Zou Lu-Xi, Sun Ling
School of Management, Zhejiang University, Hangzhou, China.
Department of Nephrology, Xuzhou Central Hospital, The Xuzhou School of Clinical Medicine of Nanjing Medical University, Xuzhou, China.
Front Public Health. 2020 Dec 1;8:571984. doi: 10.3389/fpubh.2020.571984. eCollection 2020.
Hemorrhagic fever with renal syndrome (HFRS) is a life-threatening public health problem in China, accounting for ~90% of HFRS cases reported globally. Accurate analysis and prediction of the HFRS epidemic could help to establish effective preventive measures. In this study, the geographical information system (GIS) explored the spatiotemporal features of HFRS, the wavelet power spectrum (WPS) unfolded the cyclical fluctuation of HFRS, and the wavelet neural network (WNN) model predicted the trends of HFRS outbreaks in mainland China. A total of 209,209 HFRS cases were reported in mainland China from 2004 to 2019, with the annual incidence ranged from 0 to 13.05 per 100,0000 persons at the province level. The WPS proved that the periodicity of HFRS could be half a year, 1 year, and roughly 7-year at different time intervals. The WNN structure of 12-6-1 was set up as the fittest forecasting model for the HFRS epidemic. This study provided several potential support tools for the control and risk-management of HFRS in China.
肾综合征出血热(HFRS)在中国是一个危及生命的公共卫生问题,约占全球报告的HFRS病例的90%。准确分析和预测HFRS疫情有助于制定有效的预防措施。在本研究中,地理信息系统(GIS)探索了HFRS的时空特征,小波功率谱(WPS)揭示了HFRS的周期性波动,小波神经网络(WNN)模型预测了中国大陆HFRS疫情的爆发趋势。2004年至2019年中国大陆共报告HFRS病例209,209例,省级层面的年发病率为每100,000人0至13.05例。WPS证明,在不同时间间隔下,HFRS的周期可能为半年、1年和大约7年。将12-6-1的WNN结构设置为HFRS疫情最合适的预测模型。本研究为中国HFRS的控制和风险管理提供了几种潜在的支持工具。