Evidence map›Paper›PMID 39269993›Full record

ArticlePLoS computational biology2024

AnophelesModel: An R package to interface mosquito bionomics, human exposure and intervention effects with models of malaria intervention impact.

Monica Golumbeanu, Olivier Briët, Clara Champagne, Jeanne Lemant, Munir Winkel, Barnabas Zogo, Maximilian Gerhards, Marianne Sinka, Nakul Chitnis, Melissa Penny and 2 more

Abstract read
In one paragraph

Article in PLoS computational biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Estimating mosquito bionomics parameters with a hierarchical Bayesian model.Current research in parasitology & vector-borne diseases · 2026
    Article
  3. Article
  4. Article
  5. Article
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

12 authors.

Monica GolumbeanuSwiss Tropical and Public Health Institute (Swiss TPH), Allschwil, Switzerland.ORCID 0000-0002-8459-9983
Olivier BriëtSwiss Tropical and Public Health Institute (Swiss TPH), Allschwil, Switzerland.
Clara ChampagneSwiss Tropical and Public Health Institute (Swiss TPH), Allschwil, Switzerland.
Jeanne LemantSwiss Tropical and Public Health Institute (Swiss TPH), Allschwil, Switzerland.ORCID 0000-0003-1522-0025
Munir WinkelSwiss Tropical and Public Health Institute (Swiss TPH), Allschwil, Switzerland.
Barnabas ZogoUniversity of Montpellier, Montpellier, France.
Maximilian GerhardsSwiss Tropical and Public Health Institute (Swiss TPH), Allschwil, Switzerland.
Marianne SinkaDepartment of Biology, University of Oxford, Oxford, United Kingdom.
Nakul ChitnisSwiss Tropical and Public Health Institute (Swiss TPH), Allschwil, Switzerland.
Melissa PennySwiss