A Spatial Autocorrelation Method for Taenia solium Risk Mapping: The Case of Lao PDR

Abstract

Background: The World Health Organization has identified Taenia solium mapping tools as an important development for intensifying control in hyperendemic areas. Taenia solium has also been identified as a priority by the Lao PDR government. There is a limited understanding of the distribution of T. solium due to inherent diagnostic challenges. Method: Global and local autocorrelation statistics were applied to available risk factor data sourced from national censuses to map the risk of Taenia solium in Lao PDR. Results: Approximately 50% of villages could be considered hot spots for one or more risk factors. Different risk factor hot spots co-occurred in 30% of villages. Twenty per cent of villages were classified as hot spots for the proportion of households owning pigs and another risk factor. Northern Lao PDR was the dominant high-risk area. This is consistent with passive reports, limited surveys, and anecdotal reports. One smaller area in southern Lao PDR was also identified as high-risk. This is of particular interest because T. solium has not previously been investigated in this area. Conclusions: The methods applied provide a simple, rapid, and versatile approach that allows endemic countries to begin mapping the risk of T. solium at a sub-national level.