A study on the control strategies of COVID-19 based on household model

Ruohong Liu

doi:10.1117/12.2648627

27 September 2022 A study on the control strategies of COVID-19 based on household model

Ruohong Liu

Proceedings Volume 12345, International Conference on Applied Statistics, Computational Mathematics, and Software Engineering (ASCMSE 2022); 123451N (2022) https://doi.org/10.1117/12.2648627
Event: 2022 International Conference on Applied Statistics, Computational Mathematics, and Software Engineering (ASCMSE 2022), 2022, Qingdao, China

Abstract

COVID-19 disease, a new infectious disease that has emerged in recent years, poses a serious threat to humans. In this paper, a household epidemiological model was used to study the spread of COVID-19 in the community, using the viral load-based household model of infectious diseases proposed by Becker, combined with the chain binomial model, to derive the household reproduction number. The results of the sensitivity analysis showed that isolation and antiviral treatment were effective in controlling the spread of the disease; hospital isolation was more effective than home isolation in controlling the spread of the COVID-19 disease in the community; and the earlier the isolation, the more effective the prevention, suggesting that when faced with a serious outbreak of infectious disease, The rapid response of the government to ensure adequate health resources can effectively reduce the number of infections in households and effectively contained the rapid spread of the epidemic. The analysis of antiviral drugs shows that timely treatment of infected individuals with antiviral drugs is an effective way to control outbreaks, and that delayed use of antiviral drugs can lead to a reduction in the effectiveness of isolation measures. Therefore, researchers should accelerate their research to develop targeted antiviral drugs as soon as possible.

Citation Download Citation

Ruohong Liu "A study on the control strategies of COVID-19 based on household model", Proc. SPIE 12345, International Conference on Applied Statistics, Computational Mathematics, and Software Engineering (ASCMSE 2022), 123451N (27 September 2022); https://doi.org/10.1117/12.2648627

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