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Accepted Manuscript
Relationship between biosecurity and production/antimicrobial treatment char-
acteristics in pig herds
M. Laanen, D. Persoons, S. Ribbens, E. de Jong, B. Callens, M. Strubbe, D.
Maes, J. Dewulf
PII: S1090-0233(13)00404-8
DOI: http://dx.doi.org/10.1016/j.tvjl.2013.08.029
Reference: YTVJL 3848
To appear in: The Veterinary Journal
Accepted Date: 24 August 2013
Please cite this article as: Laanen, M., Persoons, D., Ribbens, S., de Jong, E., Callens, B., Strubbe, M., Maes, D.,
Dewulf, J., Relationship between biosecurity and production/antimicrobial treatment characteristics in pig herds,
The Veterinary Journal (2013), doi: http://dx.doi.org/10.1016/j.tvjl.2013.08.029
This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers
we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and
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Relationship between biosecurity and production/antimicrobial treatment characteristics in pig herds M. Laanen a, *, D. Persoons a, b, S. Ribbens c, E. de Jong c, B. Callens a, M. Strubbe c, D. Maes a, J. Dewulf a a Unit of Veterinary Epidemiology, Department of Reproduction, Obstetrics and Herd Health, Faculty of Veterinary Medicine, Ghent University, 9820 Merelbeke, Belgium b Pharma.be, Belgian Association for the Pharmaceutical Industry, 1170 Brussels, Belgium c Animal Health Care Flanders, 9000 Drongen, Belgium * Corresponding author: Tel.: +32 9 264 75 48. E-mail address: [email protected]
Abstract
The biosecurity status of 95 breeder-finisher pig herds was quantified using a risk-
based weighted scoring system. Data relating to herd-, farmer- and production- characteristics
and to the prophylactic use of antimicrobials were also collected. The average external
biosecurity score (measures to prevent pathogens from entering a herd) was 65 (range, 45 -89)
and the average internal score (measures to reduce the within-herd spread of pathogens) was
52 (range, 18 - 87).
External scores were positively associated with herd size, while internal scores were
negatively associated with both ‘age of buildings’ and ‘years of experience of the farmer’,
indicating that biosecurity is generally better implemented in larger herds, in more modern
facilities and by younger farmers. External and internal biosecurity scores were positively
associated with daily weight gain and negatively associated with feed conversion ratio of
fattening pigs. Internal scores were negatively associated with disease treatment incidence,
suggesting that improved biosecurity might help in reducing the amount of antimicrobials
used prophylactically. This study demonstrates and quantifies a clear link between biosecurity
and both production- and antimicrobial treatment-related criteria in pig herds.
Keywords: Pig; Biosecurity; Scoring; Daily weight gain; Feed conversion; Antimicrobial
treatment
Introduction
Biosecurity embraces all aspects of the prevention of pathogens entering and spreading
within a group of animals (Amass and Clark, 1999), and can thus be divided into two parts.
External biosecurity relates to the prevention of pathogens entering a herd, and internal
biosecurity is how the spread of pathogens within a herd is reduced. It is assumed that higher
levels of biosecurity lead to improved animal health and productivity, and to a reduction of
the use of antimicrobials (Ribbens et al., 2008), which are important features of sustainable
animal production.
There are documented relationships between the management and incidence of
specific diseases in pig herds (Maes et al., 2008; Fraile et al., 2010; Lambert et al., 2011;
Meyns et al., 2011), and research has resulted in many recommendations with regard to
biosecurity measures to reduce disease (Amass and Clark, 1999; Boklund et al., 2003, 2004;
Ribbens et al., 2008). Given the inherent challenges in measuring an entity such as
biosecurity, previous workers have not attempted to quantify its effect although a risk-based
weighted biosecurity scoring system has now become available (Laanen et al., 2010)1.
Although limited and responsible use of antimicrobials is desirable, recent studies
indicate that over the last 9 years there has been increased prophylactic use of these drugs in
pigs in Belgium, where ‘group level’ use of antimicrobials is the most common way to
administer antimicrobials (Callens et al., 2012). The majority of these treatments are
prophylactic, administered to groups of pigs by farmers at crucial time-points in production
such as at castration and weaning, following veterinary advice (Dunlop et al., 1998).
