ArticlePloS one2023
Improving social resilience amid the COVID-19 epidemic: A system dynamics model.
Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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2 authors.
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Abstract
Social resilience is a key factor in disaster management, but compared to resilience in other fields, research on social resilience is still limited to assessment or evaluation, and there is still a lack of dynamic and procedural research, which is also a challenge. This article constructs a causal feedback model and a system dynamics model of social resilience during the COVID-19 epidemic, so as to analyze the dynamic characteristics and improvement path of social resilience. After verifying the effectiveness of the model, model simulation is conducted and the following important conclusions are drawn: social resilience dynamically changes during the research cycle and is influenced by social entity behavior and social mechanisms; The sensitivity factors for the two variables that measure social resilience, namely panic degree and damage degree, are the real-time information acquisition of public and the epidemic awareness of local government, respectively. Therefore, the path to enhancing social resilience should be pursued from both the public and government perspectives, including improving the public's ability to access real-time information, increasing the timeline of government information disclosure, and enhancing local governments' understanding and awareness of the epidemic.
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