Dasymetric estimation of tuberculosis incidence rates and facility-level hot spot analysis in Johannesburg

Crankshaw, Beth Pulane
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South Africa is listed by the World Health Organisation (WHO) (2020) as one of the top 20 global contributors to absolute case numbers for TB burden and is among the 14 countries with the highest burden of HIV associated TB, and multi-drug resistant TB (MDR-TB).Understanding the geographical disparities in TB distribution provides a foundation upon which informed decisions around targeted interventions can be made. Determining TB disease incidence at a fine scale is therefore critical in the field of public health where strategic interventions, e.g. targeting disease hotspots, can result in exponential reductions in transmission and incidence. However, routine geographic analysis of the distribution of TB are not at an appropriate scale for such knowledge generation due to the format in which population and health data are available. This project therefore explores an alternative dasymetric areal interpolation technique for determining incidence of microbiologically-confirmed pulmonary TB (mPTB) from facility-level data where catchment populations are unknown. A series of hot spot detection techniques are then applied to the dasymetric mPTB output to identify areas of high incidence. Standard approaches are explored including K-Nearest Neighbour (KNN), inverse distance and fixed distance weighting techniques, as well as the cluster morphology AMOEBA method