production

Fitting

Driving

7

4

2

2

46.7

26.7

13.3

13.3

Health institution

attended

TGH

St. Florence

Darben

6

6

3

40.0

40.0

20.0

4.2.1.2 Mapping

The mapping exercise identified many significant assets or landmarks of shared

importance in the catchment areas. Elnasri (2005) reported in a similar exercise that such

assets, including households, water sources, a veterinary service outpost and pastures/

grazing resources were all expected to have momentous economic impact on their

livelihoods.

The mapping yielded a map (Figure 4.3) which provided a fair idea of the expected

herding practices of the farmers, grazing patterns of cattle and probable milking practices.

According to Hutchinson (1962) the nature of settlement and distribution of the

community, together with other factors such as proximity to the frontier, security or danger

47

from predators and cattle thieves, and the ease of access to abundant pastures, were all key

in determining herding practices. The map revealed that the households of the farmers

were nucleated; and grazing distances were found at quite some distance away from

households. It also offered an insight into the likelihood of herded animals coming into

contact with other animals: both wild and domestic Cattle herding was done by hired

Fulani herdsmen. The mapping also revealed that the veterinary outpost in the area was not

functioning, resulting in poor accessibility to veterinary care.

Figure 4.3: Participatory map of resources important to farmers’ livelihood

4.2.1.3 Analysis of Seasonal Calendar

Figure 4.4 is a picture taken during a seasonal calendar session and 4.5 is a translation

from the ground onto a white platform. The farmers seemed to be very familiar with the

seasons and the events that occurred during the different seasons.

48

Figure 4.4: Seasonal calendar session at farmers’ PRA

Figure 4.5: Seasonality of events on the calendar

4.2.1.3.1 Seasonal Occurrence of Rainfall

Two rainy seasons were acknowledged: the major and the minor seasons. The major

rainfall period is from April- July and the minor September to November. According to

farmers, the rainy seasons were famous for ushering in abundance of grass needed for

grazing the cattle and since milk production depended on grass basically, it peaked and so

did incomes and associated tradeoffs such as expenditure on food and non-food items.

Disease periods

HseConsumptn

Income

Labor

Milking

Dry season

Rainy season

Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul

49

Pasture for animals was reportedly difficult to find in the dry seasons and farmers needed

to search wide and far.

4.2.1.3.2 Milk Production

As the farmers revealed, milking occurs all year round. This was consistent with Fulani

practices documented by Okantah, (1990). Milking is done manually, and under

unhygienic conditions (Figure 4.6 & 4.7), which could cause some bacteriological

problems due to contaminations. Several documentaries have pointed to fecal material as a

major means of introducing bacteria into milk (Sanaa et al. 1993).

Figure 4.6: Farmer milking Figure 4.7: Filtering of milk on retail market

4.2.1.3.3 Seasonal Occurrence of Diseases

The farmers reported observing rapid surges in diseases with the rains. They attributed this

to the springing up of fresh grass. They however described bovine tuberculosis to occur all

year round. Such seasonal variations of the prevalence of diseases and disease-causing

agents in animals and animal products, respectively are consistent with literature (Eddie

and Scott, 1980; Murray et al., 1996; and Laven & Lawrence 2006) Farber et al. (1988)

& Husu (1990) documented high prevalence of Listeriosis, in colder winter seasons. They

50

associated this with indoor housing and silage feeding. Lund et al., (1991) however

characterized more incidences of Listeriae isolations in the warmer seasons than in the

colder months suggesting that factors other than silage feeding were also implicit in the

occurrence of Listeriae in raw milk. An example is poor quality pasture (Kumar et al.,

2007).

4.2.1.4 Preference Ranking on Livelihood Indices of Farmers

Figure 4.8 and Appendix C (I) show the result of the matrix scoring on livelihood of the

respondents. Incidence of animal diseases was most crucial to farmers. Access to market

and farm management (including water availability) was also found to have significant

influence on farmers‘ welfare. According to (Cornish and Lawrence, 2001) the most

acutely perceived problems for farmers were access to credit, markets and in peri-urban

areas water supply.

Figure 4.8: Constraints to the livelihood indices of farmers

51

4.2.1.5 Proportional Piling of Disease Symptoms of Animals

The farmers had astounding knowledge of the diseases of the cattle. They were made to

describe the symptoms too. Presented in Table 4.12 is a Lexicon of local terms for diseases

and symptoms (in farmer‘s language) they identified and perceived to be important to

them. These diseases were confirmed at a near-by veterinary office. The impact of these

diseases on livelihood was then determined in a proportional piling (Figure 4.9 and

Appendix C (II)) which was illustrated on Figures 4.10 & 4.11. The exercise was done

both in the dry and rainy seasons.

Table 4.12: Lexicon of local terms for diseases and symptoms farmer’s language

Probable veterinary diagnosis Local terms Case definition

Tuberculosis Butse Fever, lack of rumination and deep long

coughs which suggested lung infection.

Mastitis Lawre Udder inflames, reddens and hardens Milk

produced sometimes changes color. Also

milk produced does not homogenize well

once settled.

Foot and Mouth disease (FMD) Safa Excessive salivation of the mouth, with

blisters on tongue, and foot. Mouth smelled

bad also.

Diarrhea Chartol Excessive discharge of watery stool

Diarrhea (bloody) Chartol nyinyan Diarrhea with blood in feces

Stillbirths/ premature births Woperre Calves dead on arrival/ calves born before

their due. When such calves survive, they

usually had slow development and their hair

also was rough.

Extreme coldness Pewri Hairs stand straight on-end due to the cold

Dermatophilosis Gborle Subcutaneous rashes on animals. Treatment

was by applying hot metal to parts of animal

with infection.

Circular movements

(uncoordinated movements)

Lade Animal turns in circles as though it had

become mad. Usually it did not survive.

52

Figure 4.9: Piling of stone at session followed by their distribution by symptom

Figure 4.10: Comparison of the impact of disease on various livelihood indices

53

Figure 4.11: Comparison of the impact of disease on various livelihood indices

The Kendall‘s W co-efficient of concordance of prevalence was 0.796 at a significance of

0.01. This showed a strong correlation between the results from the two sessions

(Appendix C (III)). Also for the impact, a W of 0.904 at the significance of 0.01 was

computed (Appendix C (III)). These combined probably indicated two things. The first

was the immediate and thorough comprehension of the concepts of PRA by farmers. The

second was the unambiguous and almost universal opinion of informants concerning the

nature of pertinent issues affecting their livelihoods. Thus, the PRA concept exhibited both

friendliness and amenability whiles being robust, logical and effective still.

Highest among the symptoms were deep coughs/ breathes and rashes both at a rate of

11.0% by followed by a tetrad of symptoms (all at 9.0% prevalence) including bloody/

watery diarrhea, skinny but eats well (progressive emaciation), swollen/ sore feet and

spontaneous abortion/ stillbirths. Least common were facial paralysis and circling

54

movements. Also, symptoms whose impacts were very crucial to farmers‘ livelihoods and

thus had higher importance were deep coughs/ breathes (17.0%), swollen/ sore feet

(14.0%), skinny but eats well (13.0%), spontaneous abortions/ stillbirths (10.0%) and

rashes (10.0%). These were followed by sudden deaths, watery/ bloody diarrhea and

premature births (all at 7%). At the bottom were facial paralysis, circling movement/

uncoordinated movements and sudden inability to walk (at 3, 1 and 0 percent respectively).

As concerning the preferred options of solutions farmers ranked the symptoms in a

descending order as deep cough/ breathe rashes (25.0%), swollen soured feet (15.0%),

watery/ bloody diarrhea (8.0%), and boils (6.0%), in appetence (5.0%) and spontaneous

abortions/ stillbirths (4.0%). Premature births and sudden deaths were 3.0% and 2.0%

respectively whiles skinny but eats well (progressive emaciation), sudden inability to walk

and drooling tongue were lowest (0.0% each).

Participants demonstrated a clear distinction between prevalence and importance. By way

of a typical illustration, it was observed that though all disease symptoms prevalence were

quite high (which indicated a similar trend for the occurrence of cattle disease in these

areas), such symptoms as emaciation, drooling tongue and sudden inability to walk had

little impact on farmers livelihoods and therefore importance were almost nil. .

55

4.2.2 Assembler’s PRA

4.2.2.1 Mapping

Mapping with Assemblers identified many milk production areas around Ashaiman, which

were within the distant range of 12-40 km. These are cluster of farms, which varied in

number and sizes, at different locations. Hill (1964) gave a wide range of between 50- 200

cows kept by Fulani herdsmen on behalf of absentee owners.

It was revealed that assemblers to not inform milk retailers of where they obtain their milk

from. With-holding of such information from retailers was seen by Assemblers as a job

security. It was noted that assemblers handled relatively varied volumes of milk, ranging

from about 3 to 135 L. Milk handled were usually the bulked amount of milk from several

low yielding cows. Sometimes one Assembler collects milk from more than one farm in a

given location.

4.2.2.2 Milk Handling by Assemblers

Handling of milk was just as Omore et al., (2004) described. After milking and bulking,

milk was transferred into plastic jerry cans and covered tightly. Though these made

handling convenient for Assemblers, Omore et al., (2003) found them more likely to

contaminate milk with bacteria since they could not be cleaned easily. Assemblers then

transported these from the sites of production to the Retailer. Times taken from the first

collection to delivery varied. However, what did not vary much was the mode of

transportation which was mainly by public vehicles. It was revealed that some Assemblers

56

kept milk from various farms with them (unrefrigerated) until the quantities they had were

enough to justify the transportation costs to the retail point.

4.2.3 PRA with Milk/ Milk Product Retailers

The retailers expressed their expectations as, generally: (1) to receive enough milk at

cheaper prices all year round to sell and (2) to see faster increases in the numbers of non-

traditional consumers (i.e. non- Fulani and/ or non-Muslim consumers). These, according

to them, would help their business to grow.

4.2.3.1 Mapping

The map developed showed that informal milk/ milk product marketing was concentrated

mainly in two sites in the same electoral area, Tulaku. Some retailers were however dotted

around both Tulaku and other electoral areas (Figure. 4.12).

Figure 4.12: Map of Electoral Areass (EA) with informal retailing of dairy products

at Ashaiman. (EAs and dairy marketing were represented with the red and yellow cola

nuts respectively)

57

4.2.3.2 Quality Control at Retail

It emerged also that Retailers at the main markets mostly were able to buy more milk from

the Assemblers. Uncharacteristic of the general lack of quality control management along

such channels in Ghana (Omore et al., 2003), Retailers were found to be quality conscious

as far as it led to serious economic consequences on their part. They had adapted to the

practice of keeping milk from different Assemblers separately, and would only mix them

together the next day if found still suitable for intended use. Otherwise, such produce

would be discarded after it had been shown to the Assembler who supplied it. Other times

too, the clotting-on-boiling test, described also by Omore et al., (2002), was done to

determine suitability for heat processing (Figure 4.13(a)). Failure of test meant rejection. It

was observed however, that water, averaging about 15 L, used for the washing of bowls at

the milk joints, was never changed during the entire sale period. Soap and detergents were

also never used in washing of bowls. Water turned from being transparent to opaque

(Figure 4.13(b)). This was typical of the poor hygiene reported (Donkor et al., 2007).

Figure 4.13: Clot-on-boil Quality Test (a) Water used in washing bowls (b)

58

4.2.3.2 Marketing of Milk/ Milk Products at Old Tulaku, Ashaiman

The small retailers dotted about acquired their supply of milk/ milk products from agents at

the main markets, usually the Old Tulaku market, rather than from the Assemblers. They

did not usually buy large quantities of milk/ milk product. A reason was that their locations

did not offer them space to boil and ferment milk collected from Assemblers, which was

the typical practice. Products sold on the informal milk markets were of various types.

