The spatio-temporal epidemic dynamics of COVID-19 outbreak in Africa

Gayawan, Ezra, Awe, Olushina O, Oseni, Bamidele M., Uzochukwu, Ikemefuna C., Adekunle, Adeshina, Samuel, Gbemisola, Eisen, Damon P., and Adegboye, Oyelola A. (2020) The spatio-temporal epidemic dynamics of COVID-19 outbreak in Africa. Epidemiology and Infection, 148. e212.

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Abstract

Corona virus disease 2019 (COVID-19), caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was first detected in the city of Wuhan, China in December 2019. Although, the disease appeared in Africa later than other regions, it has now spread to virtually all countries on the continent. We provide early spatio-temporal dynamics of COVID-19 within the first 62 days of the disease's appearance on the African continent. We used a two-parameter hurdle Poisson model to simultaneously analyse the zero counts and the frequency of occurrence. We investigate the effects of important healthcare capacities including hospital beds and number of medical doctors in different countries. The results show that cases of the pandemic vary geographically across Africa with notably high incidence in neighbouring countries particularly in West and North Africa. The burden of the disease (per 100 000) mostly impacted Djibouti, Tunisia, Morocco and Algeria. Temporally, during the first 4 weeks, the burden was highest in Senegal, Egypt and Mauritania, but by mid-April it shifted to Somalia, Chad, Guinea, Tanzania, Gabon, Sudan and Zimbabwe. Currently, Namibia, Angola, South Sudan, Burundi and Uganda have the least burden. These findings could be useful in guiding epidemiological interventions and the allocation of scarce resources based on heterogeneity of the disease patterns.

Item ID: 64271
Item Type: Article (Research - C1)
ISSN: 1469-4409
Copyright Information: © The Author(s), 2020. Published by Cambridge University Press. This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Date Deposited: 07 Sep 2020 21:29
FoR Codes: 49 MATHEMATICAL SCIENCES > 4905 Statistics > 490502 Biostatistics @ 50%
42 HEALTH SCIENCES > 4202 Epidemiology > 420205 Epidemiological modelling @ 50%
SEO Codes: 92 HEALTH > 9201 Clinical Health (Organs, Diseases and Abnormal Conditions) > 920109 Infectious Diseases @ 100%
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