1 See: http://www.biocheck.ugent.be
The data suggest that guidelines for prudent use of antimicrobials are not currently
being sufficiently implemented in Belgium. However, no official action plan to reduce
antimicrobial use is currently implemented in Belgium as in other European countries
(Nielsen et al., 2007; Cogliani et al., 2011). Studies exploring ways to reduce the amount of
antimicrobials used are therefore warranted. The objectives of this study were to investigate
the relationship between the implementation of biosecurity in pig herds in Belgium, and
various production parameters and the prophylactic use of antimicrobials.
Materials and methods
Herd selection
Herds were selected from the National Identification and Registration Database of
Belgium (Sanitel-Pigs, 2005). The selection criteria were that herds were ‘farrow-to-finish’ in
type, and contained at least 80 sows and 400 fattening pigs. From a total of 2658 herds fitting
these criteria, a random sample of 250 herds, stratified by province, was selected. Random
selection was performed using a computer-generated list (Cameron, 1999), and all selected
herds were invited to participate by telephone. Farmers who declined to take part were asked
to explain their reasons for not participating.
Data collection
All participating herds were visited on one occasion by the same investigator between
September 2009 and January 2011. During this visit, the biosecurity practices on the farm
were observed, and the farmer was interviewed in relation to herd-, farmer- and production-
characteristics, the application of biosecurity, and the prophylactic use of antimicrobials using
a standardised questionnaire. The interviewer ensured no comments were made that might
influence the farmer’s responses and, after the visit, the farmers received a full evaluation and
list of recommendations concerning their biosecurity.
Collection of herd, farmer and production data
The following data were collected: number of sows/fattening pigs, the age of the farm
buildings (taken as the age of the oldest building in which the pigs were housed), and the
years of experience of the farmer (i.e. the number of years a farmer had kept his/her own
herd). Production characteristics collected were: daily weight gain (DWG) and feed
conversion ratio (FCR) of fattening pigs, mortality of fattening pigs, and seroprevalence of
salmonella infection. The FCR is a measure of an animal’s efficiency in converting feed into
body mass and reflects the mass of feed needed to produce 1 kg of bodyweight. A low FCR is
therefore desirable from a financial perspective.
The DWG, FCR and mortality rate (all at herd level) during the year preceding the
visit, were verified by consulting farm production records, and the seroprevalence of
salmonella infection was quantified by the mean sample:positive ratio (S/P)-value obtained
from the official national control programme records2. The mean S/P-values were determined
by indirect ELISA (Herdcheck Swine Salmonella Antibody Test Kit, Idexx laboratories) on
12 blood samples taken from fattening pigs every 4 months. None of the visited herds were
considered salmonella ‘problem herds’ (defined as herds having ≥3 consecutive samplings
with an average S/P-value of >0.6).
Quantification of biosecurity status of herds
2 See: http://www.dgz.be (accessed 22 April 2011).
Quantification was achieved using a previously defined risk-base scoring system of
both external and internal aspects of biosecurity, each of which was divided into six sub-
categories (Table 1)3. Each sub-category contained between 2 and 13 questions resulting in a
total of 109 questions (see Appendix A, Supplementary material). A ‘weight’ was attributed
to each question and sub-category on the basis of published data relating to pathogen
transmission, knowledge of infectious risks, and expert opinion on the risk of infection
through different transmission routes. As direct contact between diseased and susceptible
animals is generally acknowledged to be the most important route of transmission of
infectious diseases, biosecurity measures aimed at preventing such contact between animals
was considered more important than that preventing indirect contact. In addition to the
transmission route per se, the frequency with which a given infection had the opportunity to
transmit via this route also dictates the risk of transmission and was thus factored into our
scoring system.