These included raw fresh milk (not boiled), fresh milk (boiled) and naturally fermented

milk (nyarmie, nunu and combination of both). These were consumed with other

traditional food products such as Fura, Lekri and Couscous (Omore et al., 2003, Smith,

1998)). Figure 4.14 is a summary of activities that took place at milk/ milk product retail.

59

Source: Retailers’ PRA survey

Figure 4.14: Pathway for milk transformation and sale at Ashaiman

Sale of raw milk without

chilling (as received from

Assembler). This goes on

through to the start of the

heating process and

continues till milk is hot

Preparation and sale of raw milk at

retail: Milk usually at ambient

temperature, but sometimes warm or

even hot is sold by dishing out usually

into plastic rubbers with the same

container used for dishing out milk that

has not received any heating. No chilling

is applied at this stage but majority of

customers do not consumed it there.

Preparation of naturally fermented

boiled milk: Boiled milk which is left

deliberately or not is fermented naturally

(does not employ starter cultures nor is it

controlled. Fermentation introduces

special flavor and aroma characteristics

which consumers appreciate.

Preparation of naturally fermented

milk: Milk which could not be boiled

and was left deliberately or not, is

fermented naturally (does not employ

starter cultures nor is it controlled.

Fermentation introduces special flavor

and aroma characteristics which

consumers appreciate

There is usually combination of

both boiled and not boiled

fermented milk products before sale

to the consumer. Preparation

involves addition of water and ice

block (both of which can influence

the safety of the product. Volume

per unit gallon of raw milk also

increases and therefore profit. It is

therefore not a wonder that retailers

would typically halt the sale of raw

and boiled milk to ferment and sell

subsequently

URBAN CONSUMPTION AT ASHAIMAN

60

4.2.3.3 Matrix Scoring for Retailers

At the sessions with Retailers, it was noted that the main constrains to the milk retail trade

were inaccessibility to markets, unavailability of the raw produce, inaccessibility to credit,

transportation and unhygienic conditions in that order. Figure 4.15 is representation of the

results of the matrix scoring exercise captured in Appendix D (I).

Figure 4.15: Plot of livelihood constraints against retailers’ livelihoods indices

Access to market first, and then availability of milk were found to be the two most

important parameters that affected income and therefore security. Also, the two most

important parameters that affected food consumption and other utilities were still access to

markets and availability of milk. Hence, access to markets was identified to influence

livelihood indices the most.

The Pearson‘s correlation coefficient between income and the other livelihood indices

were strong. It was 0.995, 0.991 and 0.984 respectively for security, food consumption and

other utilities consumption. The correlation between security as per food consumption and

61

other utilities were also 0.987 and 0.975, respectively. The correlation between other

utilities and food consumption was similarly high. It was 0.993 (P <0.01) significant level

for two-tailed test) (Appendix D (II)).

It emerged that the trade was relatively more profitable per unit volume during the periods

of scarcity (i.e. the dry seasons). Motivated by a surge in demand and an expectant

increase in income, some Retailers adulterate their milk/ milk products with water. Others

also adulterate milk with imported milk powder when preparing the naturally fermented

products (i.e. nyarmie, nunu and the combined meal). The almost perfect negative

correlation between market access and availability of raw produce on one side, and

hygiene on the other was consistent with a report by (Omore et al., 2003) that chronicled

unhygienic conditions on such markets. The Retailers revealed that patronage of milk and

milk products was affected by several factors, including the coldness or hotness of the

season. The chilled milk was less consumed during the rainy seasons when the weather

was generally cold. Milk spoilage during the bumper period was considered a problem.

This was primarily because of inadequate refrigeration in these marketing channels.

The PRA revealed that hygiene is not very important to milk retailers since it did not

influence their livelihoods directly. It was however perceived that Retailers would improve

hygiene and safety standards if it would make their merchandise more acceptable to

customers and thus increase patronage.

62

4.2.3.4 Milk Distribution from Production to Consumption and Evolution of Hazards

Figure 4.16 & 4.17 show the summary of the milk pathway as collated in the PRA. From

the PRA, the distances of the milk production areas from Ashaiman and the quantities of

milk produced that ends up on the informal milk markets at Ashaiman was determined.

Modeling unique events that affect the evolution of the hazard from production to

consumption yielded Figure 4.18 based on the MPRM.

63

52.0km 46.0km

39.0km

43.0km

35.0 km 42.5km

32.0km

30.0km 25.0km

. 23.5km

23.5km ..L 24.0km

.

.

17.9km 18.8km 20.3km

45.0L

15.0km

12.0 km 13.0km

Raw milk Boiled milk Fermented milk (width is amount in liters)

Figure 4.16: Quantitative milk distribution model; production to retail, for Ashaiman

Manya

Mampoh, Shai hills

Okyibleku

Dodowa

Suta

Tachukope

Odumase

URBAN CONSUMERS AT ASHAIMAN

Katamanso

Ablekuma

Afienya

Apolonia

Dawhenya

Mataheko

Kpone barrier

Prampram

Gbetseli

Mobole

Doryum Asebi

RETAILERS AT ASHAIMAN

64

39.0 L 54.0 L

67.5 L

63.0 L

36.0 L 63.0 L

45.0L 81.0 L

63.0 L 33.8L

.

41.5L 27.0 L 49.5 L

.

27.0L 54.0 L

31.5L 45.0L

36.0 L 81.0 L


Figure 4.17: Quantitative milk distribution model; production to retail, for Ashaiman

Manya

Mampoh, Shai hills

Okyibleku

Dodowa

Suta

Tachukope

Odumase


Katamanso

Ablekuma

Afienya

Apolonia

Dawhenya

Mataheko

Kpone barrier

Prampram

Gbetseli

Mobole

Doryum Asebi


65

Infected animals

Cross-contamination &

Mixing

Growth & Inactivation

Inactivation

Inactivation/ Cross-contamination

Cross-contamination &

Removal

Cross-contamination

Figure 4.18: Schematic presentation of food exposure pathway modeled using the

MPRM

Animals at farm

Milking

Feces in milk

Pooling/ bulking

Milk at wholesale

Transport/ storage

Milk at retail/ shop

Boiling of milk

Serving/dishing

out

Serving/ dishing

out

Natural fermentation

Serving/ dishing

out

At consumption At consumption At consumption

Milk consumed with other products

66

4.3 Questionnaire Survey

4.3.1Retailers Questionnaire Survey

4.3.1.1 Demographic Characteristics of Retailers

The demographic profile of Retailers of dairy products sourced from the informal

market(s) at Ashaiman was obtained from questionnaire survey (Appendix E (I)) and is

presented on Table 4.13. Mostly, they were middle- aged Fulani Muslim females between

the ages of 26-35years. Retailers (n=9) occupying this niche at Ashaiman were all

employed in the study. Most resided at Tulaku. They largely lacked formal education and

all sought medical care from the TGH. Generally, Retailers had been plying their trade for

varying periods, ranging from 6 to over 10 years. Milk was sold almost every day except

for special occasions such as the Muslim holidays.

Table 4.13: Demographic characteristics of consumer respondents

Characteristic Category Respondents

n %

Gender Female 9 100.0

Age (yrs.) 26- 35

36- 45

6

3

66.7

33.3

Religion Islam 9 100.0

Ethnicity Akan

Dagomba

Fulani

Other Northern tribes

1

1

5

2

11.1

11.1

55.6

22.2

Residence Tulaku

Roundabout

Zenu

Asensuba

5

2

1

1

55.6

22.2

11.1

11.1

Level of formal

education

None

Primary

Secondary

8

0

1

88.9

0.0

11.1

Occupational status Vocational/ Petty trader 9 100.0

Health institution

attended

Tema General Hospital 9 100.0

67

4.3.1.2 Traditions of the Milk Retail Trade

As indicated in Table 4.14 the types of milk product(s) sold were raw untreated milk,

boiled milk and fermented milk. Consumers were mostly individuals from various walks of

life, who usually purchased small quantities. The total amount of milk/ milk products sold

was difficult to obtain. Estimates made by observing sales on peak and scanty days

suggested that raw unpasteurized milk was the least sold. Retailers barely sold 5.0 L of raw

milk per day, but the maximum that could be sold was 7.0 L. More boiled milk was sold

and quantities sold ranged up to and over 8.0 L. Sales of fermented milk were very high,

ranging up to and over 500 L per day. Figure 4.19 shows the proportions of the various

milk product types Retailers‘ sell.

Table 4.14: Traditions of the milk retail trade

Questions? Answers (%)

How long have you been selling milk/ milk product(s)?

<1yr

1-2yrs.

3-5yrs.

6-10yrs.

>10yrs.

0 (0.0)

0 (0.0)

0 (0.0)

3 (33.3)

6 (66.7)

How many days in a week do you sell milk/ milk product(s) during the

dry season?

<3days

3-6days

7days

0 (0.0)

0 (0.0)

9 (100.0)

How many days in a week do you sell milk/ milk product(s) during the

rainy season?

<3days

3-6days

7days

0 (0.0)

0 (0.0)

9 (100.0)

What type(s) of milk product do you sell?

Raw milk only

Boiled milk only

Naturally fermented milk only

Two of the above only

Raw, boiled and naturally fermented milk

0 (0.0)

0 (0.0)

0 (0.0)

0 (0.0)

9 (100.0)

68

Who are your usual customers?

Individual consumers

Co-operate bodies

Institution

9 (100.0)

0 (0.0)

0 (0.0)

What quantity of raw milk do you sell per day in the dry season?

3.0-4.0L

4.1-5.0L

5.1-6.0L

6.1-7.0L

>7.0L

What quantity of boiled milk do you sell per day in the dry season?

4.0-5.0L

5.1-6.0L

6.1-7.1L

7.1-8.0L

>8.0L

What quantity of fermented milk do you sell per day in the dry season?

100.0-150.0L

151.0-200.0L

201.0-250.0L

251.0-300.0L

>300.0

3 (33.3)

4 (44.4)

1 (11.1)

1 (11.1)

0 (0.0)

1 (11.1)

2 (22.2)

3 (33.3)

1 (11.1)

2 (22.2)

1 (11.1)

3 (33.3)

2 (22.2)

2 (22.2)

1 (11.1)

Figure 4.19: Percent average quantities of type(s) of dairy product sold at retail

Naturally fermented milk

Boiled milk

Raw milk

69

4.3.1.3 Supply of Raw Milk to Retailers

Milk supply was from the Assemblers. During the dry season, milk was more often

received early in the morning, however in the rainy season they were received more at late

mornings or early afternoons as indicated on Table 4.15.

Table 4.15: Supply of raw milk to retailers What is your source of raw milk supply?

Farm/ Kraal

Assembler

Hawkers

Others

0 (0.0)

9 (100.0)

0 (0.0)

0 (0.0)

What period(s) do you receive raw milk supply in the dry season?

Early mornings (7:00am-8:30am)

Late mornings (8;30am-11:30am)

Mid-afternoons (11:30am-2:00pm)

Late afternoons (2:00pm-4:30pm)

Other

6 (66.7)

0 (0.0)

0 (0.0)

0 (0.0)

3 (33.3)

What period(s) do you receive raw milk supply in the rainy season?

Early mornings (7:00am-8:30am)

Late mornings (8;30am-11:30am)

Afternoons (11:30am-2:00pm)

Late afternoons (2:00pm-4:30pm)

Other

3 (33.3)

0 (0.0)

0 (0.0)

0 (0.0)

6 (66.7)

4.3.1.4 Quantities of Milk Supplied by Assembler

The quantities of milk received varied with the seasons as was production volumes at the

farms (Table 4.16). In the dry season majority of them receive 50-90 L of milk, even

though some could receive over 200.0 L. In comparison, during the rainy season, majority

of retailers receive 91.0-135.0 L of milk and some receive in excess of 270.0 L.

70

Table 4.16: Quantities of milk supplied by Assembler What quantities of raw milk do you receive in the dry season?

