02161nas a2200265 4500000000100000008004100001260001200042653002400054653005700078653004000135653002300175653001800198653001300216653001200229653003900241100001400280700001200294700001000306245008900316856006600405300000900471490000600480520139500486022001401881 2023 d bMDPI AG10aInfectious Diseases10aPublic Health, Environmental and Occupational Health10aGeneral Immunology and Microbiology10aNeurocysticercosis10aTaenia solium10aZoonoses10aLao PDR10aNeglected tropical diseases (NTDs)1 aLarkins A1 aBruce M1 aAsh A00aA Spatial Autocorrelation Method for Taenia solium Risk Mapping: The Case of Lao PDR uhttps://www.mdpi.com/2414-6366/8/4/221/pdf?version=1681451765 a1-100 v83 a

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.

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