ArticleMolecular biology and evolution2021
Evaluating the Performance of Malaria Genetics for Inferring Changes in Transmission Intensity Using Transmission Modeling.
Article in Molecular biology and evolution, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.
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Who cites it
30 citing papers in PubMed, 44 citations in OpenAlex.
- Absence of false negative RDT results due to pfhrp2 deletion among symptomatic malaria infections in Kenya: findings from the 2022 Kenya national longitudinal surveillance of pfhrp2/3 deletions.Malaria journal · 2026Article
- Malaria control and the unexpected spread of diagnostic-resistantbioRxiv : the preprint server for biology · 2026Article
- Accuracy of Plasmodium falciparum genetic data for estimating parasite prevalence and malaria incidence in Uganda.Malaria journal · 2026Article
- Complexity of Infection andmedRxiv : the preprint server for health sciences · 2026Article
- Rare variation in malaria parasites biases population-genetic inference.bioRxiv : the preprint server for biology · 2026Article
- Haplotype diversity ofFrontiers in parasitology · 2026Article
- Genetic metrics decodeFrontiers in genetics · 2026Article
- Assessing the impact of temporal changes in transmission on Plasmodium falciparum strains in Asembo, western Kenya (1996-2017) using within-host metrics via 24-SNP barcodes.Malaria journal · 2025Article
- Accuracy of Plasmodium falciparum genetic data for estimating parasite prevalence and malaria incidence in Uganda.Research square · 2025Article
- Genetic polymorphism of MSP2 and its implications for Plasmodium falciparum resistance in N'Djamena, Chad.Tropical diseases, travel medicine and vaccines · 2025Article
- Measuring changes ineLife · 2025Article
- Antimalarial drug resistance and population structure of Plasmodium falciparum in Mozambique using genomic surveillance at health facilities in 2021 and 2022.Scientific reports · 2025Article
- Sensitive and modular amplicon sequencing of Plasmodium falciparum diversity and resistance for research and public health.Scientific reports · 2025Article
- Sensitive and modular amplicon sequencing ofbioRxiv : the preprint server for biology · 2025Article
- Bridging the Gap from Molecular Surveillance to Programmatic Decisions for Malaria Control and Elimination.The American journal of tropical medicine and hygiene · 2025Review
- Article
- Review of MrsFreqPhase methods: methods designed to estimate statistically malaria parasite multiplicity of infection, relatedness, frequency and phase.Malaria journal · 2024Review
- Risk of selection and timelines for the continued spread of artemisinin and partner drug resistance in Africa.medRxiv : the preprint server for health sciences · 2024Article
- Modelling transmission dynamics and genomic diversity in a recombining parasite population.Wellcome open research · 2024Article
- Malaria surveillance reveals parasite relatedness, signatures of selection, and correlates of transmission across Senegal.Nature communications · 2023Article
Corrections and comments
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Authors and funding
16 authors at 7 institutions in 5 countries.
Funding
Abstract
Substantial progress has been made globally to control malaria, however there is a growing need for innovative new tools to ensure continued progress. One approach is to harness genetic sequencing and accompanying methodological approaches as have been used in the control of other infectious diseases. However, to utilize these methodologies for malaria, we first need to extend the methods to capture the complex interactions between parasites, human and vector hosts, and environment, which all impact the level of genetic diversity and relatedness of malaria parasites. We develop an individual-based transmission model to simulate malaria parasite genetics parameterized using estimated relationships between complexity of infection and age from five regions in Uganda and Kenya. We predict that cotransmission and superinfection contribute equally to within-host parasite genetic diversity at 11.5% PCR prevalence, above which superinfections dominate. Finally, we characterize the predictive power of six metrics of parasite genetics for detecting changes in transmission intensity, before grouping them in an ensemble statistical model. The model predicted malaria prevalence with a mean absolute error of 0.055. Different assumptions about the availability of sample metadata were considered, with the most accurate predictions of malaria prevalence made when the clinical status and age of sampled individuals is known. Parasite genetics may provide a novel surveillance tool for estimating the prevalence of malaria in areas in which prevalence surveys are not feasible. However, the findings presented here reinforce the need for patient metadata to be recorded and made available within all future attempts to use parasite genetics for surveillance.
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