Modeling outbreaks of COVID-19 in China: The impact of vaccination and other control measures on curbing the epidemic
| Autor: | Wenting Zha, Han Ni, Yuxi He, Wentao Kuang, Jin Zhao, Liuyi Fu, Haoyun Dai, Yuan Lv, Nan Zhou, Xuewen Yang |
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| Jazyk: | angličtina |
| Rok vydání: | 2024 |
| Předmět: | |
| Zdroj: | Human Vaccines & Immunotherapeutics, Vol 20, Iss 1 (2024) |
| Druh dokumentu: | article |
| ISSN: | 21645515 2164-554X 2164-5515 |
| DOI: | 10.1080/21645515.2024.2338953 |
| Popis: | ABSTRACTThis study aims to examine the development trend of COVID-19 in China and propose a model to assess the impacts of various prevention and control measures in combating the COVID-19 pandemic. Using COVID-19 cases reported by the National Health Commission of China from January 2, 2020, to January 2, 2022, we established a Susceptible-Exposed-Infected-Asymptomatic-Quarantined-Vaccinated-Hospitalized-Removed (SEIAQVHR) model to calculate the COVID-19 transmission rate and Rt effective reproduction number, and assess prevention and control measures. Additionally, we built a stochastic model to explore the development of the COVID-19 epidemic. We modeled the incidence trends in five outbreaks between 2020 and 2022. Some important features of the COVID-19 epidemic are mirrored in the estimates based on our SEIAQVHR model. Our model indicates that an infected index case entering the community has a 50%–60% chance to cause a COVID-19 outbreak. Wearing masks and getting vaccinated were the most effective measures among all the prevention and control measures. Specifically targeting asymptomatic individuals had no significant impact on the spread of COVID-19. By adjusting prevention and control parameters, we suggest that increasing the rates of effective vaccination and mask-wearing can significantly reduce COVID-19 cases in China. Our stochastic model analysis provides a useful tool for understanding the COVID-19 epidemic in China. |
| Databáze: | Directory of Open Access Journals |
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