Foodborne Outbreak Investigation, Hanoi, Vietnam 01 – 05 June 2009 Study Design and Measures of...

Foodborne Outbreak Investigation, Hanoi, Vietnam 01 – 05 June 2009

Study Design and Measures of Association

Dr Danilo Lo Fo Wong

Study Design and Measures of Association

Dr Danilo Lo Fo Wong


Outline Outline

Study objectives

Types of study design

Measures of association


Study objectivesStudy objectives

Investigate an outbreak

Measure disease frequency

Assess risk factors

Investigate trends

Hypothesis generating

Hypothesis testing


Main types of studiesMain types of studies

Experimental Experimental studiesstudies

Observational studiesObservational studies

Cross-sectional studiesCross-sectional studies

Longitudinal studiesLongitudinal studies

Case-control studiesCase-control studiesCohort studiesCohort studies

Clinical trialsClinical trials



Evaluate the association between exposure (E) and disease outcome (D)

No random allocation of exposure or intervention

Harmonise groups as much as possible except for the exposures under investigation



TimeTime

D+D+

D-D-

DiseasedDiseased

Non-diseasedNon-diseased

E+E+

E-E-

ExposedExposed

Non-exposedNon-exposed

Study onsetStudy onset


Cohort study (prospective)Cohort study (prospective)

E+E+

E-E-

D+D+

D-D-

D+D+

D-D-

TimeTime


Cohort study (retrospective)Cohort study (retrospective)

E+E+

E-E-

D+D+

D-D-

D+D+

D-D-

TimeTime


Cohort studyCohort study

Applications:

(Foodborne) disease outbreak

Usually high attack rates

Identifiable & manageable setting– Single event (wedding, picnic, etc.)– Single location (cafeteria, restaurant, etc.)

Assess (foodborne) disease incidence

Assess risk factors


Cohort studyCohort study

Advantages

Clear temporal relationship

Least susceptible to some forms of bias

Possibility to examine multiple diseases

Disadvantages

No control over exposure

Not suitable for rare or long-latent diseases

Loss to follow-up threatens validity

More expensive than other observational designs


Case-control studyCase-control study

D+D+

D-D-

E+E+

E-E-

E+E+

E-E-

TimeTime



Applications:

(Foodborne) disease outbreak

Unclear setting of exposure– Spread out over time and space– Large cohort and/or rare disease

Increase in reported cases

Assess risk factors for sporadic illness



Advantages

Efficient use of time and resources

Well-suited for rare diseases

Examine multiple exposures

Relatively inexpensive

Best when cohort study is not feasible

Disadvantages

Not suited for rare exposures

Difficult to identify appropriate controls

Ascertaining historic exposure often difficult

Sensitive to some forms of bias


Cross-sectional studyCross-sectional study

TimeTime

D+D+

D-D-

E+E+

E-E-



Applications:

Prevalence estimate

Screening

Risk factor studies

Hypothesis generating



Advantages

One stop, one time

Least expensive

Based on sample of general population

– not restricted to people seeking medical care

Disadvantages

Not suitable if disease is rare or of short duration

Not possible to determine temporal relationship


Steps to develop a studySteps to develop a study

Hypothesis generation

Develop study objectives

Decide which type of study works best

Study methods– Design survey tool/questionnaire– Identify subjects ((non)diseased or (non)exposed)– Determine sample size


Steps to develop a studySteps to develop a study

Data gathering– Actively acquired data– Registered data– Published data

Statistical analysis– Descriptive– Analytic

• Univariate• Multivariate


2 x 2 Table2 x 2 Table

a. No. of subjects that are exposed and have the diseasea. No. of subjects that are exposed and have the disease

b. No. of subjects that are exposed and do not have the diseaseb. No. of subjects that are exposed and do not have the disease

c. No. of subjects that are not exposed and have the diseasec. No. of subjects that are not exposed and have the disease

d. No. of subjects that are not exposed and do not have the diseased. No. of subjects that are not exposed and do not have the disease

aa bb

cc ddNoNo

YesYesExposureExposure

YesYes NoNo

DiseaseDisease

a+ba+b

c+dc+d

a+ca+c b+db+d nn


Measures of associationMeasures of association

Disease frequency (absolute)– Attack rate

Strength of association (relative)– Relative risk (RR)– Odds ratio (OR)

Significance of association– Chi-squared– P-values– Confidence intervals (CI)


Disease frequencyDisease frequency

Attack rate: – the proportion of subjects at risk that develop disease (i.e.

