Epidemiology Statistics

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epidiomology statistik







  • Scenario An outbreak of gastroenteritis occurred in Bandar Tun Razak, a suburban neighborhood, on the evening of April 28. A total of 89 people went to the emergency departments of the three local hospitals during that evening. No more cases were reported afterward. The patients complained of headache, fever, nausea, vomiting and diarrhea. The disease was severe enough in 19 patients to require hospitalization for rehydration. The local health department was immediately notified of a potential food-borne outbreak of gastroenteritis in Bandar Tun Razak. Exercise 1 1. Define epidemic, endemic and pandemic. 2. Describe the gastroenteritis outbreak according to disease transmission and epidemiological triad. 3. What are the possible causes of the outbreak? 4. List and discuss steps that should be taken in outbreak investigations 5. What further information needed?

  • Exercise 2 The epidemic team, including a medical epidemiologist (public health physician Health Officer), health inspectors and a nurse, visited the local hospitals to interview the attending physicians, the patients and some of their relatives. Some stool samples were obtained from patients for microbiologic identification of the causative agent. The distribution of the disease by person (age and gender) was found as follows:

    Gastroenteritis Outbreak Findings by Person, Case Distribution by Age and Gender

    Female Male Total by age Age group No %Females No %Male No %

    0 - 5 yr 1 1 6 - 10 yr 38 37 11 yr and

    older 10 2 Total by gender

    Please calculate the totals for each column and row and their corresponding percentages to try to determine if there are any important differences by age or by gender. Interpret your findings.

    Discuss the epidemic curve above

  • Exercise 3 Therefore the epidemic team investigated the places where affected persons, their relatives and neighbors ate that day (April 28). The following table shows the team's findings:

    Gastroenteritis Outbreak Findings by Place


    People who attended

    Ill people

    Attack rate

    People who did not attend

    Ill people

    Attack rate

    Relative risk

    Cafeteria LRT 207 61 157 47 Kedai Makan Ali 246 25 122 13 Restaurant ABC 475 68 189 29 Elementary school cafeteria 239 67 495 22

    Please calculate the attack rates per 100 (incidence rates per 100) by place to try to determine where the contaminated meal was served. For each place compare attack rates (AR) for those who attended with attack rates for those who did not, by using the relative risk (i.e., RR = AR in attendees/AR in non attendees). Interpret your findings.

  • Exercise 4 Once the implicated place was determined, the investigation centered on the food. The following table includes the food items served in that place on April 28:

    Gastroenteritis Outbreak Findings by Person Ate the food item Did not eat the food item Food

    Item No. people

    Ill people

    Attack rate

    No. people

    Ill people

    Attack rate

    Relative risk

    Beef rendang 276 28 266 27 Burger 218 21 131 14 Salad 105 49 297 15 Baked potato 139 11 213 31 Fruit cocktail 88 48 279 25 Ice cream 175 18 203 49

    Important note: None of the kitchen personnel were ill. The names of the kitchen personnel and their participation in the food preparation are as follows: Ms Mary prepared the beef rendang and the potatoes, Johan prepared the salad and the fruit, Salmah served all dishes except the ice cream, and Jamilah prepared the burgers and served the ice cream. The ice cream was a commercial brand and was bought at a nearby supermarket. Please calculate the attack rates per 100 (incidence rates per 100) by food item to try to determine the one that was probably contaminated. Compare attack rates (AR) for those who ate the food item with attack rates for those who did not eat the food item, by using the relative risk (i.e., RR = AR in those who ate the food/AR in those who did not eat the food). Interpret your findings.

  • Exercise 5 Given that the epidemic team worked fast enough and the implicated meal(s) was (were) identified before all food leftovers were discarded, food samples from some meal leftovers were taken to the laboratory. In addition, stool samples were taken from the kitchen personnel who prepared or handled each different food item. The laboratory confirmed that Salmonella toxin was present in some of the food samples and that one of the kitchen personnel of that place had the same Salmonella species. Furthermore, the Salmonella species found in the food and the kitchen worker was the same species found in stool samples of the patients. Please discuss these findings and identify the kitchen worker possibly responsible for the outbreak. Discuss the general principle of prevention and control of gastroenteritis outbreak.

