Zheng J X, Xia S, Lü S, Zhang Y, Zhou X N
National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research); NHC Key Laboratory of Parasite and Vector Biology; WHO Collaborating Centre for Tropical Diseases; National Center for International Research on Tropical Diseases, Shanghai 200025, China.
Zhongguo Xue Xi Chong Bing Fang Zhi Za Zhi. 2021 Apr 16;33(2):133-137. doi: 10.16250/j.32.1374.2020253.
To create a model based on meteorological data to predict the regions at risk of schistosomiasis during the flood season, so as to provide insights into the surveillance and forecast of schistosomiasis.
An interactive schistosomiasis forecast system was created using the open-access R software. The schistosomiasis risk index was used as a basic parameter, and the species distribution model of snails was generated according to the cumulative rainfall and temperature to predict the probability of snail distribution, so as to identify the regions at risk of schistosomiasis transmission during the flood season.
The framework of the web page was built using the Shiny package in the R program, and an interactive and visualization system was successfully created to predict the distribution of snails, containing snail surveillance site database, meteorological and environmental data. In this system, the snail distribution area may be displayed and the regions at risk of schistosomiasis transmission may be predicted using the species distribution model. This predictive system may rapidly generate the schistosomiasis transmission risk map, which is simple and easy to perform. In addition, the regions at risk of schistosomiasis transmission were predicted to be concentrated in the middle and lower reaches of the Yangtze River during the flood period.
A schistosomiasis forecast system is successfully created, which is accurate and rapid to utilize meteorological data to predict the regions at risk of schistosomiasis transmission during the flood period.
基于气象数据创建一个模型，以预测汛期血吸虫病的风险区域，从而为血吸虫病的监测和预报提供见解。
使用开源的R软件创建了一个交互式血吸虫病预测系统。将血吸虫病风险指数作为基本参数，根据累计降雨量和温度生成钉螺的物种分布模型，以预测钉螺分布的概率，从而确定汛期血吸虫病传播的风险区域。
使用R程序中的Shiny包构建了网页框架，成功创建了一个交互式可视化系统来预测钉螺的分布，该系统包含钉螺监测站点数据库、气象和环境数据。在这个系统中，可以显示钉螺分布区域，并使用物种分布模型预测血吸虫病传播的风险区域。这个预测系统可以快速生成血吸虫病传播风险图，操作简单易行。此外，预计汛期血吸虫病传播的风险区域集中在长江中下游地区。
成功创建了一个血吸虫病预测系统，该系统利用气象数据准确、快速地预测汛期血吸虫病传播的风险区域。
