The use of epidemiological tools in conflict-affected populations: open-access educational resources for policy-makers

Table of Contents

1. Welcome
2. Introduction: Epidemiology in crises
3. Ethical issues in data collection
4. Need for epidemiologic competence
5. Surveys - Introduction
6. Surveys - Description of sampling methods
7. Surveys - Sampling error, bias, accuracy, precision, & sample size
8. Surveys - Resources required for surveys
9. Surveys - Critiquing survey reports
10. Surveillance - When to do surveillance
11. Surveillance - Methods
12. Surveillance - Common problems
13. Programme data
14. Rapid assessment
15. Mortality - Indicators and their measurement
16. Mortality - Data sources
17. Mortality - Interpretation and action
18. Nutrition - Introduction and background
19. Nutrition - Indicators and their measurement
20. Nutrition - Data sources
21. Nutrition - Interpretation and action
22. Health services
23. Vaccination programmes
24. Water supply, sanitation, and shelter
25. Violence
26. Presentation of results
27. Formulating conclusions and recommendations
    1. Over-interpreting results
    2. Extrapolating results to other populations
    3. Knowing background information
    4. Interpreting in context
    5. Targeting recommendations
28. Dissemination and action

Knowing background information

(go to Outline)

Be familiar with the accuracy and precision of each of the indicators measured in a survey.

No measurements are perfect. All have measurable biases which lower accuracy and variability which lowers the precision. To properly assess the validity of the survey results, you must know how good its measurements are. Survey reports should describe the measurement methods in enough detail that the reader can easily do such assessment.

Evaluate your survey results relative to known scientific fact.

If the results of your data collection seem to contradict known scientific fact, your methods and results may need some re-evaluation. For example, if a survey shows a very low age-specific mortality rate for children less than 5 years of age in the midst of a measles outbreak in a population with a high prevalence of acute protein-energy malnutrition, perhaps there is something wrong with how you measured mortality.

Of course, interpreting your survey results in light of known scientific fact means you need to know a great deal about the outcomes you include in your survey. As a result, you need to be very knowledgeable and experienced in measuring the outcomes of interest.