Meteorological conditions, elevation and land cover as predictors for the distribution analysis of visceral leishmaniasis in Sinkiang province, Mainland China.

Abstract Visceral leishmaniasis (VL) is a fatal disease caused by sandfly-borne protozoa of the Leishmania genus. This study explored the influence of environmental factors on the distribution of VL in Sinkiang province, Mainland China, which is a known natural focus of leishmaniasis. Disease identification records were obtained from publicly available data, in which the existence of VL at each geographical location had been recorded as part of the surveillance of leishmaniasis in Sinkiang province. Maximum entropy modelling (Maxent) was used to predict the distribution of VL across Sinkiang province, and to match this distribution against environmental variables relating to elevation, climate and land cover, obtained from the WorldClim database, China Meteorological Data Sharing System and the National Geomatic Center of China dataset, respectively. Finally, a regional-scale map was developed to show the potential distribution of VL in the Sinkiang province. Receiver-Operating characteristic (ROC) analysis was used to evaluate the performance of the model. The daily average temperature, maximum temperature of the warmest quarter, daily precipitation and precipitation of the driest month were each found to be predictive of the distribution of VL in Sinkiang. Moreover, we found that presence of VL was significantly influenced by the distribution of grassland and shrubland. The results demonstrate that with proper construction and design, probability surfaces using Maxent can be used as an accurate method by which to predict the distribution of VL in Sinkiang province. The information generated by the model could be used to inform the design of detailed prevention and control strategies for leishmaniasis in this region of Mainland China. Graphical abstract Unlabelled Image Highlights • Meteorological factors and land cover may affect the distribution of VL. • Jackknife method was used to measure the importance of risk variables. • Temperature and precipitation affect the distribution of VL in Sinkiang province. • Distribution of VL has been found high in grassland and shrubland area. • A risk forecast map was built based on the results of MaxEnt model. [ABSTRACT FROM AUTHOR]