Making Pastoralists Count: Geospatial Methods for the Health Surveillance of Nomadic Populations

Nomadic pastoralists are among the world’s hardest-to-reach and least-served populations. Pastoralist communities are notoriously difficult to capture in household surveys due to factors including their high degree of mobility, the remote terrain they inhabit, fluid domestic arrangements, and cultural barriers. Most surveys utilize census-based sampling frames which do not accurately capture the demographic and health parameters of nomadic populations. As a result, pastoralists are largely “invisible” in population data such as the Demographic and Health Surveys (DHS). By combining remote sensing and geospatial analysis, we developed an alternative sampling strategy designed to capture the current distribution of nomadic populations. We then implemented this sampling frame to survey a population of mobile pastoralists in southwest Ethiopia, focusing on maternal and child health (MCH) indicators. Using standardized instruments from DHS questionnaires, we assessed the MCH status of this population in order to draw comparisons with regional and national data. We find substantial disparities between our data collected using a geospatial sampling frame and regional DHS data in core MCH indicators including vaccination coverage, skilled birth attendance, and nutritional status. Census-based measures do not adequately capture population-level characteristics, risking substantial misreporting of the health status of mobile populations. Our study is the first to employ a geospatial survey of a nomadic group at the population level, and our field validation demonstrates that this methodology is a logistically feasible alternative to conventional sampling frames. Geospatial sampling methods open up cost-affordable and logistically feasible strategies for sampling pastoralists and other mobile populations, which is a crucial first step towards reaching these underserved groups with health services.