50.0-90.0L

91.0-135.0L

136.0-200.0L

>200.0L

4 (44.4)

1 (11.1)

3 (33.3)

1 (11.1)

What quantities of raw milk do you receive in the rainy season?

95.0-135.0L

136.0-200.0L

201.0-270.0L

>270.0L

4 (44.4)

2 (22.2)

2 (22.2)

1 (11.1)

4.3.1.5 Milk/ Milk Product Handling During Sale

Retailers found it convenient to keep raw milk at ambient temperature during sale. Boiled

milk could however be kept hot or warm also. Naturally fermented milk on the other hand

was always kept chilled. This was done by adding iced cubes to the milk periodically. This

information is contained on Table 4.17.

Table 4.17: Milk/ milk product handling during sale Questions Answer (%)

How do you keep raw milk during sale?

Ambient

Chilled

Other

9 (100.0)

0 (0.0)

0 (0.0)

How do you usually keep boiled milk during sale?

Ambient only

Hot only

Both

0 (0.0)

0 (0.0)

9 (100.0)

How do you keep naturally fermented milk product during sale?

Ambient

Chilled

0 (0.0)

9 (100.0)

If chilled, is temperature checked?

No

Yes

0 (0.0)

9 (100.0)

If Yes, how do you respond to a warming product?

Refrigerating it

Breaking iced block into milk

0 (0.0)

9 (100.0)

71

4.3.1.6 Association of Milk with Probable Diseases

The general view among retailers was that milk consumption could cause various diseases

(Table 4.18) especially when not boiled. Diarrhea was the most common result in that

event though other lesser frequent ones occurred (Figure 4.20). Diarrhoea and many of the

described symptoms have been known to result from several factors including lactose

intolerance (Kretchmer, 1972) or the presence of pathogens in the milk (CFSPH, 2005).

Table 4.18 Association of milk with probable diseases Questions Answer (%)

Could milk/ milk consumption be responsible for disease in man?

No

Yes

0 (0.0)

9 (100.0)

Mention some means by which milk/ milk product could be

responsible for diseases in man

Symptoms were right

Symptoms were wrong

Some symptoms were right and others wrong

0 (0.0)

0 (0.00

9 (100.0)

Mention some precautions to prevent milk/ milk product causing

these diseases

Symptoms were right

Symptoms were wrong

Some symptoms were right and others wrong

0 (0.0)

0 (0.00

9 (100.0)

Figure 4.20: Disease symptoms associated identified by retailers

72

4.3.1.7 Suspected Symptoms Associated with Listeriosis in Retailers

Symptoms suggestive of L. monocytogenes infections were also prevalent among the raw

milk retailer-consumers as spontaneous abortions were recorded in 3 (33.3%) of them.

Some had had spontaneous abortions more than once. One out of the nine respondents had

also experienced stillbirths. Details can be found in Table 4.19.

Table 4.19: Suspected symptoms associated with listeriosis in Retailers

Have you ever been infected with a suspected case of foodborne

disease associated with milk consumption?

No

Yes

0 (0.0)

9 (100.0)

Did you seek medical help?

No

Yes

0 (0.0)

9 (100.0)

Have you ever experienced a birth abnormality such as spontaneous

abortions, still births and/ or premature births?

No

Yes

6 (66.7)

3 (33.3)

If yes, how often has Spontaneous abortions occurred?

Once

Twice

Three times

If yes, how often has Stillbirths occurred?

Once

Twice

Three times

2 (66.7)

0 (0.0)

1 (33.3)

1 (100.0)

0 (0.0)

0 (0.0)

If Yes, was medical help sought?

No

Yes

0 (0.0)

3 (100.0)

4.3.1.8 Handling Practices of Milk after Receipt from Assembler

The survey revealed that, typically milk Retailers receive milk at ambient temperature

since the Assemblers do not have cold-chain facilities (Table 4.20). Also milk is strained

through nylon net in a metal frame to remove any debris. The net is usually not washed

73

prior to its reuse. The strained milk could be sold as-is, or boiled or fermented overnight

before it is sold. Sales of boiled milk begins when the heating process begins, thus the milk

might not be adequately heated before dispensing to consumers.

Table 4.20: Handling practices of milk after receipt from Assembler In what state do you usually receive milk from Assemblers?

Ambient

Boiled

Chilled

9 (100.0)

0 (0.0)

0 (0.0)

Is milk sieved when being poured into receptive containers?

No

Yes

0 (0.0)

9 (100.0)

If Yes, with what is it sieved?

A piece of cloth

A sieve made with net

0 (0.0)

9 (100.0)

Are sieve/ cloth washed before use?

No

Yes

0 (0.0)

9 (100.0)

If Yes, with what are they washed?

Water only

Water and sponge

Water, sponge and soap

Other

9 (100.0)

0 (0.0)

0 (0.0)

0 (0.0)

Are sieve/ cloth washed before use on every physically separated

milk consignment?

No

Yes

0 (0.0)

9 (100.0)

74

4.3.2.1 Demographic Characteristics of Consumers

The demographic profile of consumers as was obtained from administering a questionnaire

(Appendix E (II)) is presented in Table 4.21. Consumers of milk from informal markets are

predominantly young multi- ethnic adult Muslim females between the ages of 26-35years.

Nearly half of the sampled population lacked any formal education and were self-

employed. Some public service workers with higher formal education were also

interviewed. Most of these consumers sought medical care from the T.G.H.

Table 4.21: Demographic characteristics of consumer respondents

Characteristic Category Respondents

N %

Sex Female

Male

83

67

55.3

44.7

Age (yrs.) 15-25

26-35

36-45

>45

61

55

28

6

40.7

36.7

18.7

4.0

Religion Christianity

Islam

66

84

44.0

56.0

Location Agyei Kojo

Tema

Lebanon

Mantseman

Asensuba

Niiman

Taboo

Market Square

Night Market

Tsinagbe

Tulaku

Maamomo

Obakatse

Zongo Laka

4

3

14

3

13

5

6

11

11

14

48

5

8

5

2.7

2.0

9.3

2.0

8.7

3.3

4.0

7.3

7.3

9.3

32.0

3.3

5.3

3.3

75

Ethnicity Ga/Adangbe

Akan

Ewe

Dagomba

Fulani

Other Northern tribes

Other Nationals

41

18

20

30

10

23

8

27.3

12.0

13.3

20.0

6.7

15.3

5.3

Level of formal

education

None

Primary

Secondary

Tertiary

67

18

57

8

44.7

12.0

38.0

5.3

Occupational status Artisan

Businessman/ woman

Public service worker

Vocational/ Petty trader

Student

Unemployed

33

19

8

70

14

6

22.0

12.7

5.3

46.7

9.3

4.0

Health institution

usually attended

Ashaiman Health Center

Daben Hosp.

Private clinic

Tema General Hosp. (only)

Tema General and other

Other

14

13

16

62

41

4

9.3

8.7

10.7

41.3

27.3

2.7

Summary statistics

Profile of consumers sampled for this study, Total number of respondents (N) = 150

n = Frequency

4.3.2.2 Knowledge on Milk/ Milk Product Consumption Trends

Consumption of milk/ milk products from the informal markets was for varying periods of

time, ranging from less than a year to over 10 years. The rate of consumption though was

influenced by factors such as taste, availability and affordability. Consumption of raw milk

was high among typical ethnic groups, the Fulanis and Dagombas, and yet for fermented

milk, which was the most consumed overall, unconventional consumers such as the

Adangmes and the Akans reported higher consumption. Consumption was mostly daily but

a proportion also consumed twice or more. Details can be found on Table 4.22. The high

consumption corroborates with raw milk supply to these markets (Appendix E)

76

Table 4.22 Milk consumption habit of consumers Questions Number (%)

How long have you been consuming dairy products from the

informal market?

<1yr

1-2yrs

3-5yrs

6-10yrs

>10yrs

82 (54.7)

19 (12.7)

19 (12.7)

18 (12.0)

12 (8.0)

Why do you consume milk/ milk product from the informal

market with little regulations?

Culture only

Taste only

Availability only

Affordability only

Combination of taste/ availability/ affordability

All the above

0 (0.0)

26 (17.3)

5 (3.3)

1 (0.7)

53 (35.3)

65 (43.3)

Which type(s) of dairy products do you patronize?

Raw milk only

Boiled milk only

Naturally fermented milk only

Combination of raw/ boiled/ naturally fermented milk

Wagashi only

All types

1 (0.7)

0 (0.0)

15 (10.0)

44 (29.3)

0 (0.0)

90 (60.0)

How often do you consume raw milk?

Once a day

Once 2 days

Twice a week

Once a week

Once in 2 weeks

Once a month

Once in more than a month

How frequent do you consume boiled milk?

Twice daily

Once a day

Once 2 days

Twice a week

Once a week

Once in 2 weeks

Once a month

How frequent do you consume fermented milk?

Once a day

Twice a day

Once 2 days

1 (2.2)

9 (19.6)

12 (26.1)

14 (30.4)

4 (8.7)

4 (8.7)

2 (4.3)

4 (3.4)

5 (4.3)

9 (7.8)

52 (44.8)

30 (25.9)

12 (10.4)

4 (3.4)

105 (71.9)

4 (2.7)

24 (16.5)

77

Twice a week

Once a week

Once in 2 weeks

Once a month

0 (0.0)

8 (5.5)

0 (0.0)

0 (0.0)

4.3.2.3 Attitude of Consumers to Food Hygiene on the Informal Market

The results on consumer attitudes to food hygiene are summarized in Table 4.23. Some of

the consumers interviewed expressed concern about the hygiene on the fresh milk retail

market. The issues raised included retailers not wearing aprons, stray animals wandering

around, retailers serving into improperly washed bowls after they have been used, non-use

of sponge and soap in washing of bowls and wash water not being regularly changed.

Majority of them, about 83%, expressed the fact that improperly handled food can cause

illness, especially gastro-intestinal diseases.

Table 4.23 Consumer attitudes to food hygiene on the informal market Questions? Answers (%)

Have you ever received any formal training in food hygiene?

No

Yes

147 (98.0)

3 (2.0)

If Yes, where did you receive it from?

Workshop

Seminar

Health institution

School

0 (0.0)

0 (0.0)

0 (0.0)

3 (100.0)

Are you satisfied with conditions under which milk/ milk product were

sold?

No

Yes

87 (58.0)

63 (42.0)

If No, what can be done to improve upon it?

Retailers wear aprons

Not to allow animals to be wondering around

Bowls be washed with sponge and soap

Water used for washing bowls be changed regularly

34 (22.7)

56 (37.3)

62 (41.3)

49 (32.7)

Could food be responsible for disease in man?

No

Yes

26 (17.3)

124 (82.7)

If Yes, which of the following is a symptom associated with foodborne

infections?

78

Diarrhea

Vomiting

Weight loss

Miscarriages/ stillbirths/ premature births

124 (82.7)

60 (40.0)

18 (12.0)

0 (0.0)

4.3.2.4 Fresh Milk Handling Practices of Consumers

Some consumers keep milk and milk products for some time after transportation before

consumption. About 9% of consumers of the raw unpasteurized milk, 21% of consumers of

boiled milk and 19% of consumers of fermented milk store the products. The condition of

storage is either by refrigeration or at ambient temperature. About three percent of

consumers keep raw untreated milk at ambient temperature and two percent also keep

boiled milk at ambient temperature. Presented in Table 4.24 are some of the handling

conditions.

Table 4.24 Fresh milk handling practices of consumers Questions Numbers (%)

Where do you purchase your milk/ milk product from?

Farm gate

Assembler

Retailer

0 (0.0)

0(0.0)

150 (100.0)

Do you consume Raw milk at point of sale?

No

Yes

Do you consume Boiled milk at the point of sale?

No

Yes

Do you consume Fermented milk at the point of sale?

No

Yes

89 (59.3)

6 (4.0)

76 (50.7)

40 (26.7)

73 (48.7)

73 (48.7)

If No, how do you transport milk/ milk product?

