Spatial Analysis of HIV Infection and Associated Risk Factors in Botswana

Malebogo Solomon, Luis Furuya-Kanamori and Kinley Wangdi
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Malebogo Solomon: Department of Global Health, Research School of Population Health, Australian National University, Canberra, ACT 2601, Australia
Luis Furuya-Kanamori: Department of Global Health, Research School of Population Health, Australian National University, Canberra, ACT 2601, Australia
Kinley Wangdi: Department of Global Health, Research School of Population Health, Australian National University, Canberra, ACT 2601, Australia

IJERPH, 2021, vol. 18, issue 7, 1-13

Abstract: Botswana has the third highest human immunodeficiency virus (HIV) prevalence globally, and the severity of the epidemic within the country varies considerably between the districts. This study aimed to identify clusters of HIV and associated factors among adults in Botswana. Data from the Botswana Acquired Immunodeficiency Syndrome (AIDS) Impact Survey IV (BIAS IV), a nationally representative household-based survey, were used for this study. Multivariable logistic regression and Kulldorf’s scan statistics were used to identify the risk factors and HIV clusters. Socio-demographic characteristics were compared within and outside the clusters. HIV prevalence among the study participants was 25.1% (95% CI 23.3–26.4). HIV infection was significantly higher among the female gender, those older than 24 years and those reporting the use of condoms, while tertiary education had a protective effect. Two significant HIV clusters were identified, one located between Selibe-Phikwe and Francistown and another in the Central Mahalapye district. Clusters had higher levels of unemployment, less people with tertiary education and more people residing in rural areas compared to regions outside the clusters. Our study identified high-risk populations and regions with a high burden of HIV infection in Botswana. This calls for focused innovative and cost-effective HIV interventions on these vulnerable populations and regions to curb the HIV epidemic in Botswana.

Keywords: Botswana; HIV; spatial analysis; clusters; risk factors (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2021
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