After the outbreak of COVID-19,the interaction of infectious disease systems and social systems has challenged traditional infectious disease modeling methods.Starting from the research purpose and data,researchers im...After the outbreak of COVID-19,the interaction of infectious disease systems and social systems has challenged traditional infectious disease modeling methods.Starting from the research purpose and data,researchers im-proved the structure and data of the compartment model or used agents and artificial intelligence based models to solve epidemiological problems.In terms of modeling methods,the researchers use compartment subdivi-sion,dynamic parameters,agent-based model methods,and artificial intelligence related methods.In terms of factors studied,the researchers studied 6 categories:human mobility,nonpharmaceutical interventions(NPIs),ages,medical resources,human response,and vaccine.The researchers completed the study of factors through modeling methods to quantitatively analyze the impact of social systems and put forward their suggestions for the future transmission status of infectious diseases and prevention and control strategies.This review started with a research structure of research purpose,factor,data,model,and conclusion.Focusing on the post-COVID-19 infectious disease prediction simulation research,this study summarized various improvement methods and analyzes matching improvements for various specific research purposes.展开更多
基金We received project support and design guidance from National Key R&D Program of China(Grant No.2021ZD0111201)The Na-tional Natural Science Foundation of China(Grant Nos.82161148011,72171013)+2 种基金Conselho Nacional de Desenvolvimento Científico e Tec-nolgico(CNPq-Refs.441057/2020-9,309569/2019-2),CJS-CNPqFundação deAmparo a Pesquisa do Estado do Rio de Janeiro(FAPERJ)The Russian Foundation for basic Research,Project number 21-51-80000.
文摘After the outbreak of COVID-19,the interaction of infectious disease systems and social systems has challenged traditional infectious disease modeling methods.Starting from the research purpose and data,researchers im-proved the structure and data of the compartment model or used agents and artificial intelligence based models to solve epidemiological problems.In terms of modeling methods,the researchers use compartment subdivi-sion,dynamic parameters,agent-based model methods,and artificial intelligence related methods.In terms of factors studied,the researchers studied 6 categories:human mobility,nonpharmaceutical interventions(NPIs),ages,medical resources,human response,and vaccine.The researchers completed the study of factors through modeling methods to quantitatively analyze the impact of social systems and put forward their suggestions for the future transmission status of infectious diseases and prevention and control strategies.This review started with a research structure of research purpose,factor,data,model,and conclusion.Focusing on the post-COVID-19 infectious disease prediction simulation research,this study summarized various improvement methods and analyzes matching improvements for various specific research purposes.
