module 4: epidemiology investigationadph.org/epi/assets/module_4.pdfmodule learning objectives...

Module 4:Module 4:Module 4:Module 4:Epidemiology InvestigationEpidemiology Investigation

Epidemiology DivisionAnalysis and Reporting Branch

Epidemiology DivisionBureau of Clinical Laboratories

Bureau of Environmental Services



Module Learning ObjectivesModule Learning ObjectivesDevelop a case definitionExplain an epidemic curveDevelop an initial hypothesisList three types of study design and a method of statistical analysisCalculate measures of associationInterpret significance of dataDetermine if hypotheses are confirmed or rejectedPerform group exercise


Bureau of Environmental Services2

Estimated Annual US Estimated Annual US Foodborne Disease BurdenFoodborne Disease Burden

Foodborne Illnesses47.8 million

Hospitalizations127 839127,839

Deaths3 0373,037



AL Foodborne Outbreak (FBO) TeamAL Foodborne Outbreak (FBO) TeamMontgomery

Surveillance Branch - EpidemiologySurveillance Branch EpidemiologyAnalysis and Reporting Branch - EpidemiologyBureau of Clinical Laboratories (BCL)Bureau of Environmental Services – Food, Milk and Lodging

Th h h SThroughout the StateEnvironmentalistsField S r eillance Staff (FSS)Field Surveillance Staff (FSS)Others (in special situations)



AL Foodborne Outbreak AL Foodborne Outbreak (FBO) Definition(FBO) Definition

An incident in which two or more persons from different households experience a similar illnessdifferent households experience a similar illness resulting from the ingestion of a common food.

Exceptions: botulism and chemical poisoningExceptions: botulism and chemical poisoning (1 case = outbreak)



How Are Outbreaks Named?How Are Outbreaks Named?The outbreak name identifies the state, the year, month, species/serotype, primary county, and sequence (orderof outbreaks in the same county in the same month).

The format is Alabama/year/month/species, serotype, or enzyme pattern/hyphen/county number/ and sequence. y p yp y q

PHA03 Deli :

PHA08 Church Luncheon :

2626



AL Foodborne OutbreaksAL Foodborne Outbreaks



County NumbersCounty NumbersAutauga 01 Conecuh 18 Houston 35 Morgan 52Baldwin 02 Coosa 19 Jackson 36 Perry 53Barbour 03 Covington 20 Jefferson 37 Pickens 54Bibb 04 Crenshaw 21 Lamar 38 Pike 55Blount 05 Cullman 22 Lauderdale 39 Randolph 56Bullock 06 Dale 23 Lawrence 40 Russell 57Butler 07 Dallas 24 Lee 41 St. Clair 58Calhoun 08 DeKalb 25 Limestone 42 Shelby 59Calhoun 08 DeKalb 25 Limestone 42 Shelby 59Chambers 09 Elmore 26 Lowndes 43 Sumter 60Cherokee 10 Escambia 27 Macon 44 Talladega 61Chilton 11 Etowah 28 Madison 45 Tallapoosa 62Ch t 12 F tt 29 M 46 T l 63Choctaw 12 Fayette 29 Marengo 46 Tuscaloosa 63Clarke 13 Franklin 30 Marion 47 Walker 64Clay 14 Geneva 31 Marshall 48 Washington 65Cleburne 15 Greene 32 Mobile 49 Wilcox 66Coffee 16 Hale 33 Monroe 50 Winston 67Colbert 17 Henry 34 Montgomery 51



Develop Initial Case Definition: Develop Initial Case Definition: C i A l d OC i A l d OCounting Apples and OrangesCounting Apples and Oranges

S t f it i f d idi h thSet of criteria for deciding whether an individual should be classified as “ill”OObjective criteria Outbreak-associated vs. normal background

Value of routine surveillance dataPrimary vs. secondary cases



Outbreak Case DefinitionsOutbreak Case Definitions

Begin general, but become increasingly specific as information is gathered

Person, Place and Time associationClinical criteriaClassify cases based on certainty

Confirmed (positive lab)( )Probable (no lab; symptoms)Suspect (no lab; some symptoms)



Revise Case DefinitionsRevise Case DefinitionsRevise Case DefinitionsRevise Case DefinitionsOngoing throughout investigationP i d fi i i dPrecise definitions reduce potential for misclassification:

Estimated 36% of enteric infections are foodborne;I l t hi t h tIncomplete case history can haunt you;Incorrectly classifying individuals can bias results;Make it harder to detect true associationsMake it harder to detect true associations.



