Evidence map›Paper›PMID 38443939›Full record

ArticleMalaria journal2024

Evaluating the performance of Plasmodium falciparum genetic metrics for inferring National Malaria Control Programme reported incidence in Senegal.

Wesley Wong, Stephen F Schaffner, Julie Thwing, Mame Cheikh Seck, Jules Gomis, Younouss Diedhiou, Ngayo Sy, Medoune Ndiop, Fatou Ba, Ibrahima Diallo and 19 more

Open access · goldAbstract read
In one paragraph

Article in Malaria journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
4.9field-weighted citation impact, top 5% of its field
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

7 citing papers in PubMed, 9 citations in OpenAlex.

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  6. BMJ open · 2024
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

29 authors at 8 institutions in 2 countries.

Wesley WongDepartment of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, MA, USA.
Stephen F SchaffnerInfectious Disease and Microbiome Program, The Broad Institute, Cambridge, MA, USA.
Julie ThwingMalaria Branch, Division of Parasitic Diseases and Malaria, Global Health Center, Centers for Disease Control and Prevention, Atlanta, GA, USA.
Mame Cheikh SeckCentre International de recherche, de formation en Genomique Appliquee et de Surveillance Sanitaire (CIGASS), Dakar, Senegal.
Jules GomisCentre International de recherche, de formation en Genomique Appliquee et de Surveillance Sanitaire (CIGASS), Dakar, Senegal.
Younouss DiedhiouCentre International de recherche, de formation en Genomique Appliquee et de Surveillance Sanitaire (CIGASS), Dakar, Senegal.
Ngayo SySection de Lutte Anti-Parasitaire (SLAP) Clinic, Thies, Senegal.
Medoune NdiopProgramme National de Lutte contre le Paludisme (PNLP), Dakar, Senegal.
Fatou BaProgramme National de Lutte contre le Paludisme (PNLP), Dakar, Senegal.
Ibrahima DialloProgramme National de Lutte contre le Paludisme (PNLP), Dakar, Senegal.
Doudou SeneProgramme National de Lutte contre le Paludisme (PNLP), Dakar, Senegal.
Mamadou Alpha DialloCentre International de recherche, de formation en Genomique Appliquee et de Surveillance Sanitaire (CIGASS), Dakar, Senegal.
Yaye Die NdiayeCentre International de recherche, de formation en Genomique Appliquee et de Surveillance Sanitaire (CIGASS), Dakar, Senegal.
Mouhamad SyCentre International de recherche, de formation en Genomique Appliquee et de Surveillance Sanitaire (CIGASS), Dakar, Senegal.
Aita SeneCentre International de recherche, de formation en Genomique Appliquee et de Surveillance Sanitaire (CIGASS), Dakar, Senegal.
Djiby SowCentre International de recherche, de formation en Genomique Appliquee et de Surveillance Sanitaire (CIGASS), Dakar, Senegal.
Baba DieyeCentre International de recherche, de formation en Genomique Appliquee et de Surveillance Sanitaire (CIGASS), Dakar, Senegal.
Abdoulaye TineCentre International de recherche, de formation en Genomique Appliquee et de Surveillance Sanitaire (CIGASS), Dakar, Senegal.
Jessica RibadoInstitute for Disease Modeling at the Bill and Melinda Gates Foundation, Seattle, WA, USA.
Joshua SureshInstitute for Disease Modeling at the Bill and Melinda Gates Foundation, Seattle, WA, USA.
Albert LeeInstitute for Disease Modeling at the Bill and Melinda Gates Foundation, Seattle, WA, USA.
Katherine E BattleInstitute for Disease Modeling at the Bill and Melinda Gates Foundation, Seattle, WA, USA.
Joshua L ProctorInstitute for Disease Modeling at the Bill and Melinda Gates Foundation, Seattle, WA, USA.
Caitlin A BeverInstitute for Disease Modeling at the Bill and Melinda Gates Foundation, Seattle, WA, USA.
Bronwyn MacInnisInfectious Disease and Microbiome Program, The Broad Institute, Cambridge, MA, USA.
Daouda NdiayeCentre International de recherche, de formation en Genomique Appliquee et de Surveillance Sanitaire (CIGASS), Dakar, Senegal.
Daniel L HartlDepartment of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA.
Dyann F WirthDepartment of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, MA, USA.
Sarah K VolkmanDepartment of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, MA, USA. svolkman@hsph.harvard.edu.
Institute of Health Research, Epidemiological Surveillance and Training · SNCentre Hospitalier National Universitaire de Fann · SNBill & Melinda Gates Foundation · USHarvard University · USInstitute for Disease Modeling · USBroad Institute · USCenters for Disease Control and Prevention · USSimmons University · US

Funding

Malaria Genomic Epidemiology for Identifying Sources of Malaria Infection and TransmissionR21AI141843 · NIAID · HARVARD SCHOOL OF PUBLIC HEALTH · PI VOLKMAN, SARAH KAY · 2019 to 2020
$439k
NIAID NIH HHS R21 AI141843NIH HHS 5R21AI141843-02
6 · The paper itself

Abstract

backgroundGenetic surveillance of the Plasmodium falciparum parasite shows great promise for helping National Malaria Control Programmes (NMCPs) assess parasite transmission. Genetic metrics such as the frequency of polygenomic (multiple strain) infections, genetic clones, and the complexity of infection (COI, number of strains per infection) are correlated with transmission intensity. However, despite these correlations, it is unclear whether genetic metrics alone are sufficient to estimate clinical incidence.

methodsThis study examined parasites from 3147 clinical infections sampled between the years 2012-2020 through passive case detection (PCD) across 16 clinic sites spread throughout Senegal. Samples were genotyped with a 24 single nucleotide polymorphism (SNP) molecular barcode that detects parasite strains, distinguishes polygenomic (multiple strain) from monogenomic (single strain) infections, and identifies clonal infections. To determine whether genetic signals can predict incidence, a series of Poisson generalized linear mixed-effects models were constructed to predict the incidence level at each clinical site from a set of genetic metrics designed to measure parasite clonality, superinfection, and co-transmission rates.

resultsModel-predicted incidence was compared with the reported standard incidence data determined by the NMCP for each clinic and found that parasite genetic metrics generally correlated with reported incidence, with departures from expected values at very low annual incidence (< 10/1000/annual [‰]).

conclusionsWhen transmission is greater than 10 cases per 1000 annual parasite incidence (annual incidence > 10‰), parasite genetics can be used to accurately infer incidence and is consistent with superinfection-based hypotheses of malaria transmission. When transmission was < 10‰, many of the correlations between parasite genetics and incidence were reversed, which may reflect the disproportionate impact of importation and focal transmission on parasite genetics when local transmission levels are low.

Indexed as

MalariaSuperinfectionHumansIncidencePlasmodium falciparumSenegal

Identifiers

PMID38443939
PMCPMC10916253
OpenAlexW4392450523

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.