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个体意见如何影响社会的防疫抵制:基于主体的模型方法。

How individuals' opinions influence society's resistance to epidemics: an agent-based model approach.

机构信息

School of Industrial Engineering, Purdue University, Grant St, West Lafayette, 47907, IN, USA.

Air Force Institute of Technology, Hobson Way, Wright-Patterson AFB, 45433, OH, USA.

出版信息

BMC Public Health. 2024 Mar 20;24(1):863. doi: 10.1186/s12889-024-18310-6.

Abstract

BACKGROUND

Protecting public health from infectious diseases often relies on the cooperation of citizens, especially when self-care interventions are the only viable tools for disease mitigation. Accordingly, social aspects related to public opinion have been studied in the context of the recent COVID-19 pandemic. However, a comprehensive understanding of the effects of opinion-related factors on disease spread still requires further exploration.

METHODS

We propose an agent-based simulation framework incorporating opinion dynamics within an epidemic model based on the assumption that mass media channels play a leading role in opinion dynamics. The model simulates how opinions about preventive interventions change over time and how these changes affect the cumulative number of cases. We calibrated our simulation model using YouGov survey data and WHO COVID-19 new cases data from 15 different countries. Based on the calibrated models, we examine how different opinion-related factors change the consequences of the epidemic. We track the number of total new infections for analysis.

RESULTS

Our results reveal that the initial level of public opinion on preventive interventions has the greatest impact on the cumulative number of cases. Its normalized permutation importance varies between 69.67% and 96.65% in 15 models. The patterns shown in the partial dependence plots indicate that other factors, such as the usage of the pro-intervention channel and the response time of media channels, can also bring about substantial changes in disease dynamics, but only within specific ranges of the dominant factor.

CONCLUSIONS

Our results reveal the importance of public opinion on intervention during the early stage of the pandemic in protecting public health. The findings suggest that persuading the public to take actions they may be hesitant about in the early stages of epidemics is very costly because taking early action is critical for mitigating infectious diseases. Other opinion-related factors can also lead to significant changes in epidemics, depending on the average level of public opinion in the initial stage. These findings underscore the importance of media channels and authorities in delivering accurate information and persuading community members to cooperate with public health policies.

摘要

背景

保护公众健康免受传染病的侵害通常依赖于公民的合作,尤其是在自我保健干预措施是减轻疾病的唯一可行手段的情况下。因此,在最近的 COVID-19 大流行背景下,已经研究了与公众舆论相关的社会方面。然而,要全面了解与舆论相关的因素对疾病传播的影响,仍需要进一步探索。

方法

我们提出了一个基于主体的模拟框架,该框架在基于假设大众媒体渠道在舆论动态中起主导作用的传染病模型中纳入了舆论动态。该模型模拟了关于预防干预措施的意见随时间的变化方式,以及这些变化如何影响病例的累计数量。我们使用 YouGov 调查数据和来自 15 个不同国家的世界卫生组织 COVID-19 新病例数据对我们的模拟模型进行了校准。基于校准模型,我们研究了不同的舆论相关因素如何改变疫情的后果。我们跟踪总新感染病例的数量进行分析。

结果

我们的结果表明,公众对预防干预措施的最初意见对病例的累计数量影响最大。在 15 个模型中,其归一化排列重要性在 69.67%至 96.65%之间变化。偏依赖图中的模式表明,其他因素,如亲干预渠道的使用和媒体渠道的响应时间,也可以带来疾病动态的实质性变化,但仅在主导因素的特定范围内。

结论

我们的研究结果揭示了在大流行早期保护公众健康时公众对干预措施的意见的重要性。研究结果表明,在传染病的早期阶段说服公众采取他们可能犹豫不决的行动是非常昂贵的,因为早期行动对于减轻传染病至关重要。其他与舆论相关的因素也会导致传染病的重大变化,这取决于初始阶段公众舆论的平均水平。这些发现强调了媒体渠道和当局在提供准确信息和说服社区成员与公共卫生政策合作方面的重要性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1ad4/10953238/9ec6d1370f9c/12889_2024_18310_Fig1_HTML.jpg

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