On foot

By bicycle

By private vehicle

By public vehicle

74 (49.3)

8 (5.3)

1 (0.7%)

33 (22.0)

How long does it take to transportation to the point of

consumption?

<30mins

101 (67.3)

79

30mins- 1hr

>1hr

13 (8.7)

2 (1.3)

Does raw milk receive any heat treatment after transportation?

No

Yes

Does boiled milk receive any treatment after transportation?

No

Yes

Does fermented milk receive any treatment after transportation?

No

Yes

40 (26.7)

49 (32.7)

76 (50.7)

0 (0.0)

73 (18.7)

0 (0.0)

If No, is raw milk consumed immediately after transportation?

No

Yes

If No, is boiled milk consumed immediately after transportation?

No

Yes

If No, is fermented milk consumed immediately after

transportation?

No

Yes

27 (18.0)

13 (8.7)

31 (17.3)

45 (33.3)

28 (18.7)

45 (30.0)

80

4.3.2.5 Qualitative Exposure Assessment for the Risk of Exposure to L.

monocytogenes from the Consumption of Dairy Product from the Informal Market

This indicated probabilities of exposure from the consumption of milk/ milk products from

the informal market. This was primarily based on handling and processing characteristics

associated with its consumption.

Milk was produced under conditions that could easily lead to its contamination. Hands

were not cleaned neither were the teat of the cows. In addition, milk-handling gears were

not adequately washed and milk was bulked. Hence, the risk associated with raw milk

consumption was high. Indications also were that the high pregnancy and child birth rate

was a concern that could not be disregarded for raw milk consumption.

However, because raw milk was usually boiled before consumption, any threat would be

significantly reduced. Similarly, most milk consumed from the informal market was

fermented reducing any risk by anticipation.

Yet fermentation was by way of backslopping where boiled samples could again be

contaminated. This raises considerable concerns among consumers. Also, how milk

storage was done was such that the risk increases again.

In general, handling of milk was such that any action taken during a processing step before

could very easily be undermined by incorrect practices at a later stage. A detail exposure

assessment can be found in Table 4.25.

81

Table 4.25: Qualitative Exposure Assessment for the risk of exposure to L.

monocytogenes from the consumption of dairy product from the informal market

Step Handling of milk/ milk

product

Basic

process

Level of

concern

Reasons for assigning

effect

Consumpti

on

Milk consumed Endpoint High High pregnancy rate and

child birth rate.

Processing Milk boiled before

consumption

Inactivation Very low More than half of

respondents who

patronize raw milk

consumed it after it has

been boiled (32.6%). The

vast majority also

preferred fermented milk

(at 97.3).

Storage Milk refrigerated/ kept

at ambient temperature.

Storage compartment

open often

Growth High Temperature abuse.

Majority who store dairy

products (at 20.7%) had

their refrigerators being

opened quite often

Transport Milk sent away after

purchase for

consumption

Growth Low Time for transportation

usually below 30mins

(67.3%).

Production Milking from several

animals combined.

Also milk kept on farms

until collected by

assemblers

Mixing and

Growth

High On farm hygiene was

low ( PRA-survey)

Processing Milk boiled before sale

Milk fermented before

sale

Milk sold raw using the

same containers as

boiled and fermented

milk

Inactivation

Inactivation

Cross

contaminati

on

Low

Low

Moderate

Most milk boiled before

sale.

Most milk is sold as

naturally fermented milk

Retailers mostly sold all

three kinds of milk

products using the same

utensils

Transport Milk collected from the

farm to the retail market

Cross

contaminati

on,

partition,

mixing and

Growth

Moderate Milk collection done at

early morning when

temperature was cool for

the dry seasons.

Distances to points of

retail were not so far. But

hygienic conditions

associated with these

practices were poor

82

4.3.2.6 Occurrence of Probable Initial Symptoms of Human Listeriosis

Most consumers had experience disease episodes characterized by chills, colds, nausea,

vomiting, diarrhea, malaise and/ or muscle aches at least once. Also, over a third of

consumers had experienced pneumonia, headaches, convulsions and/ or mental status

changes consequent to the initial symptoms, or separately. Details can be found on Table

4.26.

Table 4.26: Occurrence of probable initial symptoms of human listeriosis Question Number (%)

Have you experienced disease episodes characterized by symptoms

such as chills colds, nausea, vomiting, diarrhea, malaise and muscle

ache in respondent?

No

Yes

31 (20.7)

119 (79.3)

Have you experience symptoms to include headaches, stiff necks,

mental status changes, convulsions, pneumonia separately or

consequent to previous symptoms?

No

Yes

94 (62.7)

56 (37.3)

4.3.2.7 Occurrence of Pregnancy Related Abnormalities in Female Consumers

More than half the female consumers‘ population had suffered at least a pregnacy related

abnormality associated with spontanoues abortions, stillbirths and premature births. In

quite some proportion too, these conditions had occurred more than once. Spontanoues

abortions were the most common outcomes of these series of events including initial

symptoms and/ or progressive symptoms in most of the females. Premature births had also

ocurred in some individuals but at a much lower rate. Though stillbirths also occurred at a

rate quite faster and across a wider number of the female population, it was still smaller

compared to the occurrence of spontaneous abortions. The overwhelming observation was

83

that most experienced these abnormal pregnancy defects on the third trimester. In more

than half of the pregnant females who experienced these conditions, it occurred within a

week of the initial symptoms. In a few though, it occurred within two weeks and with less

than a fifth, took place much later (Table 4.27).

The high occurrence of these conditions within a few days to a week adds more urgency to

the situation. This was because of the casual relationship which seemed not to emphasize

so much the importance of the organism to the occurrence of these events but rather the

―pregnancy‖ or physiological state of the individual since by far most occurrences in the

victims did not take place more often beyond two weeks or even a month after initial

symptom. Furthermore, most of these females had these events in the third trimester where

it was expected that their immune response would have been significantly downregulated.

Table 4.27 Occurrence of pregnancy related abnormalities in female consumers Have you experienced spontaneous abortion, stillbirth and/ or

premature births before?

No

Yes

N/A

28 (33.7)

55 (66.3)

67 (44.7)

How often have you experienced spontaneous abortion(s) before?

Once

Twice

Three times

Four times

Five times

>Five times

20 (42.6)

14 (29.8)

8 (17.0)

2 (4.3)

2 (4.3)

1 (2.1)

How often have you experienced stillbirth(s) before?

Once

Twice

Three times

6 (85.7)

1 (14.3)

0 (0.0)

How often have you had premature birth(s)?

Once

2 (100.0)

84

Twice 0 (0.0)

During which period of gestation did spontaneous abortions/ stillbirths/

premature births occur?

1st Trimester

2nd Trimester

3rd Trimester

3 (5.5)

13 (23.6)

39 (70.9)

How long after the initial symptoms did pregnancy abnormalities

occur?

1-2days

3-7days

8-15days

16-30days

5 (9.1)

32 (58.2)

16 (29.1)

2 (3.6)

85

4.4 Results- Laboratory Analyses

4.4.1 Detection and Isolation of Listeria spp. and L. monocytogenes

Three enrichment broths were tested in the detection of L. monocytogenes, namely, UVM,

LEB and Frazer broths. Growth in the Frazer broth was very apparent, with colour change

from the initial golden yellow to dark green or black; unlike in the LEB which showed no

remarkable colour change (Figure 4.21).

Figure 4.21: Color changes after enrichment in UVM, LEB and Fraser broths

respectively

86

Figure 4.22: Color changes after enrichment in Fraser broth for retailed, production

and boiled samples consecutively from left to right

On the chromogenic OCLA agar plates, Listeria sp. appeared green generally but L.

monocytogenes developed a halo around its colonies after 24hrs incubation (Figure 4.23).

Figure 4.23: Colonies of Listeriae on OCLA. (a) Green without halo (b) Green with

halo

87

Colonies on PALCAM or Oxford agar plates were dark-green with dark haloes (Figure

4.24)

Figure 4.24: Colonies of Listeria species on (a) PALCAM Agar (b) Oxford (OXA)

Agar

Typical presumptive isolates from the different media were Gram- positive and catalase

positive. They did not take up the red color of Congo red dye, thus testing negative test for

encapsulation. At room temperature they showed motility in Citrate Indole Motility

medium (CIM) but motility was not observed above 30°C, which was characteristic of

Listeriae. The isolates suspected to be L. monocytogenes tested positive in the Beta-

hemolytic activity test. (Figures 4.25) are illustrations of hemolysis caused by S. aureus

isolate and a reference L. monocytogenes NCTC 11994 strain on sheep blood.

Figure 4.25: Blood hemolysis results: (a) S. aureus; (b) Isolate; (c) Reference strain

88

Tables 4.28 and 4.29 are summaries of the results of the characterization of the isolates.

These confirmed the detection of listeriae, including L. monocytogenes in the milk

samples.

Table 4. 28: Summary of the biochemical characteristics of Listeriae/ L.

monocytogenes

Characteristics Listeria. sp. L. monocytogenes

Motility 20-25°C + +

30-37°C - -

Esculein reaction + +

Gram‘s reaction + +

Capsule formation - -

Catalase activity + +

Hemolytic activity +/- (+)

Key + = positive reaction, - = negative reaction, +/- = negative reaction/ wide zone of

hemolytic activity, (+) = narrow zone of hemolytic activity

Table 4.29: Morphological characteristics of Listeriae/ L. monocytogenes*

Morphological characteristics Listeria spp.

Shape(s) Rod

Type(s) of margin Entire

Colony elevation(s) Raised (convex)

Colony texture(s) Smooth/ Shiny (24-48 Hrs. incubation)

Rough/ signs of movements (prolonged incubation)

Light transmission(s) Translucent

Cell diameter 0.5-1.5 mm (24 Hrs. incubation)

3.0- 5.0 mm (prolonged incubation)

NB: Growth was on Nutrient agar

89

4.4.2 PH Changes along the Milk Value Chain

Generally, pH of samples decreased from production to fermentation where it was the least

(p< 0.05). This has been captured on Table 4.30 and Appendices G (I) (III) and (II).

Average pH at production was 6.74 though the highest was 6.85. At retail, the average pH

was 6.66 prior to boiling. After boiling, the average pH was 6.44 and the range was 6.24-

6.71. As expected, there was a much steeper decrease in pH after fermentation where the

average was 4.05 and the least was 3.80.

Table 4.30 Descriptive statistics on pH changes from production to fermentation

Sample

Mean Minimum Maximum Standard

deviation

Raw 6.738 6.650 6.850 0.040

Retailed 6.658 6.420 6.760 0.090

Boiled 6.438 6.240 6.710 0.167

Fermented 4.051 3.800 4.460 0.158

Documentaries by several authors including Murphy and Boor, (2008) Cousins, (1982) &

Frank et al., (1993) have emphasized the crucial roles time and temperature of keeping raw

milk affected its pH as this could lead to the growth of organisms that could alter it.

Considering that milk is a buffer, such significant changes in pH has been attributed to

microbial activity (O'Mahony, 1988). Mastitis causing organisms are clearly of probable

concern. Organisms of most interest as far as mastitis is concerned are S. aureus, S.

Agalactiae, streptococci and coliforms (Oliver et al., 2002), Listeriae sp. (Sanaa et al.,

1993). Considering its shear endurance and obstinacy (Blackman and Frank, 1996), the

favorable daily average temperature of 27-32ºC in the environment of its trade (IBIS,

2003), the non- existence of chilling during transports (Kivaria, 2006), the distance from

production to retail, and the general lack of hygienic standards along such trades (Ghana:

90

FAO/ WB CP, 2005), the isolation of L. monocytogenes from the milk/milk product, was

thus understandably relevant.

After boiling, the average pH was 6.44 and the range was 6.24- 6.71. Often times,

reduction in pH was due to fermentation and/ or the deliberate addition of organic acids.