proportion of exposed subjects that become ill)



aa bb

cc dd

YesYes

NoNo

YesYes

NoNo

ExposureExposure

DiseaseDisease

Attack rateAttack rateexposedexposed: (diseased|exposed)/exposed = a/(a+b): (diseased|exposed)/exposed = a/(a+b)

a+ba+b

c+dc+d

a+ca+c b+db+d nn

Attack rateAttack rateunexposedunexposed: (diseased|unexposed)/unexposed = c/(c+d): (diseased|unexposed)/unexposed = c/(c+d)


ExampleExample

4040 400400

2020 420420

YesYes

NoNo

YesYes

NoNo

Eating Eating product Xproduct X

SalmonellosisSalmonellosis

440440

440440

6060 820820 880880

Attack rateAttack rateexposedexposed: 40/440 = 0.09 = 9%: 40/440 = 0.09 = 9%

Attack rateAttack rateunexposedunexposed: 20/440 = 0.05 = 5%: 20/440 = 0.05 = 5%


Strength of associationStrength of association

Relative Risk (RR)– Risk of disease for exposed vs. non-exposed– Cohort and cross-sectional studies

Odds ratio (OR)– Odds of exposure for diseased vs. non-diseased – Case-control, cross-sectional and cohort studies

OR ~ RR when:– Cases and controls representative for population– Disease not frequent



aa bb

cc dd

YesYes

NoNo

YesYes

NoNo

ExposureExposure

DiseaseDisease

a+ba+b

c+dc+d

a+ca+c b+db+d nn

OR = odds exposureOR = odds exposurediseaseddiseased/odds exposure/odds exposurenon-diseased non-diseased = (a:c)/(b:d) = ad/bc= (a:c)/(b:d) = ad/bc

RR = RiskRR = Riskexposedexposed/Risk/Riskunexposed unexposed = [a/a+b)]/[c/c+d)]= [a/a+b)]/[c/c+d)]


ExampleExample

4040 400400

2020 420420

YesYes

NoNo

YesYes

NoNo



440440

440440

6060 820820 880880

OR = (40*420)/(20*400) = 2.1OR = (40*420)/(20*400) = 2.1

RR = (40/440)/(20/440) = 2.0RR = (40/440)/(20/440) = 2.0


Significance of associationSignificance of association

Chi-squared– Test association between exposure and disease

P-value– probability that an association at least as strong as that observed

might have arisen by chance alone– P < 0.05: significant

Confidence interval (CI)– range within which in 95% of times the true value of the

estimated association lies (i.e. 95% CI)– Indication of confidence in the point-estimate



aa bb

cc dd

YesYes

NoNo

YesYes

NoNo

ExposureExposure

DiseaseDisease

a+ba+b

c+dc+d

a+ca+c b+db+d nn

Chi-squared:Chi-squared:(a+b)(c+d)(a+c)(b+d)(a+b)(c+d)(a+c)(b+d)

n(|ad-bc| - n/2)n(|ad-bc| - n/2)22

P-value = P-value = Percentiles of Chi-square distributionPercentiles of Chi-square distribution


ExampleExample

4040 400400

2020 420420

YesYes

NoNo

YesYes

NoNo



440440

440440

6060 820820 880880

Chi-squared: 7.15Chi-squared: 7.15

P-value < 0.05P-value < 0.05


Confidence IntervalConfidence Interval

Lower border = ln(OR) – Z*(var ln(OR))Lower border = ln(OR) – Z*(var ln(OR))½½ = L = L

95% Confidence Interval for OR: e95% Confidence Interval for OR: eLL to e to eUU = X to Y = X to Y

Upper border = ln(OR) + Z*(var ln(OR))Upper border = ln(OR) + Z*(var ln(OR))½½ = U = U

aa bb

cc dd

YesYes

NoNo

YesYes

NoNo

ExposureExposure

DiseaseDisease

a+ba+b

c+dc+d

a+ca+c b+db+d nn


ExampleExample

4040 400400

2020 420420

YesYes

NoNo

YesYes

NoNo



440440

440440

6060 820820 880880

Lower border = 0.74 – 1.96*(0.08)Lower border = 0.74 – 1.96*(0.08)½½ = 0.2 = 0.2

95% Confidence Interval for OR: e95% Confidence Interval for OR: e0.20.2 to e to e1.31.3 = 1.2 to 3.7 = 1.2 to 3.7

