Mapping HIV epidemics in sub-Saharan Africa with use of GPS data.

WHO and many other organisations are very interested in implementing treatment-as-prevention as a global policy to control the HIV pandemic. Widespread treatment of HIV-infected individuals with antiretroviral therapy will reduce HIV transmission, because it decreases viral load and hence infectiousness. To implement the rollout of treatment-as-prevention in an effi cient manner, estimation of the number of HIVinfected individuals and where they live is needed. This assessment will be diffi cult to accomplish, particularly in areas of sub-Saharan Africa with severe HIV epidemics. We propose a solution to this problem by using geospatial statistical techniques and global positioning system (GPS) data. To estimate the number of HIV-infected individuals in a particular area, a predictive map of the prevalence of infection could be constructed. This map would then be overlaid on a grid map that shows the geographical dispersion of the population. The size of the grid would determine the degree of spatial resolution of the overlay map (ie, the density-of-infection map). The density map would show the estimated number of HIV-infected individuals per km and their geographical distribution over the area of interest. The total number of HIVinfected individuals could be obtained by summing the estimates in each grid over the entire area. All of the geospatial techniques needed to construct density-of-infection maps for HIV are techniques that