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
    1. Inherent problems
    2. Incomplete reporting
    3. Biases from the health system
    4. Changes in the surveillance system
    5. Denominator problems
    6. Assessing quality of data
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
28. Dissemination and action

Incomplete reporting

(go to Outline)

In addition to these inherent limitations, surveillance, as practiced in humanitarian emergencies, often has several problems.

Regardless of how well trained and dedicated, health workers often fail to submit the data requested of them. They may not complete reporting forms or not remember to submit them. If only 50% of cases of a certain disease are reported, the calculated incidence rate will be only 50% of the real rate in the population. If you assume that all cases are reported, you may substantially underestimate the importance of that disease.

Remember, reporting diseases is probably not in a health care worker's job description, they are not being paid for it, and they are not being evaluated on how well they do it. It is up to the public health authorities to motivate health workers by providing feedback showing how the data collected can help their work and improve the health of the population.

When analyzing surveillance data, it may be a good idea to maintain a high degree of scepticism. Always assume that many cases of disease are not reported. If a surveillance system is stable, so that the same proportion of actual cases of disease are reported to surveillance, then the changes over time tell you much more than the absolute incidence rates. If fact, it may not be possible to rely on the incidence rates calculated from incomplete surveillance data.