Volume 19 - Article 32 | Pages 1217–1248  

Hotspots and Coldspots: Household and village-level variation in orphanhood prevalence in rural Malawi

By Alexander A. Weinreb, Patrick Gerland, Peter Fleming

Abstract

We explore the spatial distribution of orphans in two areas of Malawi. We first review pertinent themes in qualitative data collected in our research sites. Then, using spatial analysis, we show how positive and negative clusters of orphans—which we term orphanhood "hotspots" and "coldspots"—can be found at the village and sub-village levels. In the third and longest section of the paper, and using multilevel analyses with both simple and complex variance structures, we evaluate the relationship between the presence of orphans and a range of individual, household and village-level characteristics, including households' spatial relationship to each other and to other local sites of significance. This series of analyses shows that the most important covariates of orphan presence are the density of settlement, household size, and religious characteristics, with the latter measured simultaneously at both household and village-level. Other characteristics like education, reported mortality levels and HIV infection, are wholly unrelated to orphan prevalence at all analytic levels. Wealth and various spatial characteristics are only marginally associated with orphan prevalence. We conclude by reviewing some difficulties in explaining causal mechanisms underlying these observed relationships, and discussing conceptual, theoretical and programmatic implications.

Author's Affiliation

• Alexander A. Weinreb - University of Texas at Austin, United States of America EMAIL
• Patrick Gerland - United Nations, United States of America EMAIL
• Peter Fleming - University of Pennsylvania, United States of America EMAIL

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Heterophily in rural Malawi: A small-area observational study of social interaction
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Joint probabilistic projection of female and male life expectancy
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Old age mortality in Eastern and South-Eastern Asia
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Estimating trends in the total fertility rate with uncertainty using imperfect data: Examples from West Africa
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