Estimating local outbreak risks and the effects of non-pharmaceutical interventions in age-structured populations: SARS-CoV-2 as a case study.
Estimating local outbreak risks and the effects of non-pharmaceutical interventions in age-structured populations: SARS-CoV-2 as a case study.
复制标题
估计当地暴发风险和非药物干预对年龄结构人群的影响：以SARS-CoV-2为例。
DOI：
10.1016/j.jtbi.2021.110983
复制
发表时间：
2022-02-21
影响因子：
2
通讯作者：
Thompson RN
中科院分区：
文献类型：
--
作者：
Lovell-Read FA;Shen S;Thompson RN
分支过程爆发模型可以扩展到包括年龄依赖因素。传入病例引发疫情的风险取决于该病例的年龄。干预措施的有效性取决于所针对的年龄组。减少接触干预措施的组合可以减轻爆发风险。有效的病例发现减少了对全民干预的需要。在COVID-19大流行期间，世界各地均采取非药物干预措施（NPI），包括关闭学校、关闭工作场所及社交距离政策，以减少传播及预防局部疫情。然而，NPI的传播和有效性在很大程度上取决于年龄相关因素，包括接触模式和病理生理学的异质性。在这里，使用SARS-CoV-2作为案例研究，我们开发了一个分支过程模型，用于评估传染病病例到达一个新的地点将引发当地疫情的风险，考虑到宿主人群的年龄分布。我们发现，局部爆发的风险取决于指数病例的年龄，我们探讨了针对不同年龄个体的NPI的影响。减少学校和工作场所以外接触并针对所有年龄段的个人的社交距离政策预计将大幅降低当地疫情风险，而关闭学校的影响则较为有限。在这里考虑的情况下，当不同的NPI组合使用时，可以消除局部爆发的风险。我们还表明，加强对传染性个体的监测，降低了预防局部疫情所需的NPI水平，特别是如果加强对有症状病例的监测，并努力发现和隔离无症状的感染者。我们的结果反映了COVID-19大流行的真实世界经验，在此期间，密集的NPI组合降低了传播和局部爆发的风险。我们提出的一般建模框架可用于估计一系列病原体未来流行期间的局部暴发风险，充分考虑与年龄相关的因素。
Branching process outbreak models can be extended to include age-dependent factors. The risk that an introduced case initiates an outbreak depends on that case’s age. The effectiveness of interventions depends on the age groups that are targeted. Combinations of contact-reducing interventions can mitigate the outbreak risk. Effective case detection reduces the need for population-wide interventions. During the COVID-19 pandemic, non-pharmaceutical interventions (NPIs) including school closures, workplace closures and social distancing policies have been employed worldwide to reduce transmission and prevent local outbreaks. However, transmission and the effectiveness of NPIs depend strongly on age-related factors including heterogeneities in contact patterns and pathophysiology. Here, using SARS-CoV-2 as a case study, we develop a branching process model for assessing the risk that an infectious case arriving in a new location will initiate a local outbreak, accounting for the age distribution of the host population. We show that the risk of a local outbreak depends on the age of the index case, and we explore the effects of NPIs targeting individuals of different ages. Social distancing policies that reduce contacts outside of schools and workplaces and target individuals of all ages are predicted to reduce local outbreak risks substantially, whereas school closures have a more limited impact. In the scenarios considered here, when different NPIs are used in combination the risk of local outbreaks can be eliminated. We also show that heightened surveillance of infectious individuals reduces the level of NPIs required to prevent local outbreaks, particularly if enhanced surveillance of symptomatic cases is combined with efforts to find and isolate nonsymptomatic infected individuals. Our results reflect real-world experience of the COVID-19 pandemic, during which combinations of intense NPIs have reduced transmission and the risk of local outbreaks. The general modelling framework that we present can be used to estimate local outbreak risks during future epidemics of a range of pathogens, accounting fully for age-related factors.
登录
查看更多内容
影响因子：
16.6
作者：
Huang QS;Wood T;Jelley L;Jennings T;Jefferies S;Daniells K;Nesdale A;Dowell T;Turner N;Campbell-Stokes P;Balm M;Dobinson HC;Grant CC;James S;Aminisani N;Ralston J;Gunn W;Bocacao J;Danielewicz J;Moncrieff T;McNeill A;Lopez L;Waite B;Kiedrzynski T;Schrader H;Gray R;Cook K;Currin D;Engelbrecht C;Tapurau W;Emmerton L;Martin M;Baker MG;Taylor S;Trenholme A;Wong C;Lawrence S;McArthur C;Stanley A;Roberts S;Rahnama F;Bennett J;Mansell C;Dilcher M;Werno A;Grant J;van der Linden A;Youngblood B;Thomas PG;NPIsImpactOnFlu Consortium;Webby RJ
通讯作者：
Webby RJ
DOI：
10.1098/rspb.2013.1037
发表时间：
2013-08-22
期刊：
Proceedings. Biological sciences
影响因子：
--
作者：
Danon L;Read JM;House TA;Vernon MC;Keeling MJ
通讯作者：
Keeling MJ
DOI：
10.1093/infdis/jiaa691
发表时间：
2021-02-13
期刊：
The Journal of infectious diseases
影响因子：
--
作者：
Goldstein E;Lipsitch M;Cevik M
通讯作者：
Cevik M
影响因子：
11.8
作者：
Borse, Rebekah H.;Behravesh, Casey Barton;Meltzer, Martin I.
通讯作者：
Meltzer, Martin I.
影响因子：
11.8
作者：
Bullard, Jared;Dust, Kerry;Poliquin, Guillaume
通讯作者：
Poliquin, Guillaume