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Modeling the COVID-19 Epidemic With Multi-Population and Control Strategies in the United States

As of January 19, 2021, the cumulative number of people infected with coronavirus disease-2019 (COVID-19) in the United States has reached 24,433,486, and the number is still rising. The outbreak of the COVID-19 epidemic has not only affected the development of the global economy but also seriously...

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Detalles Bibliográficos
Autores principales: Sun, Deshun, Long, Xiaojun, Liu, Jingxiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8761816/
https://www.ncbi.nlm.nih.gov/pubmed/35047470
http://dx.doi.org/10.3389/fpubh.2021.751940
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author Sun, Deshun
Long, Xiaojun
Liu, Jingxiang
author_facet Sun, Deshun
Long, Xiaojun
Liu, Jingxiang
author_sort Sun, Deshun
collection PubMed
description As of January 19, 2021, the cumulative number of people infected with coronavirus disease-2019 (COVID-19) in the United States has reached 24,433,486, and the number is still rising. The outbreak of the COVID-19 epidemic has not only affected the development of the global economy but also seriously threatened the lives and health of human beings around the world. According to the transmission characteristics of COVID-19 in the population, this study established a theoretical differential equation mathematical model, estimated model parameters through epidemiological data, obtained accurate mathematical models, and adopted global sensitivity analysis methods to screen sensitive parameters that significantly affect the development of the epidemic. Based on the established precise mathematical model, we calculate the basic reproductive number of the epidemic, evaluate the transmission capacity of the COVID-19 epidemic, and predict the development trend of the epidemic. By analyzing the sensitivity of parameters and finding sensitive parameters, we can provide effective control strategies for epidemic prevention and control. After appropriate modifications, the model can also be used for mathematical modeling of epidemics in other countries or other infectious diseases.
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spelling pubmed-87618162022-01-18 Modeling the COVID-19 Epidemic With Multi-Population and Control Strategies in the United States Sun, Deshun Long, Xiaojun Liu, Jingxiang Front Public Health Public Health As of January 19, 2021, the cumulative number of people infected with coronavirus disease-2019 (COVID-19) in the United States has reached 24,433,486, and the number is still rising. The outbreak of the COVID-19 epidemic has not only affected the development of the global economy but also seriously threatened the lives and health of human beings around the world. According to the transmission characteristics of COVID-19 in the population, this study established a theoretical differential equation mathematical model, estimated model parameters through epidemiological data, obtained accurate mathematical models, and adopted global sensitivity analysis methods to screen sensitive parameters that significantly affect the development of the epidemic. Based on the established precise mathematical model, we calculate the basic reproductive number of the epidemic, evaluate the transmission capacity of the COVID-19 epidemic, and predict the development trend of the epidemic. By analyzing the sensitivity of parameters and finding sensitive parameters, we can provide effective control strategies for epidemic prevention and control. After appropriate modifications, the model can also be used for mathematical modeling of epidemics in other countries or other infectious diseases. Frontiers Media S.A. 2022-01-03 /pmc/articles/PMC8761816/ /pubmed/35047470 http://dx.doi.org/10.3389/fpubh.2021.751940 Text en Copyright © 2022 Sun, Long and Liu. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Public Health
Sun, Deshun
Long, Xiaojun
Liu, Jingxiang
Modeling the COVID-19 Epidemic With Multi-Population and Control Strategies in the United States
title Modeling the COVID-19 Epidemic With Multi-Population and Control Strategies in the United States
title_full Modeling the COVID-19 Epidemic With Multi-Population and Control Strategies in the United States
title_fullStr Modeling the COVID-19 Epidemic With Multi-Population and Control Strategies in the United States
title_full_unstemmed Modeling the COVID-19 Epidemic With Multi-Population and Control Strategies in the United States
title_short Modeling the COVID-19 Epidemic With Multi-Population and Control Strategies in the United States
title_sort modeling the covid-19 epidemic with multi-population and control strategies in the united states
topic Public Health
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8761816/
https://www.ncbi.nlm.nih.gov/pubmed/35047470
http://dx.doi.org/10.3389/fpubh.2021.751940
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