  • 1Screening Test

    Screening: DefinitionThe identification, amongst apparently healthy individuals, of those who are sufficiently at risk of a specific disorder

    Screening vs Diagnosis

    z In screening, there is no intention to make a definitive diagnosis or offer therapeutic intervention solely based on a positive result

    Screening program: Requirements (I)

    z Natural history of disease must be understood

    z Have an agreed policy on whom to treatz Prevalence of undiagnosed disease highz Disease has high morbidity and mortalityz Of public health concernz Early treatment easier and more effective

    Screening program: Requirements (II)

    z Signs present to indicate disease presencez Screening test acceptable and harmlessz Screening test must be validz Yield of screening must be highz Diagnostic work-up for a positive test must

    have acceptable morbidityz Screening exercise must be cost-effective

    The ideal screening test

    z Would always give the right answer

    z Quick, safe and simple

    z Painless, reliable and inexpensive

  • 2Structure of a study involving a screening test

    z Resembles an observational studyz Same concepts applied for diagnostic testz Designed to determine how well a test can

    discriminate between diseased and non-diseased

    z A predictor variable (the test result)z An outcome variable (presence or absence

    of disease)

    Structure of a study involving a screening test

    z The test result

    Dichotomousz +ve or -ve

    Categoricalz +, ++, +++, ++++

    Continuousz mg/dl, ng/L, etc.

    z The disease as outcome variable

    Presence or absence determined by a gold standard

    Measures of accuracy for screening tests:

    z Validity Sensitivity and specificity

    z Predictive values (PV) Positive PV and Negative PV

    Evaluation of a screening testTRUTH

    Disease No disease

    A BTrue-positive False-positive

    C DFalse-negative True-negative




    Sensitivity = AA + C

    x 100 Specificity = DB + D

    x 100

    Sensitivity Specificity

    z Sensitivity is the proportion of those with the disease who tested positive

    z Indicates how good a test is at identifying the diseased

    z Specificity is the proportion of those without the disease who tested negative

    z Indicates how good a test is at identifying the non-diseased

    Sensitivity and specificity

    z Describe the performance of a test

    z A test with a high sensitivity is useful to RULE OUT the disease

    z A test with a high specificity is useful to CONFIRM the presence of disease

  • 3Predictive values (PV)

    zAssess the usefulness of a testzA test of efficient use of time and

    resourcesz PV estimate the probability of diseasez PV describe the frequency of correct

    identificationz Positive PV and Negative PV

    Predictive valuesTRUTH

    Disease No disease

    A BTrue-positive False-positive

    C DFalse-negative True-negative




    PV+ = AA + B

    x 100 PV- = DC + D

    x 100

    Predictive values

    z PV of a positive test is the proportion of individuals who test +ve and have the disease

    z PV of a negative test is the proportion of individuals who test -ve and dont have the disease

    z The positive PV estimates the likelihood that a person who tests positive has the disease

    z The negative PV indicates the likelihood that a person who tests negative is actually disease free

    Predictive values

    z Greatest value in deciding whether to implement a screening program

    z Not useful if positive PV is low

    Sensitivity, specificity and PVsDisease status

    Cancer No cancer Total

    Positive 132 985 1117Negative 47 62295 62342

    Total 179 63280 63459

    Prevalence: 179/63459 x 100 = 0.3%Sensitivity: 132/179 x 100 = 73.7%Specificity: 62295/63280 x 100 = 98.4%+ve PV: 132/1117 x 100 = 11.8% (False +ve 88.2%)-ve PV: 62295/62342 x 100 = 99.9% (False -ve 0.01%)

    Shapiro et al., 1988


    Commentsz Mammography had an excellent specificity (98%)z False +ve tests outnumber the true +ve tests by

    over 7:1 (PV+ =12%)