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

被引:0
|
作者
Huber, Carmen [1 ,7 ]
Watts, Alexander [1 ]
Thomas-Bachli, Andrea [1 ]
McIntyre, Elvira [2 ,3 ]
Tuite, Ashleigh [1 ,4 ]
Khan, Kamran [1 ,5 ,6 ]
Cetron, Martin [2 ]
Merrill, Rebecca D. [2 ]
机构
[1] BlueDot, 207 Queens Quay West 820, Toronto, ON, Canada
[2] Natl Ctr Emerging & Zoonot Infect Dis, Div Global Migrat & Quarantine, Clifton Rd, Atlanta 1600, GA USA
[3] Perspecta Inc, 15052 Conf Ctr Dr, Chantilly, VA USA
[4] Univ Toronto, Dalla Lana Sch Publ Hlth, 155 Coll St, Toronto, ON, Canada
[5] St Michaels Hosp, Li Ka Shing Knowledge Inst, 38 Shuter St, Toronto, ON, Canada
[6] Univ Toronto, Dept Med, Div Infect Dis, 1 Kings Coll Circle, Toronto, ON, Canada
[7] BlueDot Inc, 207 Queens Quay W 801b, Toronto, ON M5J 1A7, Canada
关键词
Ebola virus disease; radiation model; road network analysis; resource allocation; population mobility; Democratic Republic of the Congo;
D O I
10.1016/j.sste.2022.100558
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
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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页数:11
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