Spatial Distribution of HIV/AIDS in Botswana
Background: The HIV/ AIDS epidemic poses a serious challenge worldwide and threatens human welfare. The severity of this epidemic varies from district to district in Botswana, with the highest prevalence recorded in Selebi-Phikwe and North-East districts. This study seeks to provide an update of the spatial distribution of HIV/AIDS prevalence using different interpolation procedures. The study also seeks to identify socio-economic, geographic, demographic and behavioural risk factors that promote the spatial distribution of HIV/AIDS prevalence. Data and Methods: This study used secondary data from the Botswana AIDS Impact Survey IV (BAIS IV), a nationally representative sample survey conducted between January and April 2013. The respondents of this study were 116482 HIV positive individuals aged 15-49 years in 12 selected districts. Inverse distance weighting, kriging and natural neighbour interpolation methods were used within ArcGIS Geographic information systems (GIS) software to generate continuous surfaces of HIV/ AIDS prevalence. Spatial autocorrelation and clustering of HIV prevalence were analysed using Moran's I and Getis-Ord General G statistics. Local indicator of spatial association (LISA), Getis-Ord Gi* and Kulldorff scans were employed to identify districts that had high or low concentration of HIV/ AIDS (Hot/Cold spots). Logistic regression was used to identify factors that were associated with spatial distribution of HIV/ AIDS prevalence. Results: Overall HIV/AIDS rates are high with Selebi-Phikwe having the highest of 18.6% followed by Francistown and Central-Mahalapye with 15.7% and 13.8% respectively. Females have a higher prevalence rate (62.7%) than men (37.3%). HIV/AIDS was also observed to be higher among the unmarried (47.7%), Christians (82.6%), fulltime workers (40.5) and among those with junior education (44.9%). Moran's I and Getis General G statistics revealed that HIV/AIDS is spatially distributed with values 0.135, p= 0.0481 and Z = 24101. P =0.016 respectively. Central-Serowe district was identified as the hotspot by both Kulrdoff scan and Getis Ord with a Log likelihood of 11248.11 and relative risk of 7.6. Three secondary clusters were also identified and these are Selebi-Phikwe, Francistown and Central-Mahalapye with relative 1.36, 1.16 and 0.28 respectively. On the contrary, the results revealed Ngwakwetse and Kgalagadi north and south as cold spots. Ordinary kriging with RMSE (6.3263) was found to be the best interpolation method and the continuous maps indicated that HIV/ AIDS is concentrated in the south, northeast and the central districts. The logit model showed that alcohol, the number of sexual partners and condom use are the common risk factors contributing to the spatial distribution of HIV/ AIDS in the selected districts of Botswana. Conclusion: The spatial differences of HIV/ AIDS across the selected districts and the identification of hot/cold spots suggest that a one size fits all kind of intervention might not be suitable for implementation in the different districts. Intervention should therefore, incorporate spatial variability and the identified risk factors. Reduced logistic regression model was significant in identifying factors associated with HIV/ AIDS.