Using spatial and population mobility models to inform outbreak response approaches in the Ebola affected area, Democratic Republic of the Congo, 2018-2020

IF 2.1 Q3 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH Spatial and Spatio-Temporal Epidemiology Pub Date : 2023-02-01 DOI:10.1016/j.sste.2022.100558
Carmen Huber , Alexander Watts , Andrea Thomas-Bachli , Elvira McIntyre , Ashleigh Tuite , Kamran Khan , Martin Cetron , Rebecca D. Merrill
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Abstract

The Democratic Republic of the Congo's (DRC) 10th known Ebola virus disease (EVD) outbreak occurred between August 1, 2018 and June 25, 2020, and was the largest EVD outbreak in the country's history. During this outbreak, the DRC Ministry of Health initiated traveller health screening at points of control (POC, locations not on the border) and points of entry (POE) to minimize disease translocation via ground and air travel. We sought to develop a model-based approach that could be applied in future outbreaks to inform decisions for optimizing POC and POE placement, and allocation of resources more broadly, to mitigate the risk of disease translocation associated with ground-level population mobility. We applied a parameter-free mobility model, the radiation model, to estimate likelihood of ground travel between selected origin locations (including Beni, DRC) and surrounding population centres, based on population size and drive-time. We then performed a road network route analysis and included estimated population movement results to calculate the proportionate volume of travellers who would move along each road segment; this reflects the proportion of travellers that could be screened at a POC or POE. For Beni, the road segments estimated to have the highest proportion of travellers that could be screened were part of routes into Uganda and Rwanda. Conversely, road segments that were part of routes to other population centres within the DRC were estimated to have relatively lower proportions. We observed a posteriori that, in many instances, our results aligned with locations that were selected for actual POC or POE placement through more time-consuming methods. This study has demonstrated that mobility models and simple spatial techniques can help identify potential locations for health screening at newly placed POC or existing POE during public health emergencies based on expected movement patterns. Importantly, we have provided methods to estimate the proportionate volume of travellers that POC or POE screening measures would assess based on their location. This is critical information in outbreak situations when timely decisions must be made to implement public health interventions that reach the most individuals across a network.

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利用空间和人口流动模型为2018-2020年刚果民主共和国埃博拉疫区的疫情应对方法提供信息
刚果民主共和国(DRC)已知的第十次埃博拉病毒病(EVD)暴发发生在2018年8月1日至2020年6月25日之间,是该国历史上最大的埃博拉病毒病暴发。在本次疫情期间,刚果民主共和国卫生部在控制点(POC,不在边境的地点)和入境点(POE)启动了旅行者健康筛查,以尽量减少通过地面和空中旅行的疾病易位。我们试图开发一种基于模型的方法,可应用于未来的疫情,为优化POC和POE的放置以及更广泛的资源分配提供决策依据,以减轻与地面人口流动相关的疾病易位风险。我们应用了一个无参数流动模型,即辐射模型,根据人口规模和开车时间,估计选定的起源地点(包括贝尼,刚果民主共和国)和周围人口中心之间地面旅行的可能性。然后,我们进行了道路网络路线分析,并包括估计的人口移动结果,以计算沿每个路段移动的旅行者的比例;这反映了可在POC或POE进行筛查的旅客比例。对贝尼来说,据估计可进行筛查的旅客比例最高的路段是进入乌干达和卢旺达的部分路线。相反,作为通往刚果民主共和国境内其他人口中心路线一部分的路段估计所占比例相对较低。我们观察到,在许多情况下,我们的结果与通过更耗时的方法为实际POC或POE放置选择的位置一致。该研究表明,在突发公共卫生事件期间,流动模型和简单的空间技术可以根据预期的流动模式,帮助确定新安置的POC或现有POE的潜在健康筛查地点。重要的是,我们提供了估算旅客比例的方法,POC或POE筛查措施将根据他们的位置进行评估。在疫情暴发时,必须及时作出决定,实施公共卫生干预措施,使整个网络覆盖到大多数人,这是至关重要的信息。
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来源期刊
Spatial and Spatio-Temporal Epidemiology
Spatial and Spatio-Temporal Epidemiology PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH-
CiteScore
5.10
自引率
8.80%
发文量
63
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