Misclassification Example: Misclassification Example: S l d ES l d ESalad ExposureSalad Exposure

Not illNot illNot ill Not ill

Salad Yes (?)Salad Yes (?)

Not ill Not ill

Salad No (?)Salad No (?)



Misclassification Example:Misclassification Example:Exposure Date Incubation PeriodExposure Date Incubation PeriodExposure Date Incubation PeriodExposure Date Incubation Period

Norovirus average incubation period: 36 hrs (range: 10-50 hrs) Epidemiology Division

Bureau of Clinical LaboratoriesBureau of Environmental Services

16

Misclassification Example:Misclassification Example:Exposure Date Incubation PeriodExposure Date Incubation PeriodExposure Date Incubation PeriodExposure Date Incubation Period

3 6 9 12 15 21 24 27 30 33 36 39 42 45 48 51 54

Norovirus average incubation period: 36 hrs (range: 10-50 hrs)

3 6 9 12 15 21 24 27 30 33 36 39 42 45 48 51 54



Make Epidemiologic AssociationsMake Epidemiologic AssociationsMake Epidemiologic AssociationsMake Epidemiologic Associations

P Pl TiPerson, Place, TimeSystematically organize key y y g yinformationDevelop initial hypothesisDevelop initial hypothesis



Person: AL Outbreak ExamplesPerson: AL Outbreak Examplespp



Symptoms: Frequency TableSymptoms: Frequency Tabley p q yy p q y



Place: Common Place: Common Exposure LocationExposure Location

Case 1 – rest. A, B, C, DCase 2 – rest. B, E, FCase 3 – rest. A, B, G, H, ICase 4 – rest. B, D, J, K, , ,

What is the common exposure location?What is the common exposure location?



Place: Common Place: Common E L ti ( t )E L ti ( t )Exposure Location (cont.)Exposure Location (cont.)Restaurant

Same restaurantMultiple restaurants, same chain or p ,ownerMultiple chains, common distributorp

Banquets, Birthday Parties, Wedding Receptions, Conferences, BasketballReceptions, Conferences, Basketball Game, School Field Trip, Summer Camp, etc.



Camp, etc.

22

PlacePlace



An Epidemic CurveAn Epidemic Curve

1112 Fatal

Non-fatalX axis = units of time (1/4 to 1/3 of incubation time)Y axis = number of cases

Shows progression of outbreak over time

89

1011

Cas

es

Non-fatal

There is an inherent delay between the date

f

567

umbe

rofC of illness onset and the

date the case is reported to Public Health

1234N

u Health

6/27 8/2 9/6 10/11 11/15 12/20 1/24 2/27 4/301

DateEpidemiology Division


24Source: Centers for Disease Control and PreventionSource: Centers for Disease Control and Prevention

SalmonellaSalmonella Outbreak Investigations: Outbreak Investigations: Ti li f R ti g CTi li f R ti g CTimeline for Reporting CasesTimeline for Reporting Cases

Patient Eats Contaminated

1-3 Days IncubationContaminated

Food PatientBecomes Ill

Time to contact with health care system = 1-5 days

Stool SampleCollected

S

Time to diagnosis = 1-3 days

Shipping Time = 0 7 days SalmonellaIdentified

Public Health Lab Receives Case

Shipping Time = 0-7 days

Lab ReceivesSample

CaseConfirmedAs Part ofOutbreak

Serotyping and “DNA fingerprinting” Time = 2-10 days


Bureau of Environmental Services25Source: CDC

PointPoint--Source ExposureSource ExposurePointPoint Source ExposureSource Exposure

910

6789

Cas

es

3456

mbe

r of

0123

Num

01 3 5 7 9 11 13 15

DaysEpidemiology Division


26

Ongoing ExposureOngoing ExposureOngoing ExposureOngoing Exposure

910

6789

Cas

es

3456

mbe

r of

0123

Num

01 3 5 7 9 11 13 15



27

y

Secondary ExposuresSecondary ExposuresSecondary ExposuresSecondary Exposures

910

6789

Cas

es

456

mbe

r of C

123

Num

01 3 5 7 9 11 13 15



28

Days

HypothesisHypothesisHypothesisHypothesis

“An unproved theory ...tentatively accepted to explain certain facts or toaccepted to explain certain facts or to provide a basis for further investigation”

Source: Webster’s New World Dictionary 3rd EditionDictionary, 3rd Edition



H th d Q ti i H th d Q ti i Hypotheses and Questionnaires Hypotheses and Questionnaires

