Environmental Risk Factors and Geographic Distribution of Severe Fever with Thrombocytopenia Syndrome in Jiangsu Province, China

Abstract

Severe fever with thrombocytopenia syndrome (SFTS) is an emerging natural focus, tick-borne disease caused by a novel bunyavirus named SFTS virus (SFTSV). The main purpose of this study was to analyze the environmental risk factors and geographic distribution of SFTS natural foci in Jiangsu Province. A retrospective space-time analysis by SaTScan software was used to detect clusters at the town level. The maximum entropy modeling method was applied to construct the ecological niche model and analyze the environmental risk factors, and then to draw the predicted risk map. The performance of the model was assessed using the area under the curve (AUC) and known occurrence locations. During the years 2010-2016, a total of 140 laboratory-confirmed indigenous SFTS cases occurred in Jiangsu Province, with 66 occurrence locations. The reported number of SFTS cases increased year by year and SFTS cases occurred from April to October with a peak between May and August each year. Three clusters detected by space-time scan statistical analysis were connected together and shared the similar ecological environmental characteristic of hilly landscape. Fifteen environmental variables with different percent contribution can influence the ecological niche model in different degrees, whereas slope (suitable range: 0.1-4) and maximum temperature of warmest month (suitable range: 32.8-34.2°C) as the key environmental factors contributed 46.1% and 23.2%, respectively. The model had high accuracy on prediction with the averaged training AUC of 0.926. Within a predicted risk map, potential areas at high risk and 10 previously unidentified endemic regions were recognized. The distribution of SFTS natural foci was under the influence of multidimensional environmental factors. Slope and maximum temperature of warmest month were the key environmental risk factors. These results provide a valuable basis for the selection of prevention and control strategies, and the identification of potential risk areas.