Indirect effects of the COVID-19 pandemic on malaria intervention coverage, morbidity, and mortality in Africa: a geospatial modelling analysis

Abstract

Background: Substantial progress has been made in reducing the burden of malaria in Africa since 2000, but those gains could be jeopardised if the COVID-19 pandemic affects the availability of key malaria control interventions. The aim of this study was to evaluate plausible effects on malaria incidence and mortality under different levels of disruption to malaria control.

Methods: Using an established set of spatiotemporal Bayesian geostatistical models, we generated geospatial estimates across malaria-endemic African countries of the clinical case incidence and mortality of malaria, incorporating an updated database of parasite rate surveys, insecticide-treated net (ITN) coverage, and effective treatment rates. We established a baseline estimate for the anticipated malaria burden in Africa in the absence of COVID-19-related disruptions, and repeated the analysis for nine hypothetical scenarios in which effective treatment with an antimalarial drug and distribution of ITNs (both through routine channels and mass campaigns) were reduced to varying extents.

Findings: We estimated 215·2 (95% uncertainty interval 143·7-311·6) million cases and 386·4 (307·8-497·8) thousand deaths across malaria-endemic African countries in 2020 in our baseline scenario of undisrupted intervention coverage. With greater reductions in access to effective antimalarial drug treatment, our model predicted increasing numbers of cases and deaths: 224·1 (148·7-326·8) million cases and 487·9 (385·3-634·6) thousand deaths with a 25% reduction in antimalarial drug coverage; 233·1 (153·7-342·5) million cases and 597·4 (468·0-784·4) thousand deaths with a 50% reduction; and 242·3 (158·7-358·8) million cases and 715·2 (556·4-947·9) thousand deaths with a 75% reduction. Halting planned 2020 ITN mass distribution campaigns and reducing routine ITN distributions by 25%-75% also increased malaria burden to a total of 230·5 (151·6-343·3) million cases and 411·7 (322·8-545·5) thousand deaths with a 25% reduction; 232·8 (152·3-345·9) million cases and 415·5 (324·3-549·4) thousand deaths with a 50% reduction; and 234·0 (152·9-348·4) million cases and 417·6 (325·5-553·1) thousand deaths with a 75% reduction. When ITN coverage and antimalarial drug coverage were synchronously reduced, malaria burden increased to 240·5 (156·5-358·2) million cases and 520·9 (404·1-691·9) thousand deaths with a 25% reduction; 251·0 (162·2-377·0) million cases and 640·2 (492·0-856·7) thousand deaths with a 50% reduction; and 261·6 (167·7-396·8) million cases and 768·6 (586·1-1038·7) thousand deaths with a 75% reduction.

Interpretation: Under pessimistic scenarios, COVID-19-related disruption to malaria control in Africa could almost double malaria mortality in 2020, and potentially lead to even greater increases in subsequent years. To avoid a reversal of two decades of progress against malaria, averting this public health disaster must remain an integrated priority alongside the response to COVID-19.

Funding: Bill and Melinda Gates Foundation; Channel 7 Telethon Trust, Western Australia.

Figure 1

Simplified methodological flow chart Orange rectangles represent input datasets, some of which are modelled results from preceding analyses. Blue rectangles represent predefined process steps for which we supplied new data. Green rectangles are new conversions added to the production chain for this project. Purple rectangles are the results of the analysis. GBD=Global Burden of Disease Study. ITN=insecticide-treated net. PfPR=Plasmodium falciparum parasite rate. WMR=World Malaria Report.

Figure 2

Estimated effect of deteriorating malaria control in Africa For each of nine scenarios of disrupted intervention coverage (table), we estimated the resulting number of malaria cases (A) and deaths (C), and the relative increases in cases (B) and deaths (D). Percentage reductions are relative to the baseline scenario of undisrupted antimalarial drug treatment and ITN distribution (as delivered via mass campaign and routine distributions). Error bars are 95% uncertainty intervals. ITN=insecticide-treated net. *ITN reduction scenarios consist of cessation of all mass distribution campaigns in addition to a reduction in routine distribution by the percentage specified.

Figure 3

Estimated effects of a 75% reduction in malaria control in Africa by country Estimates are shown for scenario 9 (no mass distributions of insecticide-treated nets, and 75% reductions in routine insecticide-treated net distribution and antimalarial drug treatment, relative to undisrupted levels). Results are mapped for absolute increases in cases (A) and deaths (B), and relative increases in cases (C) and deaths (D). Countries shaded in grey were not included in the analysis.

Figure 4

Estimated effects of deteriorating malaria control by intervention type and disruption level for the 20 most affected countries Estimated increases in cases (A) and deaths (B) for each country given reductions of 25%, 50%, and 75% (vs undisrupted baseline levels) in ITN distribution and antimalarial drug treatment, separately and combined. Bars are cumulative such that bottom segment (lightest shading) represents a 25% reduction, the bottom two segment (light and intermediate shading) represent a 50% reduction, and the full height of the bar (light, intermediate, and dark shading) represent a 75% reduction. ITN=insecticide-treated net. *ITN reduction scenarios consist of cessation of all mass distribution campaigns in addition to a reduction in routine distribution by the percentage specified.

Figure 5

Effect of cancellation of mass distribution campaigns on ITN coverage Shown, for the 24 countries with scheduled mass campaigns in 2020, are estimated ITN coverage rates in two scenarios: one in which all 2020 mass and routine distribution campaigns continue as planned (the baseline scenario) and the other in which mass campaigns are cancelled, showing the difference in expected coverage rates due to the suspension of mass campaigns alone. Details of the size of the mass campaigns planned in 2020 for each country are shown in the appendix (p 1). BEN=Benin. CMR=Cameroon. CAF=Central African Republic. TCD=Chad. CIV=Côte d'Ivoire. COD=Democratic Republic of the Congo. ERI=Eritrea. ETH=Ethiopia. GNB=Guinea‐Bissau. ITN=insecticide-treated net. KEN=Kenya. MLI=Mali. MRT=Mauritania. MOZ=Mozambique. NER=Niger. NGA=Nigeria. RWA=Rwanda. SLE=Sierra Leone. SOM=Somalia. SSD=South Sudan. SDN=Sudan. TZA=Tanzania. TGO=Togo. UGA=Uganda. ZMB=Zambia.