tetano
Editor, Senior Moderator
BMJ Glob Health
. 2020 May;5(5):e002647.
doi: 10.1136/bmjgh-2020-002647.
The Potential Effects of Widespread Community Transmission of SARS-CoV-2 Infection in the World Health Organization African Region: A Predictive Model
Joseph Waogodo Cabore[SUP] 1 [/SUP], Humphrey Cyprian Karamagi[SUP] 2 [/SUP], Hillary Kipruto[SUP] 3 [/SUP], James Avoka Asamani[SUP] 3 [/SUP], Benson Droti[SUP] 4 [/SUP], Aminata Binetou Wahebine Seydi[SUP] 5 [/SUP], Regina Titi-Ofei[SUP] 5 [/SUP], Benido Impouma[SUP] 6 [/SUP], Michel Yao[SUP] 6 [/SUP], Zabulon Yoti[SUP] 6 [/SUP], Felicitas Zawaira[SUP] 7 [/SUP], Prosper Tumusiime[SUP] 4 [/SUP], Ambrose Talisuna[SUP] 6 [/SUP], Francis Chisaka Kasolo[SUP] 8 [/SUP], Matshidiso R Moeti[SUP] 9 [/SUP]
Affiliations
Abstract
The spread of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has been unprecedented in its speed and effects. Interruption of its transmission to prevent widespread community transmission is critical because its effects go beyond the number of COVID-19 cases and deaths and affect the health system capacity to provide other essential services. Highlighting the implications of such a situation, the predictions presented here are derived using a Markov chain model, with the transition states and country specific probabilities derived based on currently available knowledge. A risk of exposure, and vulnerability index are used to make the probabilities country specific. The results predict a high risk of exposure in states of small size, together with Algeria, South Africa and Cameroon. Nigeria will have the largest number of infections, followed by Algeria and South Africa. Mauritania would have the fewest cases, followed by Seychelles and Eritrea. Per capita, Mauritius, Seychelles and Equatorial Guinea would have the highest proportion of their population affected, while Niger, Mauritania and Chad would have the lowest. Of the World Health Organization's 1 billion population in Africa, 22% (16%-26%) will be infected in the first year, with 37 (29 - 44) million symptomatic cases and 150 078 (82 735-189 579) deaths. There will be an estimated 4.6 (3.6-5.5) million COVID-19 hospitalisations, of which 139 521 (81 876-167 044) would be severe cases requiring oxygen, and 89 043 (52 253-106 599) critical cases requiring breathing support. The needed mitigation measures would significantly strain health system capacities, particularly for secondary and tertiary services, while many cases may pass undetected in primary care facilities due to weak diagnostic capacity and non-specific symptoms. The effect of avoiding widespread and sustained community transmission of SARS-CoV-2 is significant, and most likely outweighs any costs of preventing such a scenario. Effective containment measures should be promoted in all countries to best manage the COVID-19 pandemic.
Keywords: epidemiology; health systems; mathematical modelling.
. 2020 May;5(5):e002647.
doi: 10.1136/bmjgh-2020-002647.
The Potential Effects of Widespread Community Transmission of SARS-CoV-2 Infection in the World Health Organization African Region: A Predictive Model
Joseph Waogodo Cabore[SUP] 1 [/SUP], Humphrey Cyprian Karamagi[SUP] 2 [/SUP], Hillary Kipruto[SUP] 3 [/SUP], James Avoka Asamani[SUP] 3 [/SUP], Benson Droti[SUP] 4 [/SUP], Aminata Binetou Wahebine Seydi[SUP] 5 [/SUP], Regina Titi-Ofei[SUP] 5 [/SUP], Benido Impouma[SUP] 6 [/SUP], Michel Yao[SUP] 6 [/SUP], Zabulon Yoti[SUP] 6 [/SUP], Felicitas Zawaira[SUP] 7 [/SUP], Prosper Tumusiime[SUP] 4 [/SUP], Ambrose Talisuna[SUP] 6 [/SUP], Francis Chisaka Kasolo[SUP] 8 [/SUP], Matshidiso R Moeti[SUP] 9 [/SUP]
Affiliations
- PMID: 32451366
- DOI: 10.1136/bmjgh-2020-002647
Abstract
The spread of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has been unprecedented in its speed and effects. Interruption of its transmission to prevent widespread community transmission is critical because its effects go beyond the number of COVID-19 cases and deaths and affect the health system capacity to provide other essential services. Highlighting the implications of such a situation, the predictions presented here are derived using a Markov chain model, with the transition states and country specific probabilities derived based on currently available knowledge. A risk of exposure, and vulnerability index are used to make the probabilities country specific. The results predict a high risk of exposure in states of small size, together with Algeria, South Africa and Cameroon. Nigeria will have the largest number of infections, followed by Algeria and South Africa. Mauritania would have the fewest cases, followed by Seychelles and Eritrea. Per capita, Mauritius, Seychelles and Equatorial Guinea would have the highest proportion of their population affected, while Niger, Mauritania and Chad would have the lowest. Of the World Health Organization's 1 billion population in Africa, 22% (16%-26%) will be infected in the first year, with 37 (29 - 44) million symptomatic cases and 150 078 (82 735-189 579) deaths. There will be an estimated 4.6 (3.6-5.5) million COVID-19 hospitalisations, of which 139 521 (81 876-167 044) would be severe cases requiring oxygen, and 89 043 (52 253-106 599) critical cases requiring breathing support. The needed mitigation measures would significantly strain health system capacities, particularly for secondary and tertiary services, while many cases may pass undetected in primary care facilities due to weak diagnostic capacity and non-specific symptoms. The effect of avoiding widespread and sustained community transmission of SARS-CoV-2 is significant, and most likely outweighs any costs of preventing such a scenario. Effective containment measures should be promoted in all countries to best manage the COVID-19 pandemic.
Keywords: epidemiology; health systems; mathematical modelling.