Effectiveness of Social Measures against COVID-19 Outbreaks in Selected Japanese Regions Analyzed by System Dynamic Modeling.
Effectiveness of Social Measures against COVID-19 Outbreaks in Selected Japanese Regions Analyzed by System Dynamic Modeling.
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DOI：
10.3390/ijerph17176238
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发表时间：
2020-08-27
影响因子：
--
通讯作者：
Kodama K
中科院分区：
文献类型：
--
作者：
Niwa M;Hara Y;Sengoku S;Kodama K
在日本应对2019冠状病毒病（COVID-19）时，由于能力有限，病毒检测仅限于有症状的患者，导致感染传播和对策是否适当的不确定性。系统动态模型由种群流量和感染模型组成，用于描述区域人口动态并估计假设的特定区域传播率。然后将估计的区域传播率与整个干预过程中的实际患者数据进行映射。该模型与模拟研究一起证明了入境旅客检疫和居民自我隔离政策和做法的有效性。采用因果循环方法将社会因素与感染控制措施联系起来。这种因果循环模型表明，在日本背景下，防止 COVID-19 传播的唯一有效措施是国家和地方政府在疫情爆发的早期阶段进行干预，并且没有表现出社会自我强化的动力。这些发现可能有助于了解如何发展社会对未来传染病威胁的抵御能力。
In Japan’s response to the coronavirus disease 2019 (COVID-19), virus testing was limited to symptomatic patients due to limited capacity, resulting in uncertainty regarding the spread of infection and the appropriateness of countermeasures. System dynamic modelling, comprised of stock flow and infection modelling, was used to describe regional population dynamics and estimate assumed region-specific transmission rates. The estimated regional transmission rates were then mapped against actual patient data throughout the course of the interventions. This modelling, together with simulation studies, demonstrated the effectiveness of inbound traveler quarantine and resident self-isolation policies and practices. A causal loop approach was taken to link societal factors to infection control measures. This causal loop modelling suggested that the only effective measure against COVID-19 transmission in the Japanese context was intervention in the early stages of the outbreak by national and regional governments, and no social self-strengthening dynamics were demonstrated. These findings may contribute to an understanding of how social resilience to future infectious disease threats can be developed.
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影响因子：
4.5
作者：
Maharaj S;Kleczkowski A
通讯作者：
Kleczkowski A
DOI：
10.1073/pnas.2004064117
发表时间：
2020-04-21
影响因子：
11.1
作者：
Moghadas, Seyed M.;Shoukat, Affan;Galvani, Alison P.
通讯作者：
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影响因子：
3.1
作者：
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通讯作者：
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影响因子：
5.2
作者：
Chen, H-J.;Xue, H.;Wang, Y.
通讯作者：
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影响因子：
4.7
作者：
Gerli, Alberto G.;Centanni, Stefano;Soriano, Joan B.
通讯作者：
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