Based on these principles it was possible to quantify the risks of transmission in
general terms and to determine the importance of the various measures taken to reduce these
risks. The weights given to the sub-categories are detailed in Table 1, and more details,
including the calculations behind the biosecurity scores can be found in Appendix A. For each
of the listed questions, points were obtained when the biosecurity measure was applied
correctly. On occasion, points were earned by not performing a certain action (e.g. not buying
breeding pigs), whereas, where a farmer purchased breeding animals, he/she started with zero
points. The farmer gained points by applying preventive measures such as purchasing from
3 See: http://www.biocheck.ugent.be
only one supplier, or buying from a supplier of known health status (see Appendix A). The
sum of the points relating to each sub-category was ‘weighted’ accordingly.
To calculate the external or internal biosecurity score, the scores for each of the
appropriate sub-categories were totalled to give a score between ‘0’ (total absence of
biosecurity) and ‘100’ (perfect biosecurity). The overall score was calculated as the mean of
the external and internal biosecurity score (Laanen et al., 2010). The scores for the different
sub-categories were then re-calculated to scores between 0 and 100 to facilitate their
interpretation by the farmers. The questionnaire and scoring system are available as a
download4.
Quantification of antimicrobial drug use
As our study design was observational and retrospective, only standard prophylactic
antimicrobial ‘group treatments’, administered from birth until slaughter, were assessed.
Prophylactic group treatments are defined as treatments of all the animals within a group to
prevent clinical disease (Aarestrup, 2005). Because such treatments are standardised and
administered by the farmer, they are less subject to ‘recall bias’. For each group treatment, the
following data were collected: product name, indication for use, duration of therapy (days),
dosage, administration route (in-feed, in-water, or IM), and age of treated animals (days).
Prescriptions and order forms, where available, were used to verify the data.
Quantification was achieved by calculating treatment incidences (TI) defined as the
number of pigs/1000 treated daily with one dose of an antimicrobial drug (Timmerman et al.,
2006). The daily dose was quantified by means of the ‘used daily dose pig’ (UDD pig) which
4 See: http://wwww.biocheck.ugent.be
gives the dose of a drug administered/day/kg. The UDD was calculated by dividing the
amount of antimicrobial administered (mg) by the number of pigs treated, multiplied by the
estimated average weight of the pigs when treated (Timmerman et al., 2006).
Treatment incidences were calculated according to Timmerman et al. (2006). The total
amount of antimicrobial drug used was first calculated/compound. The number of days at risk
(i.e. the time in days that a pig was potentially exposed to ≥ one treatment) was set at 206
days: 70 days for the farrowing and nursery period and 136 days for fattening based on
average for all herds. The ‘kg pig’ was calculated as the number of pigs multiplied by their
average weight (standardised over the different herds) when treated. Using this method, TIs
based on the UDDpig were obtained (TIUDDpig).
Statistical analysis
Difference in herd size between participating and non-participating herds was tested
by means of an independent samples t test. The association between herd/farmer-
characteristics and biosecurity scores were tested using univariable linear regression models.
To evaluate the association between the biosecurity score and the different
production/treatment characteristics, univariable and multivariable linear regression models
were fitted to the data. Firstly, overall biosecurity score was tested univariably vs. the
different ‘outcome’ variables (DWG, FCR, mortality, Salmonella S/P-value and TIUDDpig). If
this association was significant, both parts of the score (external and internal) were also tested
univariably against all outcome variables. Next, to identify the most influential aspects of
biosecurity, all sub-categories of this criterion as scored by the Biocheck scoring system were
tested univariably, and those with P<0.2 in the univariable model were added to the
multivariable model. These variables were assessed for two-way correlations using Pearson’s
correlation coefficients. If the coefficient was >0.6, only the best-fitting variable was added to
the multivariable model. A manual, stepwise backward selection method was used with
P>0.05 as a selection criterion. Finally, all two-way interactions between significant variables
were tested. All analyses were performed using SPSS software (version 19.0).
