Abstract
Malaria transmission is influenced by climate, land use and deliberate interventions. Recent declines have been observed in malaria transmission. Here we show that the African continent has witnessed a long-term decline in the prevalence of Plasmodium falciparum from 40% prevalence in the period 1900–1929 to 24% prevalence in the period 2010–2015, a trend that has been interrupted by periods of rapidly increasing or decreasing transmission. The cycles and trend over the past 115 years are inconsistent with explanations in terms of climate or deliberate intervention alone. Previous global initiatives have had minor impacts on malaria transmission, and a historically unprecedented decline has been observed since 2000. However, there has been little change in the high transmission belt that covers large parts of West and Central Africa. Previous efforts to model the changing patterns of P. falciparum transmission intensity in Africa have been limited to the past 15 years1,2 or have used maps drawn from historical expert opinions3. We provide quantitative data, from 50,424 surveys at 36,966 geocoded locations, that covers 115 years of malaria history in sub-Saharan Africa; inferring from these data to future trends, we would expect continued reductions in malaria transmission, punctuated with resurgences.
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Acknowledgements
We thank Á. Munoz and M. Thompson for advice on long-term climate data; M. Coetzee and J. Hemmingway for details of emerging insecticide resistance; E. Okiro, M. English and D. Zurovac for comments on earlier drafts of the paper; and the individuals and institutions who have helped to assemble malaria data from across Africa over the past 21 years (see Supplementary Information 5). The present study was supported by the International Development Research Centre, Canada (1996–1998) and the Wellcome Trust, UK (1996–1997: 048335) through the Mapping Malaria Risk in Africa (MARA/ARMA) project, and the Wellcome Trust through the Malaria Atlas Project (MAP) in 2005 (034694) and funding to R.W.S. as part of his Principal Fellowship since 2007 (079080 and 103602). A.M.N. acknowledges support from the Wellcome Trust as an Intermediary Fellow (095127); R.W.S., D.K., J.M., P.A., C.W.M., P.B. and A.M.N. acknowledge the support of the Wellcome Trust for the Kenya Major Overseas Programme (077092 and 203077). R.W.S. is grateful to the Department for International Development (UK) for their support of Strengthening the Use of Data for Malaria Decision Making in Africa (DFID Programme Code 203155), which provided support to D.K. and J.M.
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R.W.S. assembled the data, designed the experiment and wrote the paper; B.S. undertook the statistical analysis; P.B. provided support for data interpretation; A.M.N. provided support for data assembly and analysis; and D.K., J.M., P.A. and C.W.M. all provided assistance in locating survey reports, abstraction of data and geo-coding. All authors have access to the data and have reviewed the paper and Supplementary Information.
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Reviewer Information Nature thanks S. Dushoff, B. Greenwood, J. Gupta and the other anonymous reviewer(s) for their contribution to the peer review of this work.
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Extended data figures and tables
Extended Data Figure 1 Availability of survey data over time.
The temporal distribution of survey data per interval selected for analysis (number of surveys shown on top of bars).
Extended Data Figure 2 Spatial distribution of survey data.
Location of 50,424 P. falciparum parasite surveys undertaken at 39,033 locations by time interval from 1900–1944 to 2010–2015.
Extended Data Figure 3 The spatial range of P. falciparum in Africa between 1900 and 1950.
Light grey, absence of natural P. falciparum transmission; pink, natural extent of transmission; dark grey, countries not included in the analysis.
Extended Data Figure 4 Model convergence: Gelman–Rubin–Brooks plots demonstrating convergence during MCMC simulation for key model parameters.
Black line, ratio of within-chain variability to between-chain variability; dark grey line, within-chain variability (pooled); light grey line, between-chain variability (average).
Extended Data Figure 5 Model validation.
Predicted Pf PR2–10 versus observed PfPR2–10 for 100 randomly selected data points. Ninety-nine per cent of data points are within 95% credible interval (CI); Spearman rank correlation 0.46, P < 0.001 (two-sided test).
Supplementary information
Supplementary Information
This file provides detailed descriptions of large data assembly, changing margins of malaria risk, statistical handling of the data, Supplementary References, Acknowledgements and Supplementary Table 1. (PDF 1889 kb)
Supplementary Data
Source data of model outputs per polygon 1900-2015. This file provides the model outputs per 520 administrative polygons in Africa for 16 prediction years since 1900. (XLSX 1285 kb)
Supplementary Data
Source data of median predictions of P. falciparum prevalance since 1900. This file contains the median and confidence range of all 520 polygon predictions of P. falciparum prevalence for 16 prediction years since 1900. (XLSX 14 kb)
Supplementary Data
Source data for GIS shape files of historical endemicity. This file provides margins and polygons of prediction of malaria at its historical extent. (ZIP 12762 kb)
Supplementary Data
Source data for GIS shape files of changing margins of malaria risk in Africa. This file shows how margins of transmission of malaria changed from 1900 to 2015. (ZIP 17572 kb)
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Snow, R., Sartorius, B., Kyalo, D. et al. The prevalence of Plasmodium falciparum in sub-Saharan Africa since 1900. Nature 550, 515–518 (2017). https://doi.org/10.1038/nature24059
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DOI: https://doi.org/10.1038/nature24059
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