Development of the second version of Global Prediction System for Epidemiological Pandemic  

作　　者：Jianping Huang Li Zhang Bin Chen Xiaoyue Liu Wei Yan Yingjie Zhao Siyu Chen Xinbo Lian Chuwei Liu Rui Wang Shuoyuan Gao Danfeng Wang 

机构地区：[1]Collaborative Innovation Center for Western Ecological Safety,Lanzhou University,Lanzhou 730000,China [2]College of Atmospheric Sciences,Lanzhou University,Lanzhou 730000,China

出　　处：《Fundamental Research》2024年第3期516-526,共11页自然科学基础研究（英文版）

基　　金：the Collaborative Research Project of the National Natural Science Foundation of China(L2224041);the Chinese Academy of Sciences(XK2022DXC005);Frontier of Interdisciplinary Research on Monitoring and Prediction of Pathogenic Microorganisms in the Atmosphere,Self-supporting Program of Guangzhou Laboratory(SRPG22–007);Gansu Province Intellectual Property Program(Oriented Organization)Project(22ZSCQD02).

摘　　要：Coronavirus disease 2019(COvID-19)is a severe global public health emergency that has caused a major cri-sis in the safety of human life,health,global economy,and social order.Moreover,CovID-19 poses significant challenges to healthcare systems worldwide.The prediction and early warning of infectious diseases on a global scale are the premise and basis for countries to jointly fight epidemics.However,because of the complexity of epidemics,predicting infectious diseases on a global scale faces significant challenges.In this study,we developed the second version of Global Prediction System for Epidemiological Pandemic(GPEP-2),which combines statis-tical methods with a modified epidemiological model.The GPEP-2 introduces various parameterization schemes for both impacts of natural factors(seasonal variations in weather and environmental impacts)and human so-cial behaviors(government control and isolation,personnel gathered,indoor propagation,virus mutation,and vaccination).The GPEP-2 successfully predicted the COVID-19 pandemic in over 180 countries with an average accuracy rate of 82.7%.It also provided prediction and decision-making bases for several regional-scale CovID-19 pandemic outbreaks in China,with an average accuracy rate of 89.3%.Results showed that both anthropogenic and natural factors can affect virus spread and control measures in the early stages of an epidemic can effectively control the spread.The predicted results could serve as a reference for public health planning and policymaking.

关 键 词：COVID-19 Epidemiological model Prediction GPEP SEIR Statistical-dynamic 

分 类 号：R181.3[医药卫生—流行病学]