Estimating Demand for Healthcare Facilities in Rural Developing Countries

Brent Lloyd
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Brent Lloyd: Nez Perce Tribe, Land Services Department, Lapwai

Agricultural & Rural Studies, 2023, vol. 1, issue 3

Abstract: Spatial analysis provides decision support for numerous public health issues such as determining locations of healthcare facilities for a given population. With limited population health data available for developing countries, spatial data analysis provides limited benefit in this regard. This paper attempts to assist public health practitioners in overcoming the health information gaps common to developing countries for determining health-related demand locations. We introduce methodologies that use generally available information from Demographic and Health Surveys (DHS). Burkina Faso, a developing country with poor health quality, is used in this paper as a case study to show how DHS data, not generally used for spatial analysis, can be used to estimate multiple area demand locations for healthcare facilities. Factors used to locate demand per administrative province included population density, proximity to major road networks, economic wealth index, birth rate, childhood stunting, and malaria rates. Major health issues in populated areas along access routes ultimately determined the estimated area demand for healthcare facility locations in this analysis.

Keywords: spatial analysis; cluster analysis; weighted factors; Getis-Ord Gi; Demographic Health Surveys; rural health; developing countries; health demand; health access; spatial accessibility (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:ris:sccars:022102

DOI: 10.59978/ar01030018

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