Results
Study participation rate and descriptive results
Of the 250 herds contacted, 47 were ‘inactive’ and of the remaining 203, 95 were
willing to participate giving a participation rate of 47.8%. Reasons for not participating
included: ‘lack of time’ (44/108), ‘not interested’ (43/108), and other reasons such as
‘personal problems’ or ‘ceasing pig production in near future’ (21/108). The average number
of sows and fattening pigs in non-participant herds (181 and 1046 on average, respectively)
were significantly lower than in those participating in the survey (289 and 1420 on average,
respectively) (P<0.01). The average external and internal biosecurity scores were 65 (range
45 - 89), and 52 (range 18 - 87), respectively. The scores for the different categories of the
Biocheck scoring system are listed in Table 1. Results of herd and farmer information,
production-characteristics of fattening pigs, and the prophylactic use of antimicrobial drugs
are detailed in Table 2.
Data analysis
Farmer and herd characteristics
Numbers of sows and fattening pigs were both positively associated with the external
(P<0.01), but not the internal (P=0.07 and P=0.24, respectively) biosecurity score. Both ‘age
of buildings’ and ‘years of experience’ were negatively associated with internal (P=0.03 and
P=0.04, respectively) but not external biosecurity (P=0.22 and P=0.51, respectively).
Daily weight gain, feed conversion ratio, mortality rate and S/P value
The overall biosecurity score, as well as both external and internal scores were
significantly associated with the DWG of fattening pigs (all P<0.01) in the univariable models
(Table 3). When evaluating associations between sub-categories of biosecurity and DWG,
‘transport of animals, removal of manure and dead animals’ (i.e. transport of animals to
slaughterhouse or other herds, removal of manure, and handling of carcasses) and ‘cleaning
and disinfection’ (i.e. methods used to clean and disinfect animal housing) were positively
associated with DWG in the multivariable model (P=0.03 and P=0.04, respectively; R²=0.14)
(Table 3).
The FCR of fattening pigs was significantly associated with overall, external and
internal biosecurity scores (all P<0.01) (Table 4). When sub-categories of biosecurity were
evaluated together in the multivariable model, the combination of two sub-categories of
external biosecurity, ‘purchase of animals and semen’ (P<0.05) (i.e. purchase and transport of
animals, use of quarantine, and purchase of semen) and ‘vermin/bird control’ (P<0.01), and
one sub-category of the internal biosecurity, ‘farrowing and suckling period’ (P<0.03) (i.e.
washing of sows, cross-fostering and handling of piglets) had the strongest association with
FCR (R²=0.24), indicating that high scores in each of these sub-categories were related to
good (i.e. low) animal FCRs.
No significant associations were found between the mortality rate of fattening pigs and
any of the biosecurity scores and neither the overall, external, or internal scores were
significantly associated with the salmonella S/P-value.
Use of antimicrobial drugs
The mean TIUDDpig was 174.22 (Table 2), indicating that, on average, approximately
17% of the animals in the herd were treated daily with one dose of antimicrobials by means of
prophylactic group treatment. The overall and internal biosecurity scores were negatively
associated (P=0.05 for both, respectively) with TIUDDpig. Using the multivariable model,
‘disease management’ (i.e. disease control, use of hospital pens, handling of diseased animals)
and ‘farrowing/suckling period’ (i.e. washing of sows, cross-fostering, handling of piglets),
were found to be most strongly negatively associated with the TIUDDpig (P=0.04 and P=0.03,
respectively; R²=0.11) (Table 5).
Discussion
This study has attempted to identify and quantify associations between herd
biosecurity and aspects of pig production/treatment. As in every observational study of this
type, the results may be subject to some bias; for example, an analysis of non-participating
farmers indicated that those owning larger herds were more likely to take part. Furthermore,
as the study was cross-sectional in type, it was not possible to allocate causal relationships to
the associations found, and there may have been other confounding factors impacting on our
data.
Although significant associations were identified, the R²-values in the various
regression models were small, suggesting unexplained variation remains. Other factors
relating to herd management, as well as vaccination protocols, animal genetics and nutrition
are likely also to affect DWG, FCR and the frequency of the use of antimicrobial drugs and
therefore contribute to unexplained variation. Moreover, as many biosecurity measures are
considered ‘proxies’ of good management, the observed associations might be partially or
largely influenced by other management factors. In consequence, our data only suggest
possible causal associations that require further assessment by prospective intervention
studies.
