Modeling Transmission Dynamics and Risk Assessment for COVID-19 in Namibia Using Geospatial Technologies

Springer Science and Business Media LLC - Tập 6 - Trang 377-394 - 2021
Kedir Mohammed Bushira1, Jacob Otieno Ongala2
1Department of Civil and Environmental Engineering, Namibia University of Science and Technology (NUST), Windhoek, Namibia
2Department of Mathematics and Statistics, Namibia University of Science and Technology (NUST), Windhoek, Namibia

Tóm tắt

The SARS-CoV-2 infections continue to increase in Namibia and globally. Assessing and mapping the COVID-19 risk zones and modeling the response of COVID-19 using different scenarios are very vital to help decision-makers to estimate the immediate number of resources needed and plan for future interventions of COVID-19 in the area of interest. This study is aimed to identify and map COVID-19 risk zones and to model future COVID-19 response of Namibia using geospatial technologies. Population density, current COVID-19 infections, and spatial interaction index were used as proxy data to identify the different COVID-19 risk zones of Namibia. COVID-19 Hospital Impact Model for Epidemics (CHIME) V1.1.5 tool was used to model future COVID-19 responses with mobility restrictions. Weights were assigned for each thematic layer and thematic layer classes using the Analytical Hierarchy Process (AHP) tool. Suitably ArcGIS overlay analysis was conducted to produce risk zones. Current COVID-19 infection and spatial mobility index were found to be the dominant and sensitive factors for risk zoning in Namibia. Six different COVID-19 risk zones were identified in the study area, namely highest, higher, high, low, lower, and lowest. Modeling result revealed that mobility reduction by 30% within the country had a notable effect on controlling COVID-19 spread: a flattening of the peak number of cases and delay to the peak number. The research output could help policy-makers to estimate the immediate number of resources needed and plan for future interventions of COVID-19 in Namibia, especially to assess the potential positive effects of mobility restriction.

