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9 Many of the approaches explored in these studies have been limited by logistical obstacles or do not lend themselves to being scaled and integrated into data collection exercises such as the DHS. Numerous methodological approaches to achieving representative samples of mobile populations have been tested, including a “waterpoint approach” in which data are collected at waterholes 6 a capture–recapture transect approach similar to that used to monitor wildlife 7 random geographic cluster sampling 8 and the use of mobile phones. With mounting concerns about emerging zoonotic pandemic disease, it is critical to find ways of including nomadic populations in household surveys and health surveillance systems.
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4, 5 Pastoralists globally face threats to their health and livelihood, including ecologic disruptions, large-scale development projects, conflict, and protracted humanitarian crises. 1 Lack of accurate data prevents anything but speculative estimates of the global population of mobile pastoralists, but estimates range from 50 to 217.5 million. Such strategies result in the “statistical invisibility” of nomadic populations. 4 Large-scale household surveys such as the Demographic and Health Surveys (DHS) Program typically use census-based sampling frames, which magnify and institutionalize the issue of mobile pastoralists’ under-enumeration in the original census.
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Combined with the dispersed distribution of their encampments and cultural barriers, these mobility patterns make surveying nomadic pastoralists notoriously difficult.ĭespite being among the most underserved populations in sub-Saharan Africa, 3 nomadic pastoralists are also underrepresented in the population data used to plan health interventions. 2 Their domestic arrangements are similarly fluid, as family members reside in different geographic locations to manage these livestock. 1 By contrast, pastoralist settlements are often highly mobile, moving over large areas of remote terrain with the herds of livestock on which they subsist. Nomadic pastoralists defy many basic premises of household demographic surveys, including the assumption that individuals are attached to a geographically stable household, and that this household represents a fixed domestic unit. Geospatial sampling methods provide cost-affordable and logistically feasible strategies for sampling mobile populations, a crucial first step toward reaching these groups with health services.
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Our field validation demonstrates that this method is a logistically feasible alternative to conventional sampling frames and may be used at the population level. Using standardized instruments from DHS questionnaires, we draw comparisons with regional and national data finding disparities with DHS data in core MCH indicators, including vaccination coverage, skilled birth attendance, and nutritional status. We then implemented this sampling frame to survey a population of mobile pastoralists in southwest Ethiopia, focusing on maternal and child health (MCH) indicators. By combining remote sensing and geospatial analysis, we developed a sampling strategy designed to capture the current distribution of nomadic populations. As a result, pastoralists are “invisible” in population data such as the Demographic and Health Surveys (DHS). Most surveys use census-based sampling frames which do not accurately capture the demographic and health parameters of nomadic populations. Pastoralist communities are difficult to capture in household surveys because of factors including their high degree of mobility over remote terrain, fluid domestic arrangements, and cultural barriers. Bonds, Department of Global Health and Social Medicine, Harvard Medical School, Boston, MA, E-mail: Abiy Hiruy, Pathfinder International, Addis Ababa, Ethiopia, E-mail: Michele Barry, The Center for Innovation in Global Health, Stanford University, Stanford, CA, E-mail: pastoralists are among the world’s hardest-to-reach and least served populations. Desiree LaBeaud, Division of Infectious Disease, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, E-mail: and Matthew H. Authors’ addresses: Hannah Wild, Stanford University School of Medicine, Stanford, CA, E-mail: Luke Glowacki, Department of Anthropology, Pennsylvania State University, E-mail: Stace Maples, Stanford Geospatial Center, Stanford University, Stanford, CA, E-mail: Mejía-Guevara, Department of Biology, Stanford University, and Stanford Center for Population Health Sciences, Stanford University School of Medicine, Stanford, CA, E-mail: Amy Krystosik and A.