Population survey sampling methods in a rural African setting: measuring mortality.

Area of Science:

• Public Health
• Demography
• Epidemiology
• Biostatistics

Background:

• Population-based sample surveys and sentinel surveillance are common in resource-poor settings for health and demographic monitoring.
• These methods face criticism regarding the representativeness of extrapolated data to the wider population.
• Assessing the impact of sampling methods on data representativeness is vital for intervention studies.

Purpose of the Study:

• To evaluate how different sampling methods affect the representativeness of 1% sample data.
• To analyze the impact on various demographic and health parameters in a rural, developing-country context.
• To inform the selection of appropriate sampling strategies for health and demographic monitoring.

Main Methods:

• Utilized data from a large community-based census and health survey in rural Burkina Faso.
• Modeled twenty 1% random samples using seven different sampling procedures across two administrative levels.
• Compared sample data against a 'gold standard' overall survey dataset to assess representativeness.

Main Results:

• All tested sampling methods and parameters demonstrated reasonable performance in representing the overall population.
• Observed variations in representativeness between different sampling approaches and demographic/health parameters.
• Parameter distribution within the total population influenced the observed variations.

Conclusions:

• Sample surveys can yield valuable demographic and health profiles for local populations.
• No single sampling method is optimal for all parameters; selection requires considering parameter distribution.
• Compromises in sampling strategy are often necessary, balancing costs, logistics, and data utility.