However, drop in pH also occurred when milk was let to stand for some time or had

received some heat treatment. The process of the latter has been illustrated in Equation 4.

Equation 4: Process of Decrease in pH of milk with Heating

…………………………………………….. (4)

Upon heating, the buffer capacity of milk salts changed, carbon dioxide is released,

organic acids are produced, and Tricalcium phosphate and casein phosphate are

precipitated with the release H+ (ion) (Magee and Harvey, 1926). Hence, the variances in

pH could be suggestive of the inconsistencies in inadequacy of the heating process.

The pH values of samples after fermentation decreased to less than 4.0 in a good

proportion (i.e. in 24 samples which represented (31.6%)). However, with most (52

samples or 68.4%) pH was observed above 4.0. The range was between 3.80- 4.46. This

showed gross inconsistencies in levels of fermentation achieved, a problem, to which

Obodai and Dodd, (2005) have advocated for the use of starter cultures for the production

of uniform product.

91

4.4.3 Prevalence of Listeriae in Milk Samples

Listeriae were detected in 203 of 304 samples, giving a prevalence of about 67% (Table

4.31). L. monocytogenes was detected in 142 (47%) of samples. Of the 76 milk samples

collected at production sites (farms), Listeria spp. were detected in 72.4%, but L.

monocytogenes in 42.1%. Screening of pre-boiled and pre-fermented samples on the retail

market showed detection rates of 96% and 79%, respectively, for Listeria spp. and L.

monocytogenes out of 76 samples. In the boiled samples however, detection was 23.7%

and 18.4% respectively, out of 76 samples. Listeria spp. and L. monocytogenes were

detected in 75% and 59% respectively out of 76 fermented milk samples.

Table 4.31: Detection and isolation of Listeriae/ L. monocytogenes in samples

State of Dairy Product

Production Retail Boiled Fermented

L. spp. L. m L. spp. L. m L. spp. L. m L. spp. L. m

Locations

Dorymu-1 2 - 4 4 - - 2 2

Kpone-2 4 - 4 4 1 1 2 2

Mampoh-3 3 3 4 4 - - 3 2

Mataheko-4 2 2 4 4 - - 4 3

Prampram-5 2 2 4 2 - - 4 3

Gbetseli-6 2 4 4 4 4 4 3 4

Mobole-7 4 - 2 2 - - 3 1

Suta-8 2 3 4 4 - - 3 2

Manya-9 4 4 4 4 - - 3 3

Odumase-10 3 2 4 3 2 2 3 4

Afienya-11 4 2 4 3 2 - 4 3

Tachukope-12 1 - 4 4 1 1 4 2

Dodowa-13 4 4 4 4 - - 2 2

Okyibleku-14 4 2 3 2 2 2 2 2

Apolonia-15 2 2 4 2 - - 3 2

Asebi-16 2 - 4 2 2 2 2 2

Katamanso-17 4 2 4 2 - - 4 4

Ablekuma-18 2 - 4 2 - - 2 -

Dawhenya-19 4 - 4 4 2 2 4 2

Total prevalence 55

(72.4)

32

(42.1)

73

(96.1)

60

(78.9)

18

(23.7)

14

(18.4)

57

(75.0)

45

(59.2)

NB: L. spp. - Listeria species; L. m- L. monocytogenes

92

The mean prevalence values of Listeria spp. and L. monocytogenes varied among the

samples taken at various times and at various points. Generally, values were higher for the

raw unprocessed samples collected at retail point. Listeria spp. was detected in almost all

samples, and L. monocytogenes was detected in 80% of samples. These values were

significantly higher than the prevalence in the samples collected at the milk production

points (sources). The milk pathways established, suggested the possibility of growth of the

pathogens from the production sites to the markets. Practices like bulking of milk, use of

plastic containers that are difficult to effectively clean, transport through distances by

Assemblers without cold-chain, are all factors that may influence the growth of the

pathogen in the milk. Within farm samples, only in one case was the pathogen detected in

the two batches of samples collected, which means that contamination is more sporadic, as

reported by Waak et al., (2002). The results generally showed high prevalence of the

pathogen at the farm level. Kells and Gilmour, (2003), also reported prevalence of up to

44% for Listeriae and 22.2% for L. monocytogenes) in raw milk samples on farm.

The prevalence of Listeriae in boiled samples suggests inadequate heating. Although

Listeriae is said to be recalcitrant, and are the most heat resistant non-spore forming

bacteria, effective pasteurization is expected to completely inactivate them. The practice of

boiling, as observed, involve holding the raw milk in big aluminum pots on stoves fueled

with charcoal or firewood (Figure 4. 26 (a)). Generally it takes time for the milk to heat up,

and there are no thermocouples to check cooking temperatures. Milk vending begins as

soon as the milk is placed on fire and the milk is fetched/ dispensed with the same

container used to transfer milk into pots (Figure 4.2(b)). The possibility of recontamination

is thus highly eminent.

93

Figure 4.26: Pot of milk on coal fire (a) Vessel for dishing out milk (b)

The higher prevalence for the fermented milk may be explained by the inadequate

acidification of the milk. Starter cultures are not added, fermentation is spontaneous and

the fermentation temperatures are not controlled. There is also a possibility of cross

contamination from utensils.

4.4.3 Mean Counts of L. monocytogenes in Milk Samples

Levels of L. monocytogenes concentration varied significantly along the milk value chain.

Generally, mean counts increased from samples at production to its highest at retail (i.e. on

the market prior to boiling) then decreased to their lowest after boiling only to

subsequently increase at fermentation to near farm level counts (P= 0.00) (Table 4.32 and

Appendix H (I), (II) & (III). This was a strong indicator that handling, and therefore

hygiene, played a very important role in the contamination of milk/ milk product with the

organism. L. monocytogenes was detected at levels of 100CFU/ ml in 36.4% of samples;

with the highest being 1467CFU/ ml. At retail, 57.9% of samples had levels of

≥100CFU/ml (i.e. an increase of about 21.48%) and highest mean count was 1733CFU/

mL. For boiled milk samples 6.9% of samples were positive for L. monocytogenes at ≥

94

100CFU/ mL (i.e. a decrease of 14.9%). Yet after fermentation, 46.1% had mean counts of

≥ 100CFU/ mL (which represented an increase again of about 31.2%) with the highest at

1533CFU/ ml.

Table 4.32: Descriptive statistics on L. monocytogenes counts from production to

fermentation

Sample

Mean

(x10CFU/m

L)

Minimum

(x10CFU/m

L)

Maximum

(x10CFU/mL)

Standard

deviation (x

10CFU/mL)

Raw 12.97 0.0 146.7 25.83

Retailed 28.64 0.0 173.3 40.41

Boiled 2.75 0.0 66.7 7.60

Fermented 14.71 0.0 153.3 16.64

The highest mean count of 1733CFU/mL was observed with raw milk at retail with 57.9%

(44) of 76 samples having mean counts ≥ 100CFU/ mL. Factors acknowledged to play

significant roles in such observed increases in the micro flora of milk included

temperature, mode of transportation, distance to destination (Luck, 1986; Murphy and

Boor, 2008) improper handling equipment and adulteration (Omore et al., 2003); and the

lack of refrigeration along such channels (Kivaria et al., 2006)

As reported earlier, the boiling effectively reduced the rate of detections of L.

monocytogenes. It likewise reduced levels of contaminations. Only 6.6% (5) of boiled

samples had mean counts ≥100CFU/mL for L. monocytogenes, which was in violation of

the <100CFU/mL set by the EC and were most likely the result of inadequate heating and/

or post processing contamination. There was 79% non-detection in 76 samples and the

remaining 12 samples had counts of ≥10CFU/mL but at less than 100CFU/ mL. These

95

observations attest to the documented effectiveness of heat treatment in eliminating L.

monocytogenes from foods (USDA, 1981; Bradshaw et al., 1987 & Donnelly and Briggs,

1986).

The mean counts in 46.1% (35) of fermented samples were ≥100CFU/mL whereas there

were no counts in 40.9% (31) of the samples. The practice of backslopping in the

fermentation process could possibly have re-introduced the microorganism into boiled

samples. This probably was the reason why there was high rate and levels of contamination

in fermented samples even after boiling had been done. Also, slow development of acid

has been recognized to also allow initial proliferation and acid adaptation of L.

monocytogenes strains prior to the acid build up. A study in Ethiopia on the souring of raw

milk into Ergo found that some L. monocytogenes strains (i.e. WS 2300 and WS 2303)

grew rapidly within the first 12 hrs. Levels though declined subsequently and at 48 h

counts became undetectable for both strains WS2300 and WS 2302. Another strain WS

2301 though was still detected until at 60 h when pH had decreased further (Ashenafi et

al., 1994). In response to this problem, authors such as Obodai and Dodd, (2005) have

advocated for the development and use of starter culture to get more consistent product.

Other authors who reached conclusions which also favored the rapid development of acid

as a means of improving the safety of fermented foods include Gran et al., (2003); Dalu

and Feresu, (1996) & Feresu and Nyati (1990); & Schaak and Marth, (1988).

Figure 4.27 is a milk distribution model indicating average levels of risk of L.

monocytogenes contamination in milk destined for consumption on the informal market.

96

Contamination Level

None

Low

39.0 L 54.0 L Moderate

67.5 L High

Highest

63.0 L

36.0 L 63.0 L

45.0L 81.0 L

63.0 L 33.8L

.

41.5L 27.0 L 49.5 L

.

27.0L 54.0 L

31.5L 45.0L

36.0 L 81.0 L


Figure 4.27: Quantitative milk distribution model: production to retail

Manya

Mampoh, Shai hills

Okyibleku

Dodowa

Suta

Tachukope

Odumase


Katamanso

Ablekuma

Afienya

Apolonia

Dawhenya

Mataheko

Kpone barrier

Prampram

Gbetseli

Mobole

Doryum Asebi


97

4.5 Risk Assessment

4.5.1 Exposure Assessment

This involved the determination of the quantities and frequencies at which milk/ milk

products were consumed by a section of the population at Ashaiman. By this, the volumes

and hence doses of L. monocytogenes consumed in milk/ milk products were determined.

Table 4.33 is the average daily/ annual consumptions of milk/ milk products for the

consuming population at Ashaiman.

Table 4.33: Amounts of milk/ milk products consumed per day at Ashaiman

Food type Respondents no

who consumed

product

Average consumption

(ml) per day

Average

consumption (ml)

per annum

Milk at production 1.0 *75.16±70.2 901.92

Milk at retail 46.0 **436.89±95.6 5242.68

Boiled milk 116.0 **654.56±125.84 7854.72

Fermented milk 141.0 **23661±113.38 283932

*Data received from farmers. **Data received from retailers’ questionnaire. All

other data was collected from consumers’ questionnaires.

NB: It was assumed that the daily consumption probability was the same on every

day of the year for individuals

4.5.1.1Need for Simulation in Assessing Risk

Analysis and therefore conclusions from studies were previously based on point estimates.

With this however, only certain markers (such as the mean, mode and median) were used

to interpret results. This did not give the accurate picture of the whole system being

studied. Increasingly, this has been replaced by the probability distribution method (that

takes into account variability and uncertainty) which represented all possible outcomes

through simulation (i.e. doing several what-ifs). Imaginably, the answer (i.e. the explicit

answer) was complex and usually losses its meaning. However, the growing use of

98

computers and the promise that these techniques can be commonly available to all

decision-makers seems to have solved this problem. Typically simulation modelling

software available for use on computers include @Risk, Crystal Ball and Analytica. The

outcomes take the form of distributions which can be explain based on the distribution

type.

4.5.1.2 Simulated L. monocytogenes Contaminated Dairy Products at Consumption

The simulated distribution for the number of L. monocytogenes in contaminated milk at

production and retail, and also for boiled and fermented milk servings was constructed

from the serving sizes and from the distribution of concentrations at point of consumption.

