Evidence map›Paper›PMID 24465196›Full record

ArticlePLoS computational biology2014

Modeling within-host effects of drugs on Plasmodium falciparum transmission and prospects for malaria elimination.

Geoffrey L Johnston, Peter W Gething, Simon I Hay, David L Smith, David A Fidock

Abstract read
In one paragraph

Article in PLoS computational biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed, 5 pooled it
–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

32 citing papers in PubMed, 5 syntheses or guidelines pooled it.

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  12. Prevalence ofParasite epidemiology and control · 2023
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Geoffrey L JohnstonDepartment of Microbiology and Immunology, Columbia University College of Physicians and Surgeons, New York, New York, United States of America ; School of International and Public Affairs, Columbia University, New York, New York, United States of America ; Bloomberg School of Public Health, John Hopkins University, Baltimore, Maryland, United States of America.
Peter W GethingSpatial Ecology and Epidemiology Group, Department of Zoology, University of Oxford, Oxford, United Kingdom.
Simon I HaySpatial Ecology and Epidemiology Group, Department of Zoology, University of Oxford, Oxford, United Kingdom.
David L SmithBloomberg School of Public Health, John Hopkins University, Baltimore, Maryland, United States of America.
David A FidockDepartment of Microbiology and Immunology, Columbia University College of Physicians and Surgeons, New York, New York, United States of America ; Division of Infectious Diseases, Department of Medicine, Columbia University College of Physicians and Surgeons, New York, New York, United States of America.

Funding

Transmission ProjectU19AI089674 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI MATTHEW G DORSEY, MOSES Robert KAMYA · 2010 to 2026
$29.3M
Pharmacologic Approaches to Combating Resistance to Antimalarial CombinationsR01AI079709 · NIAID · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI FIDOCK, DAVID A, KYLE, DENNIS E · 2008 to 2011
$2.3M
Medical Research Council K00669XMedical Research Council MR/K00669X/1NIAID NIH HHS R01 AI079709NIAID NIH HHS U19 AI089674Wellcome Trust 095066
6 · The paper itself

Abstract

Achieving a theoretical foundation for malaria elimination will require a detailed understanding of the quantitative relationships between patient treatment-seeking behavior, treatment coverage, and the effects of curative therapies that also block Plasmodium parasite transmission to mosquito vectors. Here, we report a mechanistic, within-host mathematical model that uses pharmacokinetic (PK) and pharmacodynamic (PD) data to simulate the effects of artemisinin-based combination therapies (ACTs) on Plasmodium falciparum transmission. To contextualize this model, we created a set of global maps of the fold reductions that would be necessary to reduce the malaria R C (i.e. its basic reproductive number under control) to below 1 and thus interrupt transmission. This modeling was applied to low-transmission settings, defined as having a R 0<10 based on 2010 data. Our modeling predicts that treating 93-98% of symptomatic infections with an ACT within five days of fever onset would interrupt malaria transmission for ∼91% of the at-risk population of Southeast Asia and ∼74% of the global at-risk population, and lead these populations towards malaria elimination. This level of treatment coverage corresponds to an estimated 81-85% of all infected individuals in these settings. At this coverage level with ACTs, the addition of the gametocytocidal agent primaquine affords no major gains in transmission reduction. Indeed, we estimate that it would require switching ∼180 people from ACTs to ACTs plus primaquine to achieve the same transmission reduction as switching a single individual from untreated to treated with ACTs. Our model thus predicts that the addition of gametocytocidal drugs to treatment regimens provides very small population-wide benefits and that the focus of control efforts in Southeast Asia should be on increasing prompt ACT coverage. Prospects for elimination in much of Sub-Saharan Africa appear far less favorable currently, due to high rates of infection and less frequent and less rapid treatment.

Indexed as

AlgorithmsAnimalsAntimalarialsAsia, SoutheasternCommunicable Disease ControlComputer SimulationCulicidaeGeographyHumansMalaria, FalciparumModels, TheoreticalPlasmodium falciparumSoftwareAntimalarials

Identifiers

PMID24465196
PMCPMC3900379

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.