Hypothesis generating

Hypothesis testing



Example of HypothesisExample of HypothesisExample of HypothesisExample of Hypothesis

Food item consumed at the SmithFood item consumed at the Smith Wedding reception caused illnessesData needed to test informationData needed to test information

What kind of food items were eaten?Who ate the food item? Who did not eat?Who ate the food item? Who did not eat?How much did each person eat?Illness onset (date and time)? ( )



Develop Initial HypothesisDevelop Initial Hypothesisp ypp yp

Multiple hypotheses may be p yp ycompatible with data initiallyHelps clarifyHelps clarify

What is knownWhat is missingWhat is missingActions needed to gather missing informationmissing information



Unknown Causative Agent Unknown Causative Agent gg

Review what is known about casesSymptoms, severity of diseaseEvents attended or anything unusualy gFoods consumed and methods of food preparationp p

Identify most likely agent(s)Review referencesReview referencesConsultation



Known Causative AgentKnown Causative AgentKnown Causative AgentKnown Causative Agent

Review what is known about the agentReview what is known about the agentTypical signs and symptomsModes of transmissionModes of transmissionFoods in past outbreaks

Is this situation similar to otherIs this situation similar to other previously reported incidents?Be aware of recent food recallsBe aware of recent food recalls



New Routes of Transmission New Routes of Transmission New Routes of Transmission New Routes of Transmission are Being Identifiedare Being Identified

Example:pE. coli O157:H7 in apple cider



Case Definition Case Definition vs.vs. HypothesisHypothesis

Case Definition HypothesisClassify cases vs. controls

Describe exposure to

IncludesPerson

test analyticallyTheory

PlaceTime

Do NOT include hypothesis in case Time

Symptomsdefinition!



Group ExerciseGroup Exercise

Case Definition and Hypothesis



Questionnaire Design/ Questionnaire Design/ Interview ProcessInterview Process

Questions should be clear concise andQuestions should be clear, concise and asked in an uniform way Avoid open-ended questions unlessAvoid open ended questions, unless hypotheses generating questionnaireInclude menu, when available, to avoidInclude menu, when available, to avoid recall biasQuestionnaire should take into account Qcompleteness of data collection, time involved, and relevance of questions



Questionnaire Design/ Questionnaire Design/ Q g /Q g /Interview Process Interview Process --22

Include as many not-ill as possible;Review questionnaire to make sureReview questionnaire to make sure there is no conflicting/missing information to avoid calling back;information to avoid calling back;Stool and food samples are very helpful in solving the outbreakhelpful in solving the outbreak



Examples of Examples of Examples of Examples of Epidemiological StudiesEpidemiological Studies

1. Case Series

2. Cohort Studies

3. Case-Control Studies



1 Case Series1 Case Series1. Case Series1. Case Series

A i t t ifAppropriate to use if:Small number of cases (< 5)Controls are unavailable (e gControls are unavailable (e.g., everyone ill)

Provide person place and timeProvide person, place, and time associations



2 Cohort Studies2 Cohort Studies2. Cohort Studies2. Cohort Studies

Groups of exposed and unexposed individuals can be easily identifiedyCompare risk of illness by what was/was not eaten

Example: Church supper



3 Case3 Case--Control StudiesControl Studies3. Case3. Case Control StudiesControl StudiesTypically used in foodborneinvestigations when:

Exposed group is very large orExposed group is not easily identified

Compare ill with non-ill Individuals to determine likelihood of having eaten specific foods

E l l ddi tiExamples: very large wedding reception or sporadic E. coli cases



Measures (Calculations)Measures (Calculations)Measures (Calculations)Measures (Calculations)

Measure of OccurrenceMeasure of OccurrenceAttack Rate

Measure of AssociationMeasure of AssociationRelative Risk (RR): Cohort studiesOdds Ratio (OR): Case Control studiesOdds Ratio (OR): Case-Control studies



Attack Rate: Measure of OccurrenceAttack Rate: Measure of OccurrenceAttack Rate: Measure of OccurrenceAttack Rate: Measure of Occurrence

Attack Rate (AR)Expresses occurrence of a disease among a particular at-risk population for a limited period of time often due to a verylimited period of time, often due to a very specific exposure. Can be event specific or food specific

Number ill people who consumed itemAR =

Can be event-specific or food-specific

Total number people consuming itemAR =



Measures of Association Between Measures of Association Between Exposure (Food Item) and DiseaseExposure (Food Item) and Disease

