Evidence map›Paper›PMID 42413528›Full record

ArticleThe Lancet. Infectious diseases2026

Mapping the prevalence of molecular markers of Plasmodium falciparum artemisinin partial resistance in Africa: a systematic review and spatiotemporal modelling study.

Neeva Wernsman Young, Cécile P G Meier-Scherling, Gina Cuomo-Dannenburg, George A Tollefson, Sean V Connelly, Jacob Marglous, Isabela Gerdes Gyuricza, Kelly Carey-Ewend, Ronald Kyong-Shin, Zachary R Popkin-Hall and 13 more

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Article in The Lancet. Infectious diseases, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

23 authors.

Neeva Wernsman YoungCenter for Computational Molecular Biology, Brown University, Providence, RI, USA; Department of Pathology and Laboratory Medicine, Brown University, Providence, RI, USA.
Cécile P G Meier-ScherlingCenter for Computational Molecular Biology, Brown University, Providence, RI, USA.
Gina Cuomo-DannenburgMRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK; Department of Microbiology and Immunology, Rega Institute, KU Leuven, Leuven, Belgium.
George A TollefsonCenter for Computational Molecular Biology, Brown University, Providence, RI, USA; Department of Pathology and Laboratory Medicine, Brown University, Providence, RI, USA.
Sean V ConnellyInstitute for Global Health and Infectious Diseases, University of North Carolina, Chapel Hill, NC, USA; University of North Carolina, Chapel Hill, NC, USA.
Jacob MarglousCenter for Computational Molecular Biology, Brown University, Providence, RI, USA; Department of Pathology and Laboratory Medicine, Brown University, Providence, RI, USA.
Isabela Gerdes GyuriczaUniversity of North Carolina, Chapel Hill, NC, USA.
Kelly Carey-EwendInstitute for Global Health and Infectious Diseases, University of North Carolina, Chapel Hill, NC, USA; University of North Carolina, Chapel Hill, NC, USA.
Ronald Kyong-ShinUniversity of North Carolina, Chapel Hill, NC, USA; National Institute of Biomedical Research, Kinshasa, Democratic Republic of the Congo.
Zachary R Popkin-HallInstitute for Global Health and Infectious Diseases, University of North Carolina, Chapel Hill, NC, USA; Department of Biology, Western Connecticut State University, Danbury, CT, USA.
Ayalew Jejaw ZelekeDepartment of Medical Parasitology, School of Biomedical and Laboratory Sciences, University of Gondar, Gondar, Ethiopia.
Deus S IshengomaIfikara Health Institute, Ifikara, Tanzania; National Institute for Medical Research, Dar es Salaam, Tanzania.
Abebe A FolaDepartment of Pathology and Laboratory Medicine, Brown University, Providence, RI, USA.
Alfred SimkinDepartment of Pathology and Laboratory Medicine, Brown University, Providence, RI, USA.
Karamoko NiaréDepartment of Pathology and Laboratory Medicine, Brown University, Providence, RI, USA.
Jonathan B ParrInstitute for Global Health and Infectious Diseases, University of North Carolina, Chapel Hill, NC, USA; University of North Carolina, Chapel Hill, NC, USA; Division of Infectious Diseases, Department of Medicine, UNC School of Medicine, Chapel Hill, NC, USA.
Melissa ConradDepartment of Molecular Microbiology and Immunology, Johns Hopkins School of Public Health, Baltimore, MD, USA.
Lucy C OkellMRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK.
Shazia Ruybal-PesántezMRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK; Instituto de Microbiología, Universidad San Francisco de Quito, Quito, Ecuador.
Oliver J WatsonMRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK.
Jonathan J JulianoUniversity of North Carolina, Chapel Hill, NC, USA; Division of Infectious Diseases, Department of Medicine, UNC School of Medicine, Chapel Hill, NC, USA; Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA.
Jeffrey A BaileyCenter for Computational Molecular Biology, Brown University, Providence, RI, USA; Department of Pathology and Laboratory Medicine, Brown University, Providence, RI, USA. Electronic address: jeffrey_bailey@brown.edu.
Robert VerityMRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK. Electronic address: r.verity@imperial.ac.uk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPlasmodium falciparum kelch13(k13) mutations in Africa signal emerging artemisinin partial resistance (ART-R), endangering malaria control by undermining artemisinin-based combination therapies (ACTs). Sparse surveillance obscures whether rising k13 ART-R prevalence reflects local emergence or geographical expansion. We aimed to model and infer high-resolution spatiotemporal prevalence of k13 ART-R mutations, as well as mdr1 and crt mutations (markers of reduced susceptibility to ACT partner drugs), to inform public health policy.

methodsFor this systematic review and modelling analysis, we searched PubMed, Ovid MEDLINE, and Web of Science databases for English-language primary studies reporting malaria resistance, conducted in Africa, reporting pretreatment P falciparum samples with genotyping of k13 (all codons), mdr1 N86Y, or crt K76T, and that provided sufficient survey time and location metadata and complete, primary data, published between Sept 25, 2014, and July 9, 2025, with data extracted from full-text reports. Studies identified during the systematic review were added to 11 privately held datasets that met the same eligibility criteria but were unpublished at the time of review to give the augmented systematic review. Studies from the augmented systematic review were added to existing data from the Worldwide Antimalarial Resistance Network molecular surveyor (WWARN), MalariaGEN Pf8, and the WHO malaria threats map (WHO MTM), with any duplicates removed. The integrated dataset was harmonised by use of a standardised data schema. We estimated the continuous prevalence of each mutation using a spatiotemporal Gaussian process model and summarised with median and 95% credible intervals over posterior draws. The study was registered with PROSPERO (CRD42024593923).

findingsWe identified 1119 articles during the database search, with 120 studies included in the final analysis. These were augmented with 11 privately held datasets. In total, the augmented systematic review identified 131 unique studies. Data from public repositories (WWARN, Pf8, and WHO MTM) provided an additional 447 studies after removal of duplicates. The final dataset included 93 887 samples sequenced at target k13 positions and 185 099 samples sequenced for either k13, crt K76T, or mdr1 N86Y, drawn from 578 studies encompassing 3848 distinct surveys across 47 African countries. Modelling showed distinct emergences of k13 R561H in Rwanda, k13 A675V and C469Y in Uganda, and k13 R622I in Ethiopia and Eritrea. The highest predicted prevalence of k13 mutations in 2024 was observed in Northern Province, Rwanda, at 62·2% (95% credible interval 3·9-98·6), increasing from 0·2% (0·0-0·7) in 2012 at an average annual increase of 5·2 percentage points. Modelling indicated a rapid transition from localised k13 ART-R mutation emergence to entrenched regional hot spots covering most of Uganda and Rwanda, and similarly at the border of Ethiopia, Eritrea, and Sudan. Prevalence of mdr1 N86Y, a marker of partner-drug amodiaquine reduced susceptibility, is fading, but crt K76T remains prevalent in the Horn of Africa.

interpretationThe rapid, multicentric expansion of k13 ART-R mutations in east Africa threatens ACT efficacy, especially where k13 and markers of reduced susceptibility to partner drugs, such as mdr1 N86Y, or crt K76T, co-occur. This study provides an updated k13 ART-R mutation database and high-resolution resistance maps with uncertainty quantification, supporting targeted surveillance to identify hot spots and prioritise therapeutic efficacy studies.

fundingUS National Institutes of Health.

Identifiers

PMID42413528

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