Evidence map›Paper›PMID 38363295›Full record

ArticleeLife2024

Antigenic strain diversity predicts different biogeographic patterns of maintenance and decline of antimalarial drug resistance.

Qixin He, John K Chaillet, Frédéric Labbé

Abstract read
In one paragraph

Article in eLife, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Qixin He *Department of Biological Sciences, Purdue University, West Lafayette, United States.ORCID https://orcid.org/0000-0003-1696-8203
John K Chaillet *Department of Biological Sciences, Purdue University, West Lafayette, United States.ORCID https://orcid.org/0000-0002-6156-4649
Frédéric LabbéDepartment of Ecology and Evolution, University of Chicago, Chicago, United States.ORCID https://orcid.org/0000-0002-4064-2361

Funding

Temporal strain structure and response to interventions in a high endemicity region of Plasmodium falciparum R01AI149779 · NIAID · UNIVERSITY OF CHICAGO · PI DAY, KAREN PATRICIA, KORAM, KWADWO ANSAH · 2019 to 2023
$3.0M
FIC NIH HHS R01-AI149779NIAID NIH HHS R01 AI149779
6 · The paper itself

Abstract

The establishment and spread of antimalarial drug resistance vary drastically across different biogeographic regions. Though most infections occur in sub-Saharan Africa, resistant strains often emerge in low-transmission regions. Existing models on resistance evolution lack consensus on the relationship between transmission intensity and drug resistance, possibly due to overlooking the feedback between antigenic diversity, host immunity, and selection for resistance. To address this, we developed a novel compartmental model that tracks sensitive and resistant parasite strains, as well as the host dynamics of generalized and antigen-specific immunity. Our results show a negative correlation between parasite prevalence and resistance frequency, regardless of resistance cost or efficacy. Validation using chloroquine-resistant marker data supports this trend. Post discontinuation of drugs, resistance remains high in low-diversity, low-transmission regions, while it steadily decreases in high-diversity, high-transmission regions. Our study underscores the critical role of malaria strain diversity in the biogeographic patterns of resistance evolution.

Indexed as

AntimalarialsMalariaMalaria, FalciparumAfrica South of the SaharaChloroquineDrug ResistanceHumansPlasmodium falciparumAntimalarialsChloroquineantigenic diversitydisease modelingdrug resistanceepidemiologyglobal healthGreater Mekong SubregionP. falciparum

Identifiers

PMID38363295
PMCPMC10942604

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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.