The biosecurity in herds in the current study was measured at one point in time and the
information derived was used to identify associations between parameters measured over the
preceding year. In some herds, biosecurity measures may have changed shortly before the
visit, e.g. due to an outbreak of disease, so that the resulting biosecurity score was higher at
the point of data collection than it had been over the preceding year. However, in the authors’
experience, farmers in Belgium are not particularly inclined to change their biosecurity
practices frequently, and the number of herds included in our study minimises the potential
influence of any such changes. Although the weighting attributed to the sub-categories and
questions were based on previous studies and expert opinion, they do remain a somewhat
subjective interpretation of the importance of the various aspects of biosecurity. Our scoring
system can be seen as an attempt to capture and quantify all aspects of biosecurity, facilitating
consistency in the evaluation of herds over time.
Scores of external biosecurity (typically measures implemented by herd owners on
farm visitors/suppliers), were, on average, higher than the scores for internal biosecurity
(measures relating to the husbandry/management strategies of the farmers themselves). The
positive association between herd size and level of biosecurity suggests more attention is paid
to biosecurity on larger farms, a finding previously reported for both pig and cattle herds
(Boklund et al., 2003, 2004; Nöremark et al., 2010). It was also noticeable that internal
biosecurity increased with decreasing age of the buildings, suggesting more attention should
be paid to biosecurity, and that this is more readily implemented within a more modern
infrastructure. The same held true for ‘years of experience’ of farmers, suggesting younger
farmers are more focused on implementing internal biosecurity measures.
The association found between both external and internal biosecurity status and animal
DWG/FCR indicates that, on average, herds with a better biosecurity have more efficient
production. More specifically, ‘transport of animals, removal of manure/dead animals’ and
‘cleaning and disinfection’, measures likely to reduce the risk of pathogens entering or
spreading within a herd, were most strongly associated with DWG, as has been previously
reported (Mannion et al., 2007). Sub-categories of biosecurity most strongly associated with
FCR were ‘purchase of animals and semen’, ‘vermin/bird control’ and ‘farrowing and
suckling period’. The variation in these sub-category scores explains, at least in part, the
variation in FCR between herds (R²=0.24). It would seem logical that herds taking precautions
to prevent diseases being introduced would have more healthy animals with attendant better
FCR. The association between ‘farrowing and suckling period’ and FCR suggests improving a
piglet’s health in its early life will improve its FCR during fattening. Nevertheless, as stated
above, it must be borne in mind that herds with better biosecurity may be better managed
overall, and consequently have better production values.
In contrast to the results of a previous study (Maes et al., 2004), no relationship was
found between biosecurity and the mortality rate of fattening pigs. This might reflect
differences in the methods of measuring biosecurity between these studies, or that biosecurity
is only one factor associated with mortality. There was also no relationship found between
biosecurity and the average salmonella S/P-values. Baptista et al. (2010) and Twomey et al.
(2010) demonstrated a negative association between ‘level of biosecurity’ and prevalence of
salmonella infection. These differing results may be due to variations in the way ‘salmonella
infection’ was assessed in these studies, and the fact that the present study did not include
herds with a high prevalence of salmonella infection.
The negative association between biosecurity score and TIUDDpig indicates that fewer
prophylactic group treatments with antimicrobials are given in herds with higher biosecurity.
Only internal biosecurity was significantly associated with TIUDDpig, and the categories
‘disease management’ and ‘farrowing and suckling period’ were strongly associated with this
parameter. This may reflect the fact that the correct management of diseased animals results
in a lower risk of within-herd spread of infection, which in turn leads to reduced infection
pressure and a reduction in antimicrobial treatments. Given that the majority of strategic
group treatments in pigs are given during the suckling/weaner phase (Callens et al., 2012), the
greatest factor impacting on the frequency of antimicrobial usage is to be expected in the early
part of the production cycle.