Quantities varied among 16 simulations, each comprising 32 000 iterations (Figures 4.28-

4.39 with their summaries in Tables 4.34-4.36).

99

Figure 4.28: A graph of probability density against Log10CFU of L. monocytogenes in

a ml of milk at production

100


a ml of milk at retail

101


a ml of boiled milk

102


a ml of fermented milk

Table 4.34: Summary of main indicator parameters per ml of milk/ milk products

Milk at production Milk at retail Boiled milk Fermented milk

5.0% 0.125936 1.378276 -0.0766 0.537164

95.0% 4.948085 5.655511 3.609785 4.978406

Min -1.93703 -0.31086 -1.5383 -0.73142

Mean 2.537011 3.516893 1.766592 2.757785

Max 7.474042 7.827755 4.804892 7.489203

103


a serving of milk at production

104

Figure 4. 33: A graph of probability density against Log10CFU of L. monocytogenes in

a serving of milk at retail

105


a serving of boiled milk

106


a serving of fermented milk

Table 4.35 Summary of main indicator parameters per serving of milk/ milk products


5.0% 1.121518 1.351997 1.191799 1.55023

95.0% 14.17448 14.6977 12.27205 13.56536

Min -4.43924 -4.324 -4.4041 -4.22489

Mean 7.648 8.024849 6.731927 7.557797

Max 19.58724 19.84885 18.63603 19.28268

107


total daily servings of milk at production

108


total daily servings of milk at retail

109


total daily servings of boiled milk

110


total daily servings of fermented milk

Table 4.36: Summary of main indicator parameters for total daily consumption of

milk/ milk products


5.0% -0.93678 -0.13075 -0.3327 -0.95751

95.0% 17.34901 19.38288 17.48604 24.36474

Min -7.96839 -7.56537 -7.66635 -10.4788

Mean 8.206118 9.626065 8.576669 11.70362

Max 23.67451 27.19144 26.24302 37.18237

111

4.5.1.3 Exposure Outcome

For quantities of 1 ml of the various milk products, 5% severest exposure was lowest for

boiled milk (i.e. 95% chance of that not happening was highest for boiled milk

consumption and then fermented milk). It was highest for raw milk at retail. However, the

trend would change after the volumes of consumption were considered; the 5% chance of

severest exposure and therefore infection was highest for naturally fermented milk

followed by raw milk at retail per serving; and when overall consumption was considered

it was still highest for naturally fermented milk followed by boiled milk since these two

were the most consumed (Figure 4.28- 4.39)

Mean exposure was highest, significantly, for raw milk at retail when a ml and serving

were considered. However, when the total amount of milk/ milk product consumed was

considered, fermented milk, and later boiled milk, had the highest mean exposures (Table

4.34- 4.36).

Considering the widths of Figures 4.28- 4.39 it also become evident that overall fermented

milk followed by boiled milk were more likely to cause exposure because of the high

levels of consumption of these products.

The following are some selected quantiles from simulated distributions of log10 number of

L. monocytogenes organisms in contaminated milk/ milk product servings at point of

consumption (Table 4.37).

112

Table 4.37: Selected Quantiles from Simulated Distributions of log10 Number of L.

monocytogenes Organisms in Contaminated Milk/ Milk Product Servings at Point of

Consumption

Raw milk Quantile (Log10CFU/ml) Cumulative probability

0.05 0.167

0.10 0. 333

0.15 0.500

0.20 0.667

0.25 0.833

0. 30 1.00

Retailed milk Quantile (Log10CFU/ml) Cumulative probability

0.05 0.167

0.10 0. 333

0.15 0.500

0.20 0.667

0.25 0.833

0. 30 1.00

Boiled milk Quantile (Log10CFU/ml) Cumulative probability

0.05 0.14 3

0.10 0.286

0.15 0.429

0.20 0.571

0.25 0.714

0. 30 0.857

0. 35 1.00

Fermented milk Quantile (Log10CFU) Cumulative probability

0.05 0.167

0.10 0. 333

0.15 0.500

0.20 0.667

0.25 0.833

0. 30 1.00

113

4.5.2 Dose- Response Relationship

Exponential Model assumes that each organism has the potential to cause disease. This

was represented by the r- value. This r- value is the probability that a single bacteria cell

could cause disease. The Exponential Model was used for the modeling of the probability

of illnesses from consumption of food because of its fitting for modeling severe listeriosis,

simplicity as a single parameter model and its linear nature when extrapolated to low dose

ranges.

Equation 5: Exponential Model for Dose-Response

P = 1 -e-r*N

…………………………………………………………………..…………. (5)

Where N= x*Y

Where x= Concentration per grams

Where Y= Grams per serving

This was based on Buchanan et al., (1997) who conservatively predicted morbidity for

fifty per cent of immune compromise individuals. Estimation of highest numbers assumed

in food was 104 CFU since numbers in food were not very large as compare with others

like the FDA (2001) exponential models where numbers ranged from 108-10

10 CFU.

An assumption that provided support to the application of this model was that of similar

numbers of susceptible individuals and healthy people in the population with consumption

of foods being similar in the two populations. Another applicable assumption was the

apparent lack of evidence to suggest that the risk from consuming a specific number of

Listeria varies for the equivalent populations from country to country (WHO/ FAO, 2004).

Table 4.38 is the simulated means of the probabilities of illness from the consumption of a

114

serving of milk/ milk products by consumers at Ashaiman. Ten simulations were done with

10,000 iterations. Figures 4.40- 4.43 are diagrams of exponential dose- response models

developed for milk/ milk products consumption.

Table 4.38: Probability of illness for consumers at Ashaiman estimated for different

levels of L. monocytogenes at the time of consumption with milk/ milk products

contaminated at those levels.

Milk/ milk product

code

Dose (CFU) Log10 dose

(log10

CFU/serving)

Mean probability

of illness per

serving

Milk at production 5.40x104 4.732142 9.0x10-10

Milk at retail 1.19x105 5.075414 9.39x10-10

Boiled milk 9.71x103 3.986975 7.85x10-10

Fermented milk 6.483104 4.811235 8.94x10-10

NB: Using the risk from a dose of 1 CFU as reference. R-value was selected based on

work by Buchanan et al., 1997, which was deliberately conservative at 1.179 x 10-10


associated with milk at production

115


associated with milk at retail


associated with boiled milk

116


associated with fermented milk

4.5.3. Risk Characterization Results

This involved the integration of the dose- response model per serving of milk/ milk

product and the number of servings. This gave a result that predicted the average

probability of serious illness (invasive listeriosis). The results therefore were more credible

across the milk/ milk products consuming populace at Ashaiman than for individual

consumers. Ten simulations were done with 10,000 iterations. The results, summarized,

have been presented on Table 4.39.

117

Table 4.39: Probability of illness for consumers at Ashaiman estimated for different

levels of L. monocytogenes at the time of consumption with milk/ milk products

contaminated at those levels.

Milk/ milk product code Mean probability of illness for consumers

Milk at production 1.64x10-9

Milk at retail 1.02x10-8

Boiled milk 1.30x10-8

Fermented milk 5.45x10-7

Source: From simulated values of the number of servings of milk/milk product

FIgure 4.44 represents probable routes for occurrence of listreiosis from informally sold

milk/ milk product consumption.

118

Occurrence

hazard

And

Or

Initiating

Figure 4.44: Fault tree of the events that could have led to the exposure of L.

monocytogenes to consumers of informally marketed milk/ milk product at Ashaiman

Infected animals Other contamination

sources

Lm is present in milk Milk not adequately pasteurized Milk enters the informal mkts

Supply chain permits survival Milk not boiled by trader

Milk contains Lm

Cross-

contaminatio

n

Milk consumed

without boiling Cross-

contaminatio

Other sources

of

contamination

Inadequately fermented milk

Milk consumed with viable Lm Susceptible individual

Other sources of

infection

Initiating

event

Illness due to

L. monocytogenes

119

4.5.4 Determining Critical Points for Intervention

A sensitivity analysis was performed to find critical areas of the chain of the production of

milk and milk products where control could be achieved. This was done using the

Spearman‘s rank correlation coefficient, which ranks the various factors according to

importance from a scale of -1 (direct negative correlation) to 1 (direct positive correlation):

the higher the magnitude, the more its importance to outcome. The implication of this was

high for the application of hygienic measures to achieve safety of products. Figure 4.45

indicates that the retail level contribute most to the production of listeria contaminate milk/

milk product at 0.8 whiles both boiling and fermentation to varying degrees reduced the

production of contaminated product. The strongest factor though that could be used to

address the issue was boiling/ heat treatment at -0.82

Figure 4.45: Spearman rank correlation between the estimated probabilities of L.

monocytogenes contamination for the various processes involve in milk/ milk

products production according to the PRM.

120

CHAPTER FIVE

CONCLUSIONS AND RECOMMENDATIONS

5.1 Conclusions

A high proportion (47%) of milk and milk products on the informal markets were

contaminated with L. monocytogenes. This suggests a commensurate risk of exposure and

hence infection as a result of consumption.

Prevalence/ levels of contamination did not vary significantly between the sites (P<0.05).

This indicated that milk production practices were similar on the various farms sites.

However, prevalence/ levels of contamination differed significantly between states

(p<0.05). This also underscored how crucial handling of milk along the value chain was.

Prevalence/ level of contamination increased from farm (at 42%) to their highest when

they had been transported unto the milk market (at 79%) prior to boiling.

Boiling was found as the most effective means of controlling the organism in the milk.

The boiling process largely eliminated all the organisms in the milk samples though there

were detections in 18% of boiled samples. This could be attributed to post- process

contamination.

The natural souring of milk as practiced on the milk markets at Ashaiman seemed to play

an inadequate role in reducing exposure to potential L. monocytogenes due to its

consumption. Prevalence was at 45%. However, the risk of exposure and hence infection

from this category of milk products per mL was lower than that due to the consumption of

121

raw milk purchased on the market. Nevertheless, this was the most patronized milk

product. Hence, overall, its risk implications were highest.

5.2 Recommendations

It is recommended that farmers wash teat of cows, hands and other milking equipment

adequately with a suitable antiseptic to prevent contamination of raw milk. Subsequently,

milk must be stored in the aluminum cans recommended by the FAO (which are easier to

clean), and in the absence of refrigeration, must be transported during the cool of the day.

.

On the markets, raw milk must be subjected to effective heat treatment (boiling or

pasteurization) before souring and/ or retailing to consumers as this was observed to

eliminate the organism. Also, with the probability of post-process contamination, it is

recommended that different vessels are used for dishing out different products during sale.

L. monocytogenes was detected in some boiled samples after only fermentation. Hence,

after boiling it is vitally important that hygiene be maintained to prevent recontamination

of product. Also, the efficacy of the backslopping process cannot be without dispute. Most

fermented samples in which there was non- detection of L. monocytogenes had pH≤ 4.0.

However, milk product with pH<4.0 were not appealing to consumers as they were too

sour. Hence, care must be taken to prevent contamination after boiling.

Finally, agents along the milk value chain must be educated on the hygienic handling of

milk/ milk products as contamination of milk was found at all levels of the milk value

122

chain. Consumers should also be made aware of the danger they could inadvertently cause

themselves by not handling milk/ milk products in a safe manner.

