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ORIGINAL RESEARCH article
Front. Public Health
Sec. Infectious Diseases: Epidemiology and Prevention
Volume 12 - 2024 |
doi: 10.3389/fpubh.2024.1449305
This article is part of the Research Topic Novel Interventions for the Prevention and Control of Communicable Disease View all 10 articles
Effectiveness of a Scenario-based, Community-based Intervention in Containing COVID-19 in China
Provisionally accepted- 1 Weifang People's Hospital, Weifang, Shandong Province, China
- 2 Shandong Second Medical University, Weifang, China
- 3 School of Population Medicine and Public Health, Peking Union Medical College Hospital (CAMS), Dongcheng, Beijing, China
Background: Given the significant impact of the more than three-year-long COVID-19 pandemic on people's health, social order, and economic performance, as well as the potential re-emergence of a new variant and the epidemic "Disease X," it is crucial to examine its developmental trends and suggest countermeasures to address community epidemics of severe respiratory infectious diseases.: The epidemiological characterization of various strains of COVID-19 was modeled using an improved Susceptible-Exposed-Infectious-Recovered (SEIR) model to simulate the infections of different strains of COVID-19 under different scenarios, taking as an example an urban area of a prefecture-level city in Shandong Province, China, with a resident population of 2 million. Scenarios 1-5 are scenario-based simulations the Omicron strain, and 6-8 simulate the original COVID-19 strain, with different parameters for each scenario. Scenarios 1 and 6 do not consider community NPIs and represent natural epidemic scenarios. Scenarios 2-4 assess the impact of different NPIs on the original COVID-19 strain. Scenarios 1-4 and 6-8 compare the effects of the same measures on different strains. Scenario 5 simulates the effects of implementing NPIs after an outbreak has spread widely. Compare scenarios 4 and 9 to analyze the effect of high grades versus dynamic
Keywords: pandemic COVID-19, infectious disease dynamics modeling, non-pharmacological interventions, measure effects, Scenario-based
Received: 14 Jun 2024; Accepted: 06 Nov 2024.
Copyright: © 2024 li, Zhou, Zhang, Ma and Hao. 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) or licensor 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.
* Correspondence:
Wenhao Hao, Weifang People's Hospital, Weifang, 261000, Shandong Province, China
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