Pandemic burden in low-income settings and impact of limited and delayed interventions: a granular modelling analysis of COVID-19 in Kabwe, Zambia.

Pandemic response in low-income countries or settings (LICs) 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. 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 wildtype, Beta and Delta variants. 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 healthcare to similar capacity as 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, conversely, 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, respectively, upper-middle-, lower-middle-, or LICs. Robust quantitative analyses of pandemic data are of pressing need to inform global pandemic preparedness commitments going forward.

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Declaration of interests This work was supported by the Medical Research Council (MRC) Centre for Global Infectious Disease Analysis (grant number MR/R015600/1); this award is jointly funded by the MRC and Foreign, Commonwealth and Development Office (FCDO) under the MRC/FCDO Concordat agreement, and is also part of the European and Developing Countries Clinical Trials Partnership programme (EDCTP2) supported by the EU. Serology data collection conducted by Zambart was also supported by the EDCTP2 programme. PNPG is funded by Imperial College President's PhD and MRC Pump-Priming funds. MB, ESK and AC are funded by the National Institute for Health and Care Research (NIHR) Health Protection Research Unit in Modelling and Health Economics, a partnership between the UK Health Security Agency, Imperial College London and LSHTM (grant code NIHR200908). The views expressed are those of the authors and not necessarily those of the funders, which had no involvement in the study design, data analysis, interpretation of results, or any aspects related to the drafting and submission of this manuscript. PNPG, KH, and AC have previously consulted for Pfizer, including technical modelling advise on COVID-19, although neither this nor any other private company had any involvement in the present study. All other authors declare no conflicts of interest.