123

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138

APPENDICES

APPENDIX A

Top Ten Diseases in Ashaiman and TMA

Top 10- Disease in Ashaiman (AZC) Top 10 Diseases in TMA

1. Malaria 13,996 Malaria 26922

2. Acute Respiratory Infections 2,195 Diarrhoea 1847

3. Skin Diseases 1,563 STDs 290

4. Diarrhoea 1,264 Enteric 456

5. Chicken Pox 270 Chicken Pox 174

6. Hypertension 232 HIV + 34

7. Acute Ear Infection 162 Tuberculosis 90

8. Home & Occupatn. Accidents 153 Viral Hepatis 30

9. Acute Eye Infection 150 Measles 30

10. Typhoid 139 Schistosomiasis 16

Source: Metropolitan Health Directorate, 2008

APPENDIX B (I)

Areas which produce milk sent to Ashaiman (PRA)

1. Mo bole ( town/ peri-urban) 23.5km

2. Gbetsele (town) 13.0km

3. Dwahenya (production area) 24.0km

4. Okyibleku (production area) 23.5km

5. Ablekuma (town) 18.8km

6. Congo (production area) >80.0km

7. Afienya (town) 22.3km

8. Bundasi (production area) 30.0km

9. Yoma (production area) 30.0km

10. Katamanso (peri-urban) 12km

11. Tsatsukope 34.3km

12. Akuse/ Okoenya >80.0km

13. Manya 40.0km

14. Prampram (Ningo) 25.0km

15. Asutsuare junctn (production town/ peri-urban) 80.0km

16. Adjei kojo 3.0km

17. Santeo (town) 10km

18. Suta 35.0km

19. Mataheko (town) 14.0km

20. Apolonia (peri-urban) 17.9km

21. Mampoh 29.3km

22. Asabi (production area) 40.0km

23. Kakasunanka 9.0km

139

24. Akufo panya (town) 48.0km

25. Kpone barrier 20.3km

26. Kusuberi (town) 16.9km

27. Oyibi 22.5km

28. Odumase 30.0km

29. Dodowa 43.0km

APPENDIX B (II)

Stratification of Milk Producing Areas by Geographic Locations

Group A

Mo bole, Mataheko, Gbetseli, Ablekuma,

Afienya, Akuse/ Okoenya, Kakasunanka

Group B

Kpone barrier, Dawhenya, Prampram,

Adjei kojo, Santeo, Bundasi, Congo

Group C

Tsatukope, Dorymu, Asabi, Manya,

Akufo panya, Asutsuare junctn,

Okusuberi,

Group D

Odumase, Dodowa

Group E

Apolonia, Katamanso

Group F

Okyibleku, Dodowa, Suta, Oyibi

APPENDIX C (I)

Constraints to the Livelihood of Famers

Constraint Importance

Disease

Availability of pasture/ low milk production

70

20

Market access 7

Farm management 3

144

APPENDIX C (II)

Results of the Proportional Piling of the Disease Symptoms

Symptoms Prevalence (%) Economic/

Livelihood impact

(%)

Preferred

options for

solution (%)

Boils 5 1 6

In appetence 4 5 5

Skinny but eats well 9 0 0

Inflamed udder 3 13 14

Facial paralysis 2 3 1

Dullness 4 4 1

Deep coughs/ breathes 11 17 25

Sudden deaths 6 7 2

Watery/Bloody diarrhea 9 7 8

Drooling tongue 7 2 0

Stillbirths/ Abortions 9 10 4

Premature births 7 7 3

Circling movements 1 1 1

Swollen/ soured feet 9 14 15

Sudden inability to walk 3 0 0

Rashes 11 10 20

TOTAL 100 100 100

APPENDIX C (III)

Correlation for proportional piling for disease symptoms

Correlation

Prevalence 0.796

Importance 0.904

Correlation is significant at the 0.01 level (2-tailed).

145

APPENDIX D (I)

Matrix scoring for livelihood constraints for Retailers Percentages in parenthesis

Income Food

consumption

Security Other

utilities

Access to markets 49 (54.4) 45 (50.0) 44 (48.9) 49 (54.4)

Availability of milk 25 (27.8) 20 (22.2) 19 (21.1) 25 (27.8)

Access to credit 10 (11.1) 12 (13.3) 18 (20.0) 7 (7.8)

Transportation 4 (4.4) 7 (7.8) 3 (3.3) 5 (5.6)

Hygiene 2 (2.2) 6 (6.7) 6 (6.7) 4 (4.4)

Total 90 (100.0) 90 (100.0) 90 (100.0) 90 (100.0)

APPENDIX D (II)

Correlations for matrix scoring for retailers

Income Food consumption Other utilities Security

Income 1.000 0.991 0.984 0.995

Food consumption 0.991 1.000 0.993 0.987

Other utilities 0.984 0.993 1.000 0.975

Security 0.995 0.987 0.975 1.000

All correlation significant at the 0.01 level (2-tailed)

146

APPENDIX E

Supply of Milk from Production to Retailer- Quantities in Liters (1gallon= 4.5L)

Production sites Thursday Friday Sunday Mean SD

Dorymu-1 54.0 54.0 54.0 54.0 ±0.00

Kpone-2 54.0 54.0 54.0 54.0 ±0.00

Mampoh-3 63.0 63.0 64.0 63.0 ±0.00

Mataheko-4 45.0 45.0 45.0 45.0 ±0.00

Prampram-5 33.5 33.8 34.0 33.8 ±0.25

Gbetseli-6 81.0 81.0 81.0 81.0 ±0.00

Mobole-7 63.0 63.0 63.0 63.0 ±0.00

Suta-8 36.0 36.0 36.0 36.0 ±0.00

Manya-9 65.5 67.5 69.5 67.5 ±2.00

Odumase-10 45.0 45.0 45.0 45.0 ±0.00

Afienya-11 27.0 27.0 27.0 27.0 ±0.00

Tachukope-12 81.0 81.0 81.0 81.0 ±0.00

Dodowa-13 63.0 63.0 63.0 63.0 ±0.00

Okyibleku-14 35.0 45.0 45.0 41.5 ±5.77

Apolonia-15 31.5 31.5 31.5 31.5 ±0.00

Asebi-16 39.0 39.0 39.0 39.0 ±0.00

Katamanso-17 36.0 36.0 36.0 36.0 ±0.00

Ablekuma-18 27.0 27.0 27.0 27.0 ±0.00

Dawhenya-19 50.0 48.5 50.0 49.5 ±0.87

147

APPENDIX F (I): CASE STUDY QUESTIONNAIRE- RETAILERS

Food sales/ consumption data collection

DEPARTMENT OF NUTRITION AND FOOD SCIENCE, UNIVERSITY OF

GHANA

A survey on the sales / consumption of raw milk/ milk product from the informal

market: A case study at Ashaiman, Greater Accra, Ghana.

Questionnaire for Data on Respondents

A. Demographic Data on Respondents

Data collector (name) ………………………………………………………………………

Respondent‘s code …………………………………………………………………………

Contact and location …………………………………………………………………………

Sex (M/F) …………………………… Age ………………………………………………..

Ethnicity ……………………………………………………………………………………

Religious inclination ………………………………………………………………………

Highest educational level ……………………………………………………………………

Occupation …………………………………………………………………………………

Health institution attended…………………………………………………………………

148

Date……………………

1. How long have you been selling

milk/ milk product? […]

a. <1 years

b. 1-2 years

c. 3-5 years

d. 6-10years

e. > 10years specify …………

2. How many days in a week do you

sell milk/ milk product during the

dry season? […]

a. < 2

b. 2-4

c. 5

d. 6

e. 7

3. How many days in a week do you

sell milk/ milk product during the

rainy season? […]

a. < 2

b. 2-4

c. 5

d. 6

e. 7

4. What type(s) of milk product do

you sell? [ ]

a. Raw milk only

b. Boiled milk only

c. Naturally fermented milk only

d. Other specify ………………

5. Who are your usual customers?

a. Individuals

b. Cooperate bodies

c. Institutions


6. What quantity of milk/ milk

product do you sell in the dry

season? [ ]

Product Qty

Raw milk …

Boiled milk …

Fermented milk …

7. What is your source of raw milk

supply? [ ]

a. Kraal/ farm

b. Assembler

c. Hawkers

d. Other specify …………….

8. What period(s) do you receive

raw milk supply in the dry

season? […]

a. Early mornings(before7-8:30

am)

b. Late mornings (8:31-11:

30am)

c. Afternoons (11:31-2: 00pm)

d. Late afternoons (> 2: 00pm)

e. Other specify ………………

9. What period(s) do you receive

raw milk supply in the dry

season? […]

a. Early mornings(before7-8:30

am)

b. Late mornings(8:31-11:30am)

c. Afternoons (11:31-2:00pm)

d. Late afternoons (> 2: 00pm)


10. What quantities of milk do you

receive in the dry seasons? [ ]

a. 50-90L

b. 91-135L

c. 136-200L

d. >200L

11. What quantities of milk do you

receive in the rainy season? [ ]

a. 95-135gallons

b. 136-200L

c. 201-270L

149

d. >270L

12. As far as you know do your

suppliers have any formal training

in food hygiene? […]

a. No

b. Yes

13. Have you received any formal

training in food hygiene? […]

a. No

b. Yes

14. If YES, where did you receive it?

[ ]

a. Workshop

b. Seminar

c. Health institution

d. On job


15. How long was the training? [ ]

a. 1 day

b. 2-3 days

c. 4-6 days

d. 1 week


16. How much water do you use per

day? [ ]

a. <27L

b. 27- 45L

c. > 45L


17. What is the source of your water?

[ ]

a. Borehole

b. Rain water

c. Municipal tap water

d. Water vendors


18. How do you keep raw/ boiled/

fermented milk during sale? [ ]

a. Ambient

b. Chilled

c. Hot


19. If Chilled is temperature checked

regularly? [ ]

a. No

b. Yes

20. If YES, how do you respond to a

warming product? [ ]

a. By breaking ice block into it

b. Refrigerating it

c. Other specify ………………

21. Could consumption of milk/ milk

product be responsible for disease

in man? [ ]

a. No

b. Yes

22. Mention some means by which

milk/ milk product could be

responsible for disease in man

…………………………………………

…………………………………………

…………………………………

23. Mention some precautions to

prevent milk/ milk product

causing these diseases

…………………………………………

…………………………………………

…………………

24. Have you ever been infected with

a suspected case of foodborne

disease associated with milk

consumption? [ ]

a. No

b. Yes

25. Did you seek medical help? [ ]

a. No

b. Yes

26. Have you ever experienced a birth

abnormality such as spontaneous

150

abortions, still births and/ or

premature births?

a. No

b. Yes

27. If yes, how often have they

occurred? [ ]

Symptoms freq

Spontaneous abortions ………….

Stillbirths …………...

Premature births …………

28. If YES, was medical help sought?

a. No

b. Yes

29. In what state do you usually

receive milk from Assemblers??

[…]

a. Ambient

b. Hot

c. Chilled

30. Is milk sieved when being poured

into receptive containers? [ ]

a. No

b. Yes

31. If YES, with what is it done with?

a. A piece of cloth

b. A sieve made with net

c. Other

specify………………….

32. Do you wash sieve before use?

[…]

a. No

b. Yes

33. If YES, with what is it done? [ ]

a. Water only

b. Water and sponge

c. Water, sponge and soap


34. Are sieve/ cloth washed before

use on every physically separated

milk consignment? [ ]

a. No

b. Yes

35. At retailer what is the receptacle

for consumption? […]

a. Plastic bowls

b. Plastic rubbers

c. Other specify ………………

36. Are receptacle re-used?

a. No b. Yes

151

APPENDIX F (II): CASE STUDY QUESTIONNAIRES- CONSUMERS

Food sales/ consumption data collection

DEPARTMENT OF NUTRITION AND FOOD SCIENCE, UNIVERSITY OF GHANA

A survey on the sales / consumption of raw milk/ milk product from the informal market: A

case study at Ashaiman, Greater Accra, Ghana.

Questionnaire for Data on Respondents

B. Demographic Data on Respondents

Data collector (name) ………………………………………………………………………

Respondent‘s code …………………………………………………………………………

Contact and location …………………………………………………………………………

Sex (M/F) …………………………………. Age …………………………………………

Ethnicity ……………………………………………………………………………………

Religious inclination ………………………………………………………………………

Highest educational level ……………………………………………………………………

Occupation …………………………………………………………………………………

Health institution attended …………………………………………………………………

152

Date ……………………………

1.

