Outbreak Investigation Report Template

Introduction and Background

-Summarize how outbreak came to light

-General description of cases including person, place and time and symptoms

-Possible etiologic agents (provide in-text citations APA style)

Investigation Methods

-Description of epidemiologic methods (provide copy of your questionnaire as an appendix)

-Description of microbiologic and environmental investigations (what would you have done)

Results

Table 1: Provide a table of the descriptive results for cases and controls (columns should include variable, counts and percentages for cases, counts and percentages for controls). Arrange the variables so the demographic variables are at the top, then the symptoms and lastly the risk factors.   

Table 2: Provide a table showing crude odds ratio with confidence intervals and adjusted odds ratios with confidence intervals for each variables

Figure 1: Copy of your GIS map

In text of results, first describe what is in table 1 and on the GIS map and then in table 2.

Discussion

-Summarize your significant results in a couple of sentences.

-State what the likely etiologic agent (s) and possible scenarios that led to the outbreak.

-Provide a list of recommended control measures.

-Describe the limitations of your study.

-Have a 1-2 sentence conclusion.

-Be sure to include in-text citations APA style

References

Provide a list of references APA style.

Here is example wording to help you with your results section

Different ways to describe comparisons of proportions in a 2×2 table (data not from this case study)

The proportion of cases who are women was significantly higher (43.6%) than the proportion among controls (30.2%) (P<0.001).

or

There was a significantly higher percentage of women among cases (43.6%) than controls (30.2%) (P<0.001).

or

There is a higher percentage of women among cases (43.6%) than controls (30.2%), and the difference is statistically significant (P<0.001).

Different ways to describe output from a multivariate logistic regression

There was a significantly higher crude odds for illness among women relative to men (unadjusted odds ratio 1.98; 95% CI 1.27-3.09, P=0.03). However, after controlling for age (you would put in all the variables that you are controlling for in your model), the association was no longer statistically significant (adjusted odds ratio 1.32; 95% CI 0.94-3.09, P=0.29).  

Controlling for age, (list all the variables in the model that you controlled for), being aged ≥50 years was significantly associated with illness (adjusted odds ratio 3.21; 95% CI 1.98-4.2, P=0.01) compared with being 18-34 years of age.