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战略性疫苗储备以应对新兴病毒的区域性流行:一个地理空间建模框架。

Strategic vaccine stockpiles for regional epidemics of emerging viruses: A geospatial modeling framework.

机构信息

Department of Biology, Georgetown University; Department of Epidemiology of Microbial Diseases, Yale University School of Public Health.

Department of Biology, Georgetown University.

出版信息

Vaccine. 2024 Oct 3;42(23):126051. doi: 10.1016/j.vaccine.2024.06.019. Epub 2024 Jun 19.

DOI:10.1016/j.vaccine.2024.06.019
PMID:38902187
Abstract

Multinational epidemics of emerging infectious diseases are increasingly common, due to anthropogenic pressure on ecosystems and the growing connectivity of human populations. Early and efficient vaccination can contain outbreaks and prevent mass mortality, but optimal vaccine stockpiling strategies are dependent on pathogen characteristics, reservoir ecology, and epidemic dynamics. Here, we model major regional outbreaks of Nipah virus and Middle East respiratory syndrome, and use these to develop a generalized framework for estimating vaccine stockpile needs based on spillover geography, spatially-heterogeneous healthcare capacity and spatially-distributed human mobility networks. Because outbreak sizes were highly skewed, we found that most outbreaks were readily contained (median stockpile estimate for MERS-CoV: 2,089 doses; Nipah: 1,882 doses), but the maximum estimated stockpile need in a highly unlikely large outbreak scenario was 2-3 orders of magnitude higher (MERS-CoV: ∼87,000 doses; Nipah ∼ 1.1 million doses). Sensitivity analysis revealed that stockpile needs were more dependent on basic epidemiological parameters (i.e., death and recovery rate) and healthcare availability than any uncertainty related to vaccine efficacy or deployment strategy. Our results highlight the value of descriptive epidemiology for real-world modeling applications, and suggest that stockpile allocation should consider ecological, epidemiological, and social dimensions of risk.

摘要

由于人类对生态系统的压力和人口流动的日益增加,新兴传染病的跨国流行越来越常见。早期和有效的疫苗接种可以控制疫情爆发并防止大量死亡,但最佳的疫苗储备策略取决于病原体特征、储存生态和疫情动态。在这里,我们对尼帕病毒和中东呼吸综合征的主要区域性爆发进行建模,并利用这些模型开发了一种基于溢出地理、空间异质医疗保健能力和空间分布人类流动网络的估计疫苗储备需求的通用框架。由于爆发规模高度偏斜,我们发现大多数爆发都很容易得到控制(MERS-CoV 的中位储备估计:2089 剂;尼帕病毒:1882 剂),但在极不可能的大规模爆发情况下,最大估计储备需求要高出 2-3 个数量级(MERS-CoV:约 87000 剂;尼帕病毒约 110 万剂)。敏感性分析表明,储备需求更多地取决于基本的流行病学参数(即死亡率和恢复率)以及医疗保健的可及性,而不是疫苗效力或部署策略方面的任何不确定性。我们的研究结果强调了描述性流行病学在现实世界建模应用中的价值,并表明储备分配应考虑风险的生态、流行病学和社会维度。

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