How long have you been consuming milk /

milk products from the informal market at

Ashaiman? [ ]

a. <1 year

b. 1-2years

b. 3-5 years

c. 6-10 year

d. >10 years specify………………

2. Why do you consume milk/ milk

product sold through informal channel

with little regulations? […]

a. Culture

b. Taste appeal/ acquired taste

c. Availability

d. Affordability

e. Other specify …………………

3. Which of the produce below do

you consumed? […]

Product Rank

a. Milk from cow as-is …

b Boiled milk …

c. Naturally fermented milk …

d. Wagashi …

e. Other

specify……………………….

4. How often do you consume raw/

boiled/ fermented milk?

a. Twice daily

b. Once a day

c. Once every two days

d. Once a week

e. Once in two weeks

f. Other specify …………………

5. Have you ever received any formal

training in food hygiene? [ ]

a. No

b. Yes

6. If YES, where did you receive it

from? [ ]

a. Workshop

b. Seminar

c. Health institution

d. On job

e. Other (specify) ……………

7. How long was this training? [ ]

a. 1 day

b. 2-3days

c. 4-6 days

d. 1weeks

e. Other (specify) ……………

8. Are you satisfied with conditions

under which milk/ milk products were

sold? [ ]

a. No

b. Yes

9. If No, what can be done to improve

upon it?

……………………………………………

……………………………………………

……………………………

10. Could food be responsible for

disease in man? [ ]

a. No

b. Yes

11. If Yes, which of the following is a

symptom associated with foodborne

infections?

a. Diarrhea

b. Vomiting

c. Weight loss

d. Miscarriages/stillbirths/premature

births

12. Where do you purchase your milk/

milk product from? […]

a. Farm gate

b. Assembler

153

c. Retailer

d. Other specify

………………………

13. Do you consume product at the

point of sale? […]

Milk from cow as-is (a) Yes (B) No

Boiled milk (a) Yes (B) No

Naturally fermented (a) Yes (B) No

14. If No, how do you transport milk/

milk product? [ ]

a. On foot

b. By bicycle

c. By private vehicle

d. By public vehicle

e. Other

specify……………………….

15. How long does it take to travel to

the point of consumption

a. <30mins

b. 30-1Hr.

c. >1Hr.

16. At destination does raw/ boiled/

fermented milk receive any treatment

before consumption? [ ]

a. No

b. Yes

17. If YES. Please state it [ ]

Raw ……………………………

Boiled ………………………………

Fermented …………………………

18. If NO, are milk/ milk product

usually consumed immediately after

transportation? [ ]

a. No

b. Yes

19. If NO, are milk/ milk product

stored?

a. No

b. Yes

20. If YES, how is it stored? [ ]

a. At ambience

b. Refrigerated

c. Other specify

………………………

21. Does the storage compartment

usually contain other fresh or semi fresh

foods that also require refrigeration for

extending their shelf-life

a. No

b. Yes

22. If YES, are milk/ milk product

physically separated from these foods? [

]

a. No

b. Yes

23. How often is this compartment

opened usually during the storage? [ ]

a. Not freq. (once in ≥ 1 hr.)

b. Quite freq. (once every 30mins-

1hr.)

c. Freq. (≤ 30min)

d. Other specify …………………

24. How long are milk and milk

products often stored before consumption?

[ ]

a. < 1Hr.

b. 1-2Hr.

c. >2Hr.


25. Are milk/ milk product consumed

immediately upon removal from storage? [

]

a. No

b. Yes

26. If NO, is any treatment given it

before consumption? [ ]

a. No

b. Yes

DISEASES ASSOCIATED WITH

CONSUMPTION

27. Have you experienced disease

episodes characterized by symptoms such

as chills colds, nausea, vomiting, diarrhea,

malaise and muscle ache in respondent?

154

? […]

f. No

g. Yes

28. Have you experience symptoms

including headaches, stiff necks, mental

status changes, convulsions, pneumonia

separately or consequent to previous

symptoms? [ ]

a. No

b. Yes

29. Have you had spontaneous

abortion, stillbirth and/ or premature births

before? [ ]

a. No

b. Yes

30. How often have the symptoms of

#29 occurred? [ ]

a. Once

b. Twice

c. Thrice

d. Four times

e. > Four times specify ………

31. During which period of gestation

did spontaneous abortions/ stillbirths/

premature births occur? [ ]

a. First trimester

b. Second trimester

c. Third trimester

32. How long after the initial

symptoms did pregnancy abnormalities

occur? [ ]

a. 1-2 days

b. 3-7days

c. 8-15days


APPENDIX G (I)

Mean PH of Milk/ Milk Products along the Value Chain

Mean PH of Milk/ Milk Products Along the Value Chain

Serial No. Production Retail Boil Fermented

1 6.69±0.00 6.42±0.01 6.27±0.00 3.8±0.00

2 6.75±0.00 6.69±0.00 6.29±0.00 3.81±0.00

3 6.74±0.00 6.72±0.01 6.31±0.01 4.04±0.02

4 6.73±0.01 6.71±0.00 6.44±0.02 4.07±0.02

5 6.71±0.01 6.61±0.01 6.49±0.01 4.21±0.00

6 6.73±0.00 6.68±0.00 6.58±0.01 4.18±0.01

7 6.73±0.01 6.71±0.01 6.28±0.00 4.09±0.01

8 6.74±0.01 6.72±0.01 6.71±0.00 4.02±0.01

9 6.76±0.01 6.69±0.01 6.31±0.00 4.08±0.00

10 6.72±0.00 6.70±0.00 6.69±0.00 4.10±0.00

11 6.71±0.01 6.69±0.00 6.63±0.00 4.01±0.00

12 6.71±0.01 6.65±0.01 6.69±0.00 4.10±0.00

13 6.73±0.00 6.45±0.01 6.25±0.00 3.81±0.00

14 6.76±0.01 6.72±0.01 6.68±0.01 4.17±0.01

15 6.65±0.01 6.60±1.08 6.28±0.01 3.86±0.01

16 6.73±0.01 6.72±0.00 6.26±0.00 3.82±0.00

17 6.73±0.01 6.71±0.00 6.24±0.01 3.86±0.01

18 6.68±0.01 6.48±0.01 6.29±0.00 3.90±0.01

155

19 6.72±0.00 6.71±0.00 6.32±0.01 3.95±0.00

20 6.73±0.01 6.63±0.01 6.34±0.01 4.15±0.00

21 6.75±0.02 6.72±0.01 6.62±0.01 4.14±0.00

22 6.79±0.00 6.60±0.01 6.39±0.00 4.12±0.00

23 6.71±0.00 6.70±0.00 6.67±0.01 4.11±0.00

24 6.71±0.01 6.70±0.00 6.32±0.01 4.22±0.00

25 6.72±0.01 6.63±0.02 6.32±0.00 4.18±0.00

26 6.71±0.00 6.69±0.00 6.53±0.02 4.28±0.00

27 6.72±0.00 6.69±0.00 6.52±0.00 3.84±0.00

28 6.74±0.01 6.71±0.01 6.65±0.01 3.98±0.00

29 6.79±0.02 6.72±0.00 6.62±0.01 3.81±0.00

30 6.85±0.01 6.72±0.01 6.64±0.01 4.10±0.01

31 6.80±0.01 6.74±0.01 6.30±0.01 4.13±0.01

32 6.78±0.00 6.47±0.00 6.29±0.00 4.10±0.00

33 6.81±0.00 6.74±0.00 6.30±0.00 3.82±0.00

34 6.75±0.01 6.60±0.01 6.27±0.00 4.09±0.00

35 6.82±0.01 6.76±0.02 6.64±0.00 4.05±0.00

36 6.71±0.00 6.63±0.00 6.31±0.01 4.46±0.01

37 6.71±0.01 6.62±0.01 6.59±0.00 4.25±0.00

38 6.72±0.00 6.54±0.01 6.30±0.00 4.21±0.01

APPENDIX G (II)

ANOVA for Changes in pH with State

Source SS DF MS P-Value

Between 377.382 3 125.794 0.000

Within 4.61519 300 0.015384

TOTAL (CORRECTED) 381.997 303

APPENDIX G (III)

Multiple Range Tests for pH by state. Method: 95.0 percent LSD

State Count LS Mean Homogeneous Groups

4 76 4.05053 X

3 76 6.43763 X

2 76 6.65763 X

1 76 6.73789 X

Contrast Difference +/- Limits

1 - 2 *0.0802632 0.0566092

1 - 3 *0.300263 0.0566092

1 - 4 *2.68737 0.0566092

2 - 3 *0.22 0.0566092

2 - 4 *2.60711 0.0566092

3 - 4 *2.38711 0.0566092

* Denotes a statistically significant difference.

156

APPENDIX H (I)

L. monocytogenes mean counts at various states of the milk value chain

Mean Counts in milk/ milk samples (x10CFU/ mL)

Serial No. Production Retail Boil Fermented

1 0 8.9±1.9 0 12.2±1.9

2 0 5.6±2.0 5.6±2.0 33.3±0.0

3 15.3±3.9 55.6±19.3 0 38.9±16.8

4 0 7.8±2.0 0 2.2±1.9

5 0 7.8±1.9 0 2.2±1.9

6 12.2±5.1 34.5±3.9 6.7±0.00 13.3±2.2

7 0 0 0 3.3±3.4

8 5.6±5.10 12.2±1.9 0 0

9 44.4±19.3 173.3±33.4 0 17.8±0.9

10 146.7±17.3 158.9±17.7 66.7±18.4 16.7±3.4

11 0 7.8±6.9 0 0

12 0 6.7±0.0 0 11.1±2.9

13 12.2±1.9 18.9±17.7 0 37.8±7.0

14 0 0 0 0

15 20.0±0.0 23.3±17.7 10±0.0 33.3±0.0

16 0 8.9±3.5 0 13.3±2.2

17 8.9±1.9 14.5±3.9 0 35.6±5.1

18 0 8.9±1.9 0 0

19 0 8.9±3.3 0 16.7±5.8

20 0 11.1±1.91 0 0

21 0 34.433±10.19 0 0

22 40.0±43.73 76.867±69.9 0 0

23 30.0±30.00 90±20.246 0 3.3±0.00

24 66.7±33.35 106.7±24.00 0 153.3±19.3

25 8.9±1.91 14.433±1.96 6.7±3.35 7.8±1.91

26 0 0 0 0

27 13.3±0.0 33.3±0.0 0 7.8±1.91

28 32.2±3.9 55.6±19.3 0 0

29 0 4.43±1.96 0 16.7±0.0

30 4.43±1.96 8.9±1.90 0 3.3±0.0

31 0 4.43±1.96 5.6±1.96 8.9±5.09

32 28.867±7.7 35.534±10.7 0 0

33 3.3±0.00 8.9±5.09 3.3±0.00 4.43±1.96

34 0 0 0 0

35 0 8.9±3.5 0 13.3±2.2

36 0 14.5±3.9 0 35.6±5.1

37 0 8.9±1.9 0 0

38 0 8.9±3.3 0 16.7±5.8

157

APPENDIX H (II)

ANOVA for Mean Counts by State

Source SS DF MS P-Value

Between 25842.3 3 8614.1 0.000

Within 240783.0 300 802.6

TOTAL (CORRECTED) 266625.0 303

APPENDIX H (III)

Multiple Range Tests for Mean Counts by state. Method: 95.0 percent LSD

State Count LS Mean Homogeneous Groups

3 76 2.75263 X

1 76 12.9736 X

4 76 14.7061 X

2 76 28.6402 X

Contrast Difference +/- Limits

1 - 2 *-15.6666 0.0566092

1 - 3 *10.221 0.0566092

1 - 4 -1.73245 0.0566092

2 - 3 *25.8876 0.0566092

2 - 4 *13.9341 0.0566092

3 - 4 *-11.9534 0.0566092

* Denotes a statistically significant difference.

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