The finding of a negative association between biosecurity and the prophylactic use of
antimicrobials could create opportunities in the light of ongoing consumer demand for
reduced antimicrobial usage in animal production systems. Including ‘therapeutic
antimicrobial use’ as a parameter in estimating total antimicrobial use on a herd might be
useful to further clarify the relationship between biosecurity and total antimicrobial
consumption, as this ‘therapeutic use’ category will reflect bacterial diseases occurring
despite the use of prophylactic medication. Given that pig farmers in Belgium are only
required to keep records of antimicrobial treatments for 2 months prior to the slaughter of
animals, it is very difficult to obtain reliable retrospective information on the therapeutic use
of antimicrobials throughout the production cycle. This aspect of our findings merits further
investigation in future prospective studies.
Conclusions
This study demonstrates and quantifies a clear link between biosecurity and both
production- and antimicrobial treatment-related criteria in pig herds, and indicates there are
currently substantial differences in how biosecurity is applied in pig herds in Belgium.
Aspects of both external and internal biosecurity were positively associated with daily weight
gain, and negatively associated with feed conversion ratio, respectively. Internal scores were
negatively associated with disease treatment incidence, suggesting that improved biosecurity
might reduce the prophylactic use of antimicrobials.
Appendix A. Supplementary material
Supplementary data associated with this article can be found, in the online version, at
doi:………………….Setters please insert doi number
Conflict of interest statement
None of the authors of this paper has a financial or personal relationship with other
people or organisations that could inappropriately influence or bias the content of the paper.
References Aarestrup, F.M., 2005. Veterinary drug usage and antimicrobial resistance in bacteria of animal origin. Basic and Clinical Pharmacology and Toxicology 96, 271-281. Amass, S.F., Clark, L.K., 1999. Biosecurity considerations for pork production units. Swine Health and Production 7, 217-228.
Baptista, F.M., Alban, L., Nielsen, L.R., Domingos, I., Pomba, C., Almeida, V., 2010. Use of herd information for predicting Salmonella status in pig herds. Zoonoses and Public Health 57, 49-59. Boklund, A., Mortensen, S., Houe, H., 2003. Biosecurity in 121 Danish sow herds. Acta Veterinaria Scandinavica Suppl. 100, 5-14. Boklund, A., Alban, L., Mortensen, S., Houe, H., 2004. Biosecurity in 116 Danish fattening swineherds: Descriptive results and factor analysis. Preventive Veterinary Medicine 66, 49-62. Callens, B., Persoons, D., Maes, D., Laanen, M., Postma, M., Boyen, F., Haesebrouck, F., Butaye, P., Catry, B., Dewulf, J., 2012. Prophylactic and metaphylactic antimicrobial use in Belgian fattening pig herds. Preventive Veterinary Journal 106, 53-62. Cameron, A., 1999. Survey toolbox: A practical manual and software package for active surveillance of livestock diseases in developing countries. Australian Centre for International Agricultural Research, monograph No. 54, Canberra, Australia. Cogliani, C., Goossens, H., Greko, C., 2011. Restricting antimicrobial use in food animals: Lessons from Europe. Banning non-essential antibiotic usees in food animals is intended to reduce pools of resistence genes. Microbe 6 (6), http://www.tufts.edu/med/apua/research/pew_11_846139138.pdf. Dunlop, R.H., McEwan, S.A., Meek, A.H., Friendship R.A., Clarke, R.C., Black, W.D., 1998. Antimicrobial drug use and related management practices among Ontario swine producers. The Canadian Veterinary Journal 39, 87-96. Fraile, L., Alegre, A., López-Jiménez, R., Nofrarías, M., Segalés, J., 2010. Risk factors associated with pleuritis and cranio-ventral pulmonary consolidation in slaughter-ages pigs. The Veterinary Journal 184, 326-333. Laanen, M., Beek, J., Ribbens, S., Vangroenweghe, F., Maes, D., Dewulf, J., 2010. Biosecurity on pig herds: Development of an on-line scoring system and the results of the first 99 participating herds (in Dutch). Flemish Veterinary Journal 79, 302-306. Lambert, M.E., Arsenault, J., Poljak, Z., D’Allaire, S., 2011. Epidemiological investigations in regard to porcine reproductive and respiratory syndrome (PRRS) in Quebec, Canada. Part 2: Prevalance and risk factors in breeding sites. Preventive Veterinary Medicine, 104, 84-93. Maes, D., Duchateau, L., Larriestra, A., Deen, J., Morrison, R.B., de Kruif, A., 2004. Risk factors for mortality in grow-finishing pigs in Belgium. Journal of Veterinary Medicine series B – Infectious Diseases and Veterinary Public 51, 321-326. Maes, D., Segales, J., Meyns, T., Sibila, M., Pieters, M., Haesebrouck, F., 2008. Control of Mycoplasma hyopneumoniae infections in pigs. Veterinary Microbiology 126, 297-309. Mannion, C., Leonard, F.C., Lynch, P.B., Egan, J., 2007. Efficacy of cleaning and disinfection on pig farms in Ireland. Veterinary Record 161, 371-375.
