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考虑社会特征优化疫苗接种活动策略。

Optimizing vaccination campaign strategies considering societal characteristics.

作者信息

Lee Serin, Zabinsky Zelda B, Liu Shan

机构信息

Department of Industrial & Systems Engineering, University of Washington, Seattle, Washington, US.

出版信息

Health Care Manag Sci. 2025 Mar;28(1):84-98. doi: 10.1007/s10729-025-09696-9. Epub 2025 Feb 10.

Abstract

Vaccine hesitancy continues to be a public health challenge. This study explores the dynamic interplay between disease transmission, evolving vaccination opinions, and targeted vaccination campaigns. Using a numerical experiment calibrated to the COVID-19 epidemic in King County, WA, during 2023, we optimize vaccination campaigns across various demographics. Our findings suggest that vaccination campaigns are most effective in societies with medium vaccine hesitancy, with optimal outcomes achieved by focusing on the 18-34 age group in the most densely populated regions. In societies with low hesitancy, campaigns may be unnecessary, and resources should target rural areas and the 0-17 age range to maximize impact. In high hesitancy societies, campaigns are ineffective. In such cases, efforts should focus on reducing vaccine risk perceptions. This research advances the understanding of dynamic behavioral responses to vaccination campaigns through evolutionary game theory, moving beyond models that assume static vaccination behavior. By employing a demographic-based networked compartmental model, it derives actionable and interpretable campaign strategies, providing valuable guidance for real-world implementation.

摘要

疫苗犹豫仍然是一项公共卫生挑战。本研究探讨了疾病传播、不断演变的疫苗接种观点和有针对性的疫苗接种活动之间的动态相互作用。通过一项针对2023年华盛顿州金县新冠疫情进行校准的数值实验,我们对不同人口群体的疫苗接种活动进行了优化。我们的研究结果表明,疫苗接种活动在疫苗犹豫程度中等的社会中最为有效,通过关注人口最密集地区的18 - 34岁年龄组可实现最佳效果。在疫苗犹豫程度低的社会中,开展活动可能没有必要,资源应针对农村地区和0 - 17岁年龄范围以实现最大影响。在疫苗犹豫程度高的社会中,活动是无效的。在这种情况下,应致力于降低对疫苗风险的认知。本研究通过进化博弈论推进了对疫苗接种活动动态行为反应的理解,超越了假设疫苗接种行为静态的模型。通过采用基于人口的网络分区模型,它得出了可操作且可解释的活动策略,为实际实施提供了有价值的指导。

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