A Multiobjective Optimization Model for Prevention and Control of Coronavirus Disease 2019 in China | Zendy

LI Xiao-cheng | Zendy; Liu Zhao-li | Zendy; Fangzhen Ge | Zendy

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A Multiobjective Optimization Model for Prevention and Control of Coronavirus Disease 2019 in China

Author(s) -

LI Xiao-cheng,

Liu Zhao-li,

Fangzhen Ge

Publication year - 2022

Publication title -

discrete dynamics in nature and society

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.264

H-Index - 39

eISSN - 1607-887X

pISSN - 1026-0226

DOI - 10.1155/2022/6329601

Subject(s) - covid-19 , china , disease control , cluster analysis , computer science , epidemic model , set (abstract data type) , infectious disease (medical specialty) , geography , virology , disease , medicine , environmental health , outbreak , artificial intelligence , population , archaeology , pathology , programming language

It is a global issue to set up a practical, sensitive, and useful model to eradicate or mitigate the coronavirus disease 2019 (COVID-19). Taking Central China’s Hubei Province for example, three models were established. Firstly, a susceptible-probable-infectious-recovered (SPIR) model was proposed to predict the monthly number of confirmed and susceptible cases in each city. Next, an epidemic prefecture clustering model was set up to find proper vaccine delivery sites, according to the distance of each city. Finally, a dynamic material delivery optimization model was established for multiple epidemic prefectures, aiming to speed up vaccine production and storage in each delivery site.

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