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优化 COVID-19 疫苗接种和高接触人群的作用:基于模型的方法。

Optimization of COVID-19 vaccination and the role of individuals with a high number of contacts: A model based approach.

机构信息

International Center for Condensed Matter Physics, Universidade de Brasília, Brasília, DF, Brazil.

Instituto de Física, Universidade de Brasília, Brasília, DF, Brazil.

出版信息

PLoS One. 2022 Mar 8;17(3):e0262433. doi: 10.1371/journal.pone.0262433. eCollection 2022.

DOI:10.1371/journal.pone.0262433
PMID:35259169
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8903293/
Abstract

We report strong evidence of the importance of contact hubs (or superspreaders) in mitigating the current COVID-19 pandemic. Contact hubs have a much larger number of contacts than the average in the population, and play a key role on the effectiveness of vaccination strategies. By using an age-structures compartmental SEIAHRV (Susceptible, Exposed, Infected symptomatic, Asymptomatic, Hospitalized, Recovered, Vaccinated) model, calibrated from available demographic and COVID-19 incidence, and considering separately those individuals with a much greater number of contacts than the average in the population, we show that carefully choosing who will compose the first group to be vaccinated can impact positively the total death toll and the demand for health services. This is even more relevant in countries with a lack of basic resources for proper vaccination and a significant reduction in social isolation. In order to demonstrate our approach we show the effect of hypothetical vaccination scenarios in two countries of very different scales and mitigation policies, Brazil and Portugal.

摘要

我们有强有力的证据表明接触枢纽(或超级传播者)在减轻当前 COVID-19 大流行方面的重要性。接触枢纽的接触者比人群中的平均水平多得多,并且在疫苗接种策略的有效性方面发挥着关键作用。通过使用年龄结构的 SEIAHRV(易感、暴露、感染症状、无症状、住院、康复、接种)模型,根据可用的人口统计和 COVID-19 发病率进行校准,并分别考虑那些接触者比人群中的平均水平多得多的个体,我们表明,精心选择哪些人将组成第一批接种疫苗的人,可以对总死亡人数和对卫生服务的需求产生积极影响。在缺乏适当疫苗接种基本资源和社会隔离显著减少的国家,这一点更为重要。为了证明我们的方法,我们展示了在两个规模和缓解政策非常不同的国家(巴西和葡萄牙)中假设的疫苗接种情况的影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c6d/8903293/91bf924d5857/pone.0262433.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c6d/8903293/b797de69c5e5/pone.0262433.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c6d/8903293/b15ae5cb090b/pone.0262433.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c6d/8903293/0d0f9e447044/pone.0262433.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c6d/8903293/91bf924d5857/pone.0262433.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c6d/8903293/b797de69c5e5/pone.0262433.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c6d/8903293/b15ae5cb090b/pone.0262433.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c6d/8903293/0d0f9e447044/pone.0262433.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c6d/8903293/91bf924d5857/pone.0262433.g004.jpg

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