Pandemic burden in low-income settings and impact of limited and delayed interventions: a granular modelling analysis of COVID-19 in Kabwe, Zambia
File(s)
Published version
Author(s)
Type
Journal Article
Abstract
Objectives
Pandemic response in low-income countries (LICs) or settings often suffers from scarce epidemic surveillance and constrained mitigation capacity. The drivers of pandemic burden in such settings, and the impact of limited and delayed interventions remain poorly understood.
Methods
We analysed COVID-19 seroprevalence and all-cause excess deaths data from the peri-urban district of Kabwe, Zambia between March 2020 and September 2021 with a novel mathematical model. Data encompassed three consecutive waves caused by the wild-type, Beta and Delta variants.
Results
Across all three waves, we estimated a high cumulative attack rate, with 78% (95% credible interval [CrI] 71-85) of the population infected, and a high all-cause excess mortality, at 402 (95% CrI 277-473) deaths per 100,000 people. Ambitiously improving health care to a capacity similar to that in high-income settings could have averted up to 46% (95% CrI 41-53) of accrued excess deaths, if implemented from June 2020 onward. An early and accelerated vaccination rollout could have achieved the highest reductions in deaths. Had vaccination started as in some high-income settings in December 2020 and with the same daily capacity (doses per 100 population), up to 68% (95% CrI 64-71) of accrued excess deaths could have been averted. Slower rollouts would have still averted 62% (95% CrI 58-68), 54% (95% CrI 49-61) or 26% (95% CrI 20-38) of excess deaths if matching the average vaccination capacity of upper-middle-, lower-middle- or LICs, respectively.
Conclusions
Robust quantitative analyses of pandemic data are of pressing need to inform future global pandemic preparedness commitments.
Pandemic response in low-income countries (LICs) or settings often suffers from scarce epidemic surveillance and constrained mitigation capacity. The drivers of pandemic burden in such settings, and the impact of limited and delayed interventions remain poorly understood.
Methods
We analysed COVID-19 seroprevalence and all-cause excess deaths data from the peri-urban district of Kabwe, Zambia between March 2020 and September 2021 with a novel mathematical model. Data encompassed three consecutive waves caused by the wild-type, Beta and Delta variants.
Results
Across all three waves, we estimated a high cumulative attack rate, with 78% (95% credible interval [CrI] 71-85) of the population infected, and a high all-cause excess mortality, at 402 (95% CrI 277-473) deaths per 100,000 people. Ambitiously improving health care to a capacity similar to that in high-income settings could have averted up to 46% (95% CrI 41-53) of accrued excess deaths, if implemented from June 2020 onward. An early and accelerated vaccination rollout could have achieved the highest reductions in deaths. Had vaccination started as in some high-income settings in December 2020 and with the same daily capacity (doses per 100 population), up to 68% (95% CrI 64-71) of accrued excess deaths could have been averted. Slower rollouts would have still averted 62% (95% CrI 58-68), 54% (95% CrI 49-61) or 26% (95% CrI 20-38) of excess deaths if matching the average vaccination capacity of upper-middle-, lower-middle- or LICs, respectively.
Conclusions
Robust quantitative analyses of pandemic data are of pressing need to inform future global pandemic preparedness commitments.
Date Issued
2024-10
Date Acceptance
2024-07-15
Citation
International Journal of Infectious Diseases, 2024, 147
ISSN
1201-9712
Publisher
Elsevier
Journal / Book Title
International Journal of Infectious Diseases
Volume
147
Copyright Statement
© 2024 The Author(s). Published by Elsevier Ltd on behalf of International Society for Infectious
Diseases.
This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)
Diseases.
This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)
License URL
Identifier
https://www.sciencedirect.com/science/article/pii/S1201971224002534
Publication Status
Published
Article Number
107182
Date Publish Online
2024-07-26