Zhaohui Du1, Zhiqiang Wang2, Yunxia Liu1, Hao Wang1, Fuzhong Xue1, Yanxun Liu3. 1. Department of Epidemiology and Biostatistics, School of Public Health, Shandong University, PO Box 100, 44 West Wenhua Road, Jinan 250012, Shandong, China. 2. Shandong Center for Disease Control and Prevention, Jinan, Shandong, China. 3. Department of Epidemiology and Biostatistics, School of Public Health, Shandong University, PO Box 100, 44 West Wenhua Road, Jinan 250012, Shandong, China. Electronic address: liu-yx@sdu.edu.cn.
Abstract
BACKGROUND: Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease caused by a novel bunyavirus. The spatial distribution has continued to expand, while the areas at potential high risk of SFTS have, to date, remained unclear. METHODS: Using ecological factors as predictors, the MaxEnt model was first trained based on the locations of human SFTS occurrence in Shandong Province. The risk prediction map of China was then created by projecting the training model onto the whole country. The performance of the model was assessed using the known locations of disease occurrence in China. RESULTS: The key environmental factors affecting SFTS occurrence were temperature, precipitation, land cover, normalized difference vegetation index (NDVI), and duration of sunshine. The risk prediction maps suggested that central, southwestern, northeastern, and the eastern coast of China are potential areas at high risk of SFTS. CONCLUSIONS: The potential high risk SFTS areas are distributed widely in China. The epidemiological surveillance system should be enhanced in these high risk regions.
BACKGROUND: Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease caused by a novel bunyavirus. The spatial distribution has continued to expand, while the areas at potential high risk of SFTS have, to date, remained unclear. METHODS: Using ecological factors as predictors, the MaxEnt model was first trained based on the locations of human SFTS occurrence in Shandong Province. The risk prediction map of China was then created by projecting the training model onto the whole country. The performance of the model was assessed using the known locations of disease occurrence in China. RESULTS: The key environmental factors affecting SFTS occurrence were temperature, precipitation, land cover, normalized difference vegetation index (NDVI), and duration of sunshine. The risk prediction maps suggested that central, southwestern, northeastern, and the eastern coast of China are potential areas at high risk of SFTS. CONCLUSIONS: The potential high risk SFTS areas are distributed widely in China. The epidemiological surveillance system should be enhanced in these high risk regions.
Authors: Tarcísio Visintin da Silva Galdino; Sunil Kumar; Leonardo S S Oliveira; Acelino C Alfenas; Lisa G Neven; Abdullah M Al-Sadi; Marcelo C Picanço Journal: PLoS One Date: 2016-07-14 Impact factor: 3.240