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
   1. Bias and sampling error
   2. Bias and sampling error 2
   3. Bias
   4. Measurement bias
   5. Sampling bias
   6. Sampling error
   7. Bias and sampling error - Quiz
   8. Confidence intervals
   9. Confidence intervals - Quiz
   10. Accuracy and precision - theory
   11. 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
28. Dissemination and action

Measurement bias

(go to Outline)

Measurement bias results from poorly measuring the outcome you are measuring. For example:

• The survey interviewers asking about deaths were poorly trained and included deaths which occurred before the time period of interest.

• This would lead to an overestimate of the mortality rate because deaths which should not be included are included.

• One survey team's portable machine to measure haemoglobin malfunctioned and was not checked, as should be done every day. It measured everyone's haemoglobin as 0.3 g/L too high.

• This would lead to an underestimate of the prevalence of anaemia because the readings would overestimate the haemoglobin for everyone measured by that team.