Depends on type of studyDepends on type of study“Relative risk” cohort studies

Risk of developing disease given theRisk of developing disease given the exposure

“Odds ratio” case-control studiesOdd f h i th i thOdds of having the exposure given the disease

Computer programs greatly speedComputer programs greatly speed the calculations



Estimating Risks Associated Estimating Risks Associated ggwith “Exposure”with “Exposure”

Compare attack rates among exposed and unexposed

Attack Rate (exposed) / Attack Rate (unexposed)Relative Risk = Attack Rate (exposed) / Attack Rate (unexposed)Relative Risk



2 by 2 Table to Calculate 2 by 2 Table to Calculate Relative RiskRelative RiskRelative RiskRelative Risk

Estimates magnitude of association between exposure and disease in exposed group relative to unexposed group

Disease

p g p p g p

a / (a + b)RR

totalYes ( + ) No ( - )

a + bYes ( + )E

a b ( )c / (c + d)RR =

b + da + ctotal a+b+c+d

c + dNo ( - )Exposure

c d




Relative Risk Relative Risk -- Cohort StudiesCohort StudiesRelative Risk Relative Risk Cohort StudiesCohort Studies

Measurement of the risk ofMeasurement of the risk of developing disease given a specific exposure (a food item)exposure (a food item)Compares attack rates between exposed and unexposed groups

Relative Risk Attack Rate (AR) among Exposed a / (a + b)/ ( d)===

(RR)( ) g

Attack Rate (AR) among Unexposed c / (c + d)



Number of persons who ate specified item

Number of persons who did not eat specified item

Ill Not Ill Total Attack rate (%) Ill Not Ill Total Attack rate %Baked ham 29 17 46 63 17 12 29 59Spinach 26 17 43 60 20 12 32 62Mashed potato 23 14 37 62 23 14 37 62Cabbage salad 18 10 28 64 28 19 47 60Jello 16 7 23 70 30 22 52 58Rolls 21 16 37 57 25 13 38 66Brown bread 18 9 27 67 28 20 48 58Milk 2 2 4 50 44 27 71 62Coffee 19 12 31 61 27 17 44 61Water 13 11 24 54 33 18 51 65Cakes 27 13 40 67 19 16 35 54Ice cream (van) 43 11 54 80 3 18 21 14( )Ice cream (choc) 25 22 47 53 20 7 27 74Fruit salad 4 2 6 67 42 27 69 61


Bureau of Environmental Services51Reference: CDC Epi-Ready Training Manual

Church Supper Cohort Study Church Supper Cohort Study ––Relative RiskRelative Risk

V ill iVanilla ice creamAR (exposed) ÷ AR (unexposed)79 6 ÷ 14 3 = 5 679.6 ÷ 14.3 = 5.6Persons consuming vanilla ice cream were 5.6 times more likely to become ill ythan those who did not eat vanilla ice cream



Number of persons who ate specified item

Number of persons who did not eat specified item

Ill Not Ill Total Attack rate (%) Ill Not Ill Total Attack rate %Baked ham 29 17 46 63 17 12 29 59Spinach 26 17 43 60 20 12 32 62Mashed potato 23 14 37 62 23 14 37 62Cabbage salad 18 10 28 64 28 19 47 60Jello 16 7 23 70 30 22 52 58Rolls 21 16 37 57 25 13 38 66Brown bread 18 9 27 67 28 20 48 58Milk 2 2 4 50 44 27 71 62Coffee 19 12 31 61 27 17 44 61Water 13 11 24 54 33 18 51 65Cakes 27 13 40 67 19 16 35 54Ice cream (van) 43 11 54 80 3 18 21 14( )Ice cream (choc) 25 22 47 53 20 7 27 74Fruit salad 4 2 6 67 42 27 69 61


Bureau of Environmental Services53Reference: CDC Epi-Ready Training Manual

Church Supper CohortChurch Supper CohortSSStudy Study -- Relative RiskRelative Risk

Chocolate ice creamChocolate ice creamAR (exposed) ÷ AR (unexposed)53 2 ÷ 74 1 = 0 753.2 74.1 0.7Persons consuming chocolate ice cream were 0.7 times as likely (or 30% less likely) to become ill than those who did not eat chocolate ice cream



2 by 2 Table to Calculate 2 by 2 Table to Calculate Odds RatioOdds RatioOdds RatioOdds Ratio

Estimates magnitude of association between exposure and disease in diseased group (cases) relative to non-diseased group (control)

t t lY ( ) N ( )