Meyns, T., Van Steelant, J., Rolly, E., Dewulf, J., Haesebrouck, F., Maes, D., 2011. A cross-sectional study of risk factors associated with pulmonary lesions in pigs at slaughter. The Veterinary Journal 187, 388-392. Nielsen, A.C., Aarestrup, F., Mygind, J., 2007. Risk management of antimicrobial use and resistence from food-producing animals in Denmark. In: A Contribution to the Joint FAO/WHO/OIE Expert meeting on Critically Important Antimicrobials, Rome, Italy. 17-21 September 2007, http://www.foedevarestyrelsen.dk/english/SiteCollectionDocuments/25_PDF_word_filer%20til%20download/05kontor/Risk_management_antimicrobia_%20use_and%20resistance_Denmark_E.pdf. Nöremark, M., Frössling, J., Lewerin, S.S., 2010. Application of routines that contribute to on-farm biosecurity as reported by Swedish livestock farmers. Transboundary and Emerging Diseases 57, 225-236. Ribbens, S., Dewulf, J., Koenen, F., Mintiens, K., De Sadeleer, L., de Kruif, A., Maes, D., 2008. A survey on biosecurity and management practices in Belgian pig herds. Preventive Veterinary Medicine 83, 228-241. Sanitel-Pigs, 2005. Identification and registration data of registered Belgian pig herds. Federal Agency of the Safety of the Food Chain (FASFC), Belgium. Timmerman, T., Dewulf, J., Catry, B., Feyen, B., Opsomer, G., de Kruif, A., Maes, D., 2006. Quantification and evaluation of antimicrobial drug use in group treatments for fattening pigs in Belgium. Preventive Veterinary Medicine 74, 251-263. Twomey, D.F., Miller, A.J., Snow, L.C., Armstrong, J.D., Davies, R.H., Williamson, S.M., Featherstone, C.A., Reichel, R., Cook, A.J.C., 2010. Association between biosecurity and Salmonella spp. prevalence on English pig farms. Veterinary Record 166, 722-724.
Table 1.
Sub-categories used in the Biocheck scoring system for external and internal biosecurity and overall results for the 95 ‘closed’ or ‘semi-closed’ pig herds studied.
Sub-category Weight 1 Average SD * Min Median MaxExternal biosecurity 65 8 45 66 89 Purchase of animals/semen 24 89 11 58 92 100 Transport of animals, removal of 23 66 12 30 65 96 manure/dead animals Feed, water and equipment supply 15 41 17 17 40 100 Personnel and visitors 17 64 12 24 65 100 Vermin/bird control 11 57 21 0 50 100 Environment and region 10 48 22 10 50 100 Internal biosecurity 52 15 18 53 87 Disease management 10 60 31 20 60 100 Farrowing and suckling period 14 61 20 14 64 93 Nursery unit management 14 56 24 0 57 100 Fattening unit management 14 64 26 0 71 100 Measures between compartments 28 46 18 11 43 100
and use of equipment Cleaning and disinfection 20 38 27 0 35 95 Overall biosecurity score 59 10 36 59 88
1 A ‘weight’ was attributed to each sub-category on the basis of published data relating to pathogen transmission, knowledge of infectious risks, and expert opinion on the risk of infection through different transmission routes. * SD, standard deviation.