Upper border = 0.74 + 1.96*(0.08)Upper border = 0.74 + 1.96*(0.08)½½ = 1.3 = 1.3


Interpretation RR and CIInterpretation RR and CI

RR > 1 : risk of disease among exposed greater than among unexposed

RR = 1 : risk of disease the same among exposed and unexposed

RR < 1 : risk of disease among exposed less than among unexposed (i.e. protective)

CIlower< 1 < CIupper : no significant association


Interpretation OR and CIInterpretation OR and CI

OR > 1 : odds of exposure among diseased greater than among non-diseased

OR = 1 : odds of exposure the same among diseased and non-diseased

OR < 1 : odds of exposure among diseased less than among non-diseased (i.e. protective)

CIlower< 1 < CIupper : no significant association


ExamplesExamples

OR = 2.3; 95% CI 1.2 – 28.5OR = 2.3; 95% CI 1.2 – 28.5

RR = 3.6; 95% CI 0.8 – 4.7RR = 3.6; 95% CI 0.8 – 4.7

OR = 0.4; 95% CI 0.2 – 0.7OR = 0.4; 95% CI 0.2 – 0.7

RR = 5.6; 95% CI 5.3 – 5.9RR = 5.6; 95% CI 5.3 – 5.9


Epi InfoEpi Info


Hypothesis testingHypothesis testing

Which study to design?

Nipah virus infection among abattoir workers across Malaysia

Cholera outbreak in Manila, Philippines

Foodborne salmonellosis in the Institute of Health Sciences hostel, Muscat, Oman


Nipah virus infection:Cross-sectional study Nipah virus infection:Cross-sectional study

Objective: To assess the prevalence of Nipah infection among abattoir workers and the association with pigs

Serum sampling of workers from registered abattoirs in 11 of 13 states in Malaysia

Exposure: pigs

Outcome: antibodies (ab’s) against Nipah virus

Abattoirs (n=143)

Workers (n=435)– 7 out of 435 infected (1.6%) slaughtering pigs– 0 out of 233 infected (0%) slaughtered ruminants


Nipah virus infection:Cross-sectional study Nipah virus infection:Cross-sectional study

7 workers carrying ab’s against Nipah virus from abattoirs in 3 states with clinical outbreak among pig farmers

Workers in these 3 states more likely to have Nipah antibody than those in other states

– 7/144 (4.9%) vs. 0/291 (0%), P < 0.001

Conclusion: – Nipah infection not widespread among abattoir workers in

Malaysia– Infection linked to exposure to pigs


Vibrio cholerae: Case-control study


Objective: to investigate an increasing number of diarrhea cases from a district in Manila

List of diarrhea cases from 3 hospitals in 1 district

338 suspect cholera cases admitted

Rectal swabs, environmental survey, water samples

Spot map to identify extent of outbreak

Case control study in 4 areas with highest AR’s– 56 cases– 56 controls– Matched for age and gender




2 protective factors– Boiling water prior to drinking

(OR = 0.08, 95% CI 0.02 – 0.4)– Washing drinking water containers with soap and water

(OR = 0.12, 95% CI 0.02 – 0.63)

Inspection showed leaking water pipes, numerous illegal connections and unsanitary toilet facilities

– 1 sample from household faucets positive for fecal coliforms

Conclusion: Cholera outbreak due to contaminated water


Salmonellosis Outbreak: Cohort study


Questionnaire to all students at IOHS– 123 cases identified among 158 who ate dinner (AR = 78%); 72

confirmed cases (S. Enteritidis)– 0 cases out of 91 who did not eat this meal (AR = 0%) – RR infinity, p < 0.001

Univariate analysis– Chicken (RR = 4.4; 95% CI 1.7 – 11)– Egg mousse (RR = 6.0; 95% CI 2.5 – 15)– Fried dal (RR = 1.2; 95% CI 1.0 – 1.4)– Omelet (RR = 1.3; 95% CI 1.2 – 1.4)– Chapati (RR = 6.0; 95% CI 1.7 – 11)




Restricted analysis (n=158)– Chicken (RR = 14; 95% CI 2.0 – 96)– Egg mousse (RR = 19; 95% CI 2.8 – 128)– Chapati (RR = 19; 95% CI 2.8 – 128)

Interview of kitchen staff– Time- and temperature abuse of chicken– Cross-contamination of chapati dough with raw eggs– Mousse contained raw eggs and was not cooked

Conclusion: Outbreak due to cross-contamination and time-temperature abuse during preparation of three foods in the IOHS kitchen


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Foodborne Outbreak Investigation, Hanoi, Vietnam 01 – 05 June 2009 Study Design and Measures of...

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