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Spatiotemporal spread of Plasmodium falciparum mutations for resistance to sulfadoxine-pyrimethamine across Africa, 1990–2020

Abstract:
Current malaria elimination targets must withstand a colossal challenge–resistance to the current gold standard antimalarial drug, namely artemisinin derivatives. If artemisinin resistance significantly expands to Africa or India, cases and malaria-related deaths are set to increase substantially. Spatial information on the changing levels of artemisinin resistance in Southeast Asia is therefore critical for health organisations to prioritise malaria control measures, but available data on artemisinin resistance are sparse. We use a comprehensive database from the WorldWide Antimalarial Resistance Network on the prevalence of non-synonymous mutations in the Kelch 13 (K13) gene, which are known to be associated with artemisinin resistance, and a Bayesian geostatistical model to produce spatio-temporal predictions of artemisinin resistance. Our maps of estimated prevalence show an expansion of the K13 mutation across the Greater Mekong Subregion from 2000 to 2022. Moreover, the period between 2010 and 2015 demonstrated the most spatial change across the region. Our model and maps provide important insights into the spatial and temporal trends of artemisinin resistance in a way that is not possible using data alone, thereby enabling improved spatial decision support systems on an unprecedented fine-scale spatial resolution. By predicting for the first time spatio-temporal patterns and extents of artemisinin resistance at the subcontinent level, this study provides critical information for supporting malaria elimination goals in Southeast Asia
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1371/journal.pcbi.1010317

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Role:
Author
ORCID:
0000-0002-8809-726X
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Institution:
University of Oxford
Oxford college:
Green Templeton College
Role:
Author
ORCID:
0000-0001-9947-0034


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Funder identifier:
10.13039/501100000923
Grant:
DP200100747
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Funder identifier:
10.13039/100000865
Grant:
INV OPP1181807 and INV OPP1099191
More from this funder
Funder identifier:
10.13039/100004371


Publisher:
Public Library of Science
Journal:
PLoS Computational Biology More from this journal
Volume:
18
Issue:
8
Pages:
e1010317-e1010317
Publication date:
2022-08-11
DOI:
EISSN:
1553-7358
ISSN:
1553-734X


Language:
English
Keywords:
Pubs id:
1274910
Local pid:
pubs:1274910
Source identifiers:
W4291007324
Deposit date:
2026-04-28
ARK identifier:
This ORA record was generated from metadata provided by an external service. It has not been edited by the ORA Team.

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