Table 2.
Descriptive results for ‘herd’, ‘farmer’, production characteristics, and use of antimicrobials for the 95 ‘closed’ or ‘semi-closed’ pig herds studied.
Factor N Average SD* Min Median Max Number of sows 95 289 161.66 80 220 1000 Number of fattening pigs 95 1420 877.16 400 1250 7000 Years of experience of farmer 95 21 9.90 1 20 42 Age of buildings (years) 95 32 17.01 2 30 129 Daily weight gain (g/day) † 94 681 71.10 486 676 870 Mortality (%) † 89 3.6 2.19 1.0 3.0 11.5 Feed conversion ratio † 73 2.76 0.18 2.28 2.75 3.30 Salmonella S/P value 92 0.28 0.21 0.03 0.21 0.92 TIUDDpig
* 95 174 130.47 0 150 650
* SD, standard deviation; TI, treatment incidence; † Daily weight gain, mortality and feed conversion ratio all relate to fattening pigs at a herd level during the year preceding the study.
Table 3.
Associations between different aspects of external and internal biosecurity and daily weight gain of fattening pigs in 94 ‘closed’ or ‘semi-closed’ pig herds.
R² β-coefficient P-value Univariable model Overall biosecurity 0.125 2.46 <0.01 External biosecurity 0.129 3.15 <0.01 Internal biosecurity 0.090 1.46 <0.01 Biosecurity sub-categories significant in univariable model
Transport of animals, removal of manure/dead Animals (external)
0.102 1.83 <0.01
Vermin/bird control (external) 0.091 1.00 <0.01 Fattening unit management (internal) 0.045 0.59 0.04 Cleaning and disinfection (internal) 0.099 0.84 <0.01 Biosecurity sub-categories significant in multivariable model
Transport of animals, removal of manure/ dead animals (external) 0.143
1.33 0.03
Cleaning and disinfection (internal) 0.60 0.04
Table 4.
Associations between different aspects of external and internal biosecurity and feed conversion ratio of fattening pigs in 73 ‘closed’ or ‘semi-closed’ pig herds.
R² β-coefficient P-value Univariable model Overall biosecurity 0.173 -0.007 <0.01 External biosecurity 0.200 -0.009 <0.01 Internal biosecurity 0.097 -0.004 <0.01 Biosecurity sub-categories significant in the univariable model
Transport of animals, removal of manure/dead animals (external)
0.137 -0.005 <0.01
Vermin/bird control (external) 0.123 -0.004 <0.01 Farrowing and suckling period (internal) 0.081 -0.002 0.03 Biosecurity sub-categories significant in the multivariable model
Purchase of animals/semen (external) 0.240
-0.003 0.05 Vermin/bird control (external) -0.003 <0.01 Farrowing and suckling period (internal) -0.002 0.03
Table 5.
Associations between different aspects of external and internal biosecurity and treatment incidence (TI)UDDpig based on prophylactic group treatments in 95 ‘closed’ or ‘semi-closed’ pig herds. TIUDDpig was expressed as treatment incidence/1000 pigs at risk/day and based on the daily doses used (UDDpig/1000 pigs at risk/day).
R² β-coefficient P-value Univariable model Overall biosecurity 0.037 -2.45 0.05 External biosecurity 0.015 -1.97 0.24 Internal biosecurity 0.040 -1.77 0.05 Biosecurity sub-categories significant in the univariable model
Disease management (internal) 0.061 -1.05 0.02 Farrowing and suckling period (internal) 0.064 -1.66 0.01 Nursery unit management (internal) 0.049 -1.22 0.03 Biosecurity sub-categories significant in the multivariable model
Disease management (internal) 0.108
-0.90 0.04 Farrowing and suckling period (internal) -1.43 0.03