Disease

totalYes ( + ) No ( - )

a + bYes ( + )Exposure

a b a/ca/cb/db/d

adadbcbcOROR == ==


c + dNo ( - )Exposure

c db/db/d bcbc

b da ctota



Odds Ratio Odds Ratio --CaseCase--Control StudiesControl Studies

Measurement of the odds of havingMeasurement of the odds of having an exposure (specific food consumption) given the diseaseconsumption) given the diseaseEstimates the Relative Risk derived from cohort studiesfrom cohort studies



How Valid are Your Findings?How Valid are Your Findings?Is the observed association between exposure and disease (expressed by the RR or OR) due to

Bias: systematic error

alternative explanations?

Bias: systematic error SelectionInformation (recall, interviewer, (misclassification)

ChanceSampling variabilitySampling variabilitySampling size



Examples of BiasExamples of BiasExamples of BiasExamples of Bias

Random misclassification of cases vs.Random misclassification of cases vs.controls or exposed vs. unexposed

biases OR or RR toward “1”Recall bias

cases remember exposures better than do pcontrolsproblem with retrospective studiesmay result in inflated OR



Evaluating the Role of ChanceEvaluating the Role of Chancegg

P-valueP b bilit i i ti ld hProbability a given association could have occurred by chance alone“Statistically significant” defined as p ≤ 0.05Consider all available evidence when interpreting p-values

95% Confidence Interval95% Confidence IntervalRange within which the true association lies, based on 95% assurancebased on 95% assurance



PP--vvalues and Confidence Intervals alues and Confidence Intervals Example 1Example 1

Table 16 Analysis of Food Item 2 ILL

| |


| |

5 / (5 + 10)RR = ==..3333

Example 1Example 1

ITEM2 | + - | Total-----------+---------------+------ + | 5 10 | 15 - | 9 11 | 20 -----------+---------------+------

ITEM2 | + - | Total-----------+---------------+------ + | 5 10 | 15 - | 9 11 | 20 -----------+---------------+------

9 / (9 + 11)RR = == .45

Total | 14 21 | 35 Total | 14 21 | 35

•• RR= 0.74• 95% confidence limits for RR = 0.43 < RR < 2.79 Not significant because includes “1”

•P-value = 0.486 Not significant because more than “0.05”



PP--vvalues and Confidence Intervals alues and Confidence Intervals Example 2Example 2


Table 15 Analysis of Food Item 1 ILL 11 / (11 + 4) .7333

Example 2Example 2

ITEM1 | + - | Total -----------+---------------+------ + | 11 4 | 15 - | 3 17 | 20 -----------+---------------+------

ITEM1 | + - | Total -----------+---------------+------ + | 11 4 | 15 - | 3 17 | 20 -----------+---------------+------

11 / (11 4)3 / (3 + 17)RR = =

.7333.15

Total | 14 21 | 35 Total | 14 21 | 35

•• RR= 4.89• 95% confidence limits for RR =1.65 < RR < 14.50 Significant because does not include “1”

•P-value = 0.000490 Significant because less than “0.05”



PP--vvalues and Confidence Intervals alues and Confidence Intervals Example 2 (cont.)Example 2 (cont.)

Indicates that best estimate of increased risk ofIndicates that best estimate of increased risk ofillness associated with consumption of food item 1 is4.89 times; We are 95% confident that the true risk ratio is noless than 1.65 and no greater than 14.5 times the riskof those not consuming this item. Lack of inclusionof those not consuming this item. Lack of inclusion of 1.0 in this interval demonstrates a significantly positive association.



Increase the Sample SizeIncrease the Sample Size

Increase the number of controls (persons not ill)

Outbreak # Ill # Not Ill

12 3

14 7

☺ 11 11☺ 11 11

7 21

Controls Cases



Provide Denominator Provide Denominator Among ExposedAmong Exposed

G (C )Example: AL1003JEG-26a (Church) 15 Interviewed (11 ill, 4 not ill)15 Interviewed (11 ill, 4 not ill)2 events (Banquet on Saturday and Luncheon on Sunday)and Luncheon on Sunday)

60-65 attended banquetq20-25 attended luncheon



PP--vvalue: Effect of Sample Sizealue: Effect of Sample SizeDiseaseDisease

ExposureExposure IllIll Not illNot ill TotalTotal++ --

Eat food +Eat food + 44 11 55Did not eat food Did not eat food -- 11 22 33

55 33 88



PP--vvalue: Effect of Sample Size (cont.)alue: Effect of Sample Size (cont.)DiseaseDisease