Tài liệu tham khảo

An G, Jia F (2020) Analysis of the economic impact of the NCP and countermeasure study. Financ Theor Pract 3:45–51 Centers for Disease Control and Prevention. Coronavirus disease 2019 (COVID-19) in the U.S. [cited 21 Feb 2020]. www.cdc.gov/coronavirus/2019-ncov/cases-in-us.html Champion T, Fotheringham S, Rees P, Boyle P, Stillwell J (1998) The determinants of migration flows in England: a review of existing data and evidence. Report prepared for the Department of the Environment, Transport and the Regions. The Department of Geography, University of Newcastle upon Tyne, Newcastle upon Tyne, UK, pp 31–128, ISBN 0-902155-39-3 Ekumah B, Armah FA, Yawson DO, Quansah R, Nyieku FE, Owusu SA, Odoi JO, Afitiri AR (2020) Disparate on-site access to water, sanitation, and food storage heighten the risk of COVID-19 spread in Sub-Saharan Africa. Environ Res 189:109936. https://doi.org/10.1016/j.envres.2020.109936 Flaxman S, Mishra S, Gandy A, Unwin HJT, Coupland H, Mellan TA, et al (2020) Imperial College COVID-19 Response Team. Report 13: estimating the number of infections and the impact of non-pharmaceutical interventions on COVID-19 in 11 European countries [Cited 20 Mar 2020]. https://www.imperial.ac.uk/media/imperial-college/medicine/sph/ide/gida-fellowships/Imperial-College-COVID19-Europe-estimates-and-NPI-impact-30-03-2020.pdfExternalLink Fotheringham AS, Webber MJ (1980) Spatial structure and the parameters of spatial interaction models. Geogr Anal 12:33–46 Franch-Pardo I, Napoletano BM, Rosete-Verges F, Billa L (2020) Spatial analysis and GIS in the study of COVID-19. A review. Sci Total Environ 739:140033. https://doi.org/10.1016/j.scitotenv.2020.140033 Giovanetti M, Benvenuto D, Angeletti S, Ciccozzi M (2020) The frst two cases of 2019-nCoV in Italy: where they come from? J Med Virol. https://doi.org/10.1002/jmv.25699 Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, Xu J (2020) Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet 395:405–506 Kraemer MUG, Yang C-H, Gutierrez B, Wu C-H, Klein B, Pigott DM, et al (2020) Open COVID-19 Data Working Group .The effect of human mobility and control measures on the COVID-19 epidemic in China. Science (Epub ahead of print) Prem K, Liu Y, Russell TW, Kucharski AJ, Eggo RM, Davies N, et al (2020) Centre for the Mathematical Modelling of Infectious Diseases COVID-19 Working Group The effect of control strategies to reduce social mixing on outcomes of the COVID-19 epidemic in Wuhan, China: a modelling study. Lancet Publ Health (Epub ahead of print) Rasheed Z, Stepansky J, Najjar F (2020). Tracking Africa's coronavirus cases. https://www.aljazeera.com/news/2020/04/tracking-africa-coronavirus-cases-200401081427251.html Republic of Namibia (2020) Guidelines for stage 2 under state of emergency—Presidential Statement, Windhoek Rogers A (2008) Demographic modeling of the geography of migration and population: a multiregional. Perspect Geogr Anal 40:276–296 Rothe C, Schunk M, Sothmann P, Bretzel G, Froeschl G, Wallrauch C et al (2020) Transmission of 2019-nCoV infection from an asymptomatic contact in Germany. N Engl J Med 382:970–971. https://doi.org/10.1056/NEJMc2001468 Sarfo AK, Karuppannan S (2020) Application of geospatial technologies in the COVID-19 fight of Ghana. Trans Indian Natl Acad Eng 0123456789:1–12. https://doi.org/10.1007/s41403-020-00145-3 Satty T (1995) Decision making for leaders, 3rd edn. RWS, Pittsburgh Smith SK, Tayman J, Swanson DA (2001) State and Local Population Projections: Methodology and Analysis. Kluwer, Norwell, pp 97–136 (ISBN 0-306-46493-4) COVID-19 response CHIME Model v1.1.5 manual, 2020, Version 4—Updated 5/11/2020, The Trustees of the University of Pennsylvania Tuite AR, Fisman DN, Greer AL (2020) Mathematical modelling of COVID-19 transmission and mitigation strategies in the population of Ontario, Canada. CMAJ (Epub ahead of print) Turner BL (2002) Contested identities: human-environment geography and disciplinary implications in a restructuring academy. Ann Assoc Am Geogr 92(1):52–74 Weisstein EW (2019) “SIR Model.” from MathWorld—a Wolfram web resource. https://mathworld.wolfram.com/SIRModel.html WHO (2020) Operational considerations for case management of COVID-19 in health facility and community, interim guidance, 19 March 2020. https://www.who.int/publications/i/item/operational-considerations-for-case-management-of-covid-19-in-health-facility-and-community) Wondim YK, Alemayehu EB, Abebe WB (2017) Malaria Hazard and risk mapping using GIS based spatial multicriteria evaluation technique (SMCET) in Tekeze Basin Development Corridor, Amhara Region, Ethiopia. J Environ Earth Sci 7(5):76–87 World Health Organization. Novel coronavirus—China [cited 2020 Jan 12]. https://www.who.int/csr/don/12-january-2020-novel-coronavirus-china Worldometer (2020) Worldometer COVID-19 data [cited 10 August 2020]. https://www.worldometers.info/coronavirus/country/namibia/ Wu JT, Leung K, Leung GM (2020) Nowcasting and forecasting the potential domestic and international spread of the 2019-nCoV outbreak originating in Wuhan, China: a modelling study. Lancet 395:689–697 Xie Z, Qin Y, Li Y, Shen W, Zheng Z, Liu S (2020) Spatial and temporal differentiation of COVID-19 epidemic spread in mainland China and its influencing factors. Sci Total Environ 744:140929. https://doi.org/10.1016/j.scitotenv.2020.140929 Zhao X, Li X, Nie C (2020) Backtracking transmission of COVID-19 in China based on big data source, and effect of strict pandemic control policy. Bull Chin Acad Sci 35(3):248–255