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参与式数学建模方法在 COVID-19 危机第一年的决策中的应用,约旦。

Participatory Mathematical Modeling Approach for Policymaking during the First Year of the COVID-19 Crisis, Jordan.

出版信息

Emerg Infect Dis. 2023 Sep;29(9):1738-1746. doi: 10.3201/eid2909.221493.

Abstract

We engaged in a participatory modeling approach with health sector stakeholders in Jordan to support government decision-making regarding implementing public health measures to mitigate COVID-19 disease burden. We considered the effect of 4 physical distancing strategies on reducing COVID-19 transmission and mortality in Jordan during March 2020-January 2021: no physical distancing; intermittent physical distancing where all but essential services are closed once a week; intermittent physical distancing where all but essential services are closed twice a week; and a permanent physical distancing intervention. Modeling showed that the fourth strategy would be most effective in reducing cases and deaths; however, this approach was only marginally beneficial to reducing COVID-19 disease compared with an intermittently enforced physical distancing intervention. Scenario-based model influenced policy-making and the evolution of the pandemic in Jordan confirmed the forecasting provided by the modeling exercise and helped confirm the effectiveness of the policy adopted by the government of Jordan.

摘要

我们与约旦卫生部门利益相关者一起采用参与式建模方法,为政府在实施减轻 COVID-19 疾病负担的公共卫生措施方面提供决策支持。我们考虑了在 2020 年 3 月至 2021 年 1 月期间,4 种物理隔离策略对减少约旦 COVID-19 传播和死亡的影响:无物理隔离;间歇性物理隔离,每周关闭一次所有非必要服务;间歇性物理隔离,每周关闭两次所有非必要服务;以及永久性物理隔离干预。建模结果表明,第四种策略在减少病例和死亡方面最为有效;然而,与间歇性执行的物理隔离干预相比,这种方法对减少 COVID-19 疾病的影响只是略有优势。基于情景的模型影响了政策制定,约旦大流行的演变证实了模型演练提供的预测,并有助于确认约旦政府所采取政策的有效性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6f90/10461658/9e9cee559c55/22-1493-F1.jpg

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