Exploring Impacts to COVID-19 Herd Immunity Thresholds Under Demographic Heterogeneity that Lowers Vaccine Effectiveness.
Exploring Impacts to COVID-19 Herd Immunity Thresholds Under Demographic Heterogeneity that Lowers Vaccine Effectiveness.
复制标题
探索人口异质性降低疫苗有效性对 COVID-19 群体免疫阈值的影响。
DOI：
10.1101/2022.07.18.22277763
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发表时间：
2022
期刊：
影响因子：
--
通讯作者：
DelValle,SaraY
中科院分区：
文献类型：
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作者：
Paris,ChloéFlore;Spencer,JulieAllison;Castro,LaurenA;DelValle,SaraY
新冠肺炎大流行在全球范围内造成了严重的健康、经济和社会影响。尽管以前所未有的速度开发出了高效疫苗，但接种人群的异质性降低了实现群体免疫的能力。具体地说，截至2022年春季，0-4岁人口仍然无法接种疫苗，5-11岁儿童的疫苗接种率很低。此外，老年人群对疫苗的犹豫不决进一步阻碍了达到群体免疫阈值的努力。这种不同种类的疫苗格局增加了预测疾病在人群中传播的挑战。我们建立了一个年龄结构的易感-感染-恢复型数学模型来研究未接种疫苗的亚群对群体免疫的影响。该模型考虑了两种类型的疫苗接种不足--年龄相关和行为相关--根据FDA批准的现有疫苗纳入了四个年龄组。该模型考虑了两种不同类型的疫苗，即信使核糖核酸(如辉瑞、莫德纳)和载体疫苗(如强生和强生)，以及它们的有效性。我们的目标是以新墨西哥州为例，分析不同的情景，以量化哪些亚群和疫苗特征(例如，比率或效力)对美国的感染水平影响最大。
The COVID-19 pandemic has caused severe health, economic, and societal impacts across the globe. Although highly efficacious vaccines were developed at an unprecedented rate, the heterogeneity in vaccinated populations has reduced the ability to achieve herd immunity. Specifically, as of Spring 2022, the 0–4 year-old population is still unable to be vaccinated and vaccination rates across 5–11 year olds are low. Additionally, vaccine hesitancy for older populations has further stalled efforts to reach herd immunity thresholds. This heterogeneous vaccine landscape increases the challenge of anticipating disease spread in a population. We developed an age-structured Susceptible-Infectious-Recovered-type mathematical model to investigate the impacts of unvaccinated subpopulations on herd immunity. The model considers two types of undervaccination - age-related and behavior-related - by incorporating four age groups based on available FDA-approved vaccines. The model accounts for two different types of vaccines, mRNA (e.g., Pfizer, Moderna) and vector (e.g., Johnson and Johnson), as well as their effectiveness. Our goal is to analyze different scenarios to quantify which subpopulations and vaccine characteristics (e.g., rate or efficacy) most impact infection levels in the United States, using the state of New Mexico as an example.