ExposureExposure illill Not illNot ill TotalTotal++ --

Ate food +Ate food + 88 22 101088 22 1010Did not eat food Did not eat food -- 22 44 66

1010 66 1616



PP--vvalue: Effect of Sample Size (cont.)alue: Effect of Sample Size (cont.)DiseaseDisease

ExposureExposure IllIll Not illNot ill TotalTotal++ --

Ate food +Ate food + 1212 33 1515Did not eat food Did not eat food -- 33 66 99

1515 99 2424



True StoryTrue Story

4 friends meet for dinner3 eat chicken fried rice3 eat chicken fried rice1 chop suey

3 ill with vomiting & diarrhea 12-g18 hrs. after mealNo samples available for testingp gTime temperature abuse of fried rice documentedP-value = 0.2

Is this a foodborne outbreak?Epidemiology Division


68

The Significance of SignificanceThe Significance of SignificanceThe Significance of SignificanceThe Significance of Significance“Not significant” doesn’t necessarily mean “no association ”association.The measure of association (relative risk, odds ratio) indicates the direction and strength of the ) gassociation. The statistical test (p-value), indicates how likely it is that the observed association may have occurredis that the observed association may have occurred by chance alone. No significance may reflect no association in the g ysource population but may also reflect a study size too small to detect a true association in the source population



population.

69Source: Field Epidemiology, 1996, Michael B. Gregg

Interpret ResultsInterpret ResultsInterpret ResultsInterpret ResultsHypotheses confirmed or rejected?

If rejected, develop new hypothesesTest new hypotheses by:y y

More analysis with existing dataGather and analyze new data

Final conclusionsWas it foodborne?



Problems Can Interfere Problems Can Interfere with Outbreak Solutionwith Outbreak Solution

Questionnaire designData collection (ex., incomplete data)( )Sample size (ill and not ill)No clinical or food sample for testingNo clinical or food sample for testingReporting time



Statistical SummaryStatistical SummaryRR is calculated in cohort studiesRR compares rate of illness in exposed group to rate of illness in unexposed groupOR is calculated in case-control studiesOR odds in favor of exposure among casesOR = odds in favor of exposure among cases compared to the odds in favor of exposure among the controlsRR and OR are both measures of association“Not significant” ≠ “No association” No significance may reflect lack of association but may also reflect a study size too small to detect true association



Statistical Take Home MessageStatistical Take Home MessageggIf RR or OR = 1, then there is no association between consuming food item and getting sick;between consuming food item and getting sick;If RR or OR is less than 1, then food item is “protective”;If RR or OR is more than 1, then food item is “implicated”;If the 95% CI includes 1 then the result is notIf the 95% CI includes 1, then the result is not considered statistically significant (i.e. there is no statistical difference between the groups);The lower the p-value the more unlikely the results are due to chance



MultiMulti--state FBOsstate FBOsNot all agents are created equal (e.g. S. typhimurium)Microbes have fingerprints too!g pCDC monitors a database (PulseNet) with microbial fingerprint information and notifies states that are part

fof multi-state outbreaks;Periodical conference calls with involved states and regulatory agencies to collaborate on outbreakregulatory agencies to collaborate on outbreak investigation and response;More information from cases may be neededMore information from cases may be neededCDC and ADPH website, links, and media coverage



National 2010 FBOsNational 2010 FBOs



Module Summary Module Summary T k H P i tT k H P i tTake Home PointsTake Home Points

Have a working Case Definition and Hypothesis;B f ibl t f t i i (Be aware of possible routes of transmission (new and old);Questionnaire design is paramount;Questionnaire design is paramount;Interview as many people as possible including “not ill”;Avoid misclassification (exposure) and bias (e. g. recall, selection); Timeliness of reporting is key;Communication is extremely important;Communication is extremely important;Outbreak investigation is a collaborative effort!



Module Learning ObjectivesModule Learning Objectives

Developed a case definitionExplained an epidemic curveExplained an epidemic curveDeveloped an initial hypothesisLi t d th t f t d d i dListed three types of study design and a method of statistical analysisCalculated measures of associationCalculated measures of associationInterpreted significance of dataD t i d if h th fi dDetermined if hypotheses are confirmed or rejected



Group ExerciseGroup ExerciseJoe’s Thanksgiving Dinner Outbreak



module 4: epidemiology investigationadph.org/epi/assets/module_4.pdfmodule learning objectives...

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