Department of Epidemiology and Biostatistics, School of Public Health, Shandong University, PO Box 100, 44 West Wenhua Road, Jinan 250012, Shandong, China.
Shandong Center for Disease Control and Prevention, Jinan, Shandong, China.
Int J Infect Dis. 2014 Sep;26:1-8. doi: 10.1016/j.ijid.2014.04.006. Epub 2014 Jun 27.
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.
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.
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.
The potential high risk SFTS areas are distributed widely in China. The epidemiological surveillance system should be enhanced in these high risk regions.
严重发热伴血小板减少综合征（SFTS）是一种由新型布尼亚病毒引起的新发传染病。其空间分布不断扩大，然而，SFTS 的潜在高风险地区迄今仍不清楚。
利用生态因素作为预测因子，首先基于山东省人类 SFTS 发生地点对最大熵模型进行训练。然后，通过将训练模型投影到全国范围，创建中国的风险预测图。通过中国疾病发生的已知地点来评估模型的性能。
影响 SFTS 发生的关键环境因素包括温度、降水、土地覆盖、归一化差异植被指数（NDVI）和日照时间。风险预测图表明，中国中部、西南部、东北部和东海岸是 SFTS 潜在的高风险地区。
中国存在广泛分布的 SFTS 潜在高风险地区。应在这些高风险地区加强流行病学监测系统。
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