Leo C. Zulu|Ezekiel Kalipeni|Eliza Johannes
Analyzing spatial clustering and the spatiotemporal nature and trends of HIV/AIDS prevalence using GIS: the case of Malawi, 1994-2010
Michigan State University|Colgate University|Institute For Defense Analyses
although local spatiotemporal analysis improve understanding geographic variation hiv epidemic drivers search targeted interventions limited subsaharan africa despite recent declines malawis estimated 100 hiv prevalence 2011 remained among highest globally using data pregnant women malawi study 1 examines spatiotemporal trends hiv prevalence 19942010 2 2010 identifies maps spatial variationclustering factors associated hiv prevalence district level inverse distance weighting used within arcgis geographic information systems gis software generate continuous surfaces hiv prevalence point data 1994 1996 1999 2001 2003 2005 2007 2010 obtained surveillance antenatal clinics surfaces prevalence estimates extracted district level results mapped nationally spatial dependency autocorrelation clustering hiv prevalence also analyzed correlation multiple regression analyses used identify factors associated hiv prevalence 2010 spatial variationclustering mapped compared hiv clustering analysis revealed wide spatial variation hiv prevalence regional urbanrural district subdistrict levels however prevalence spatially leveling within across subepidemics declining significantly 1999 prevalence exhibited statistically significant spatial dependence nationally following initial 19951999 localized patchy lowhigh patterns epidemic spread rapidly locally hiv hotspots clustered among eleven southern districtscities coldspot captured configurations six central region districts preliminary multiple regression 2010 hiv prevalence produced model four significant explanatory factors adjusted r2 0688 mean distance main roads mean travel time nearest transport percentage taken hiv test ever percentage attaining senior primary education spatial clustering linked factors particular subsets high hivprevalence districts spatial analysis enhanced understanding local spatiotemporal variation hiv prevalence possible underlying factors potential differentiated spatial targeting interventions findings suggest intervention strategies also emphasize improved access healthhiv services basic education syphilis management particularly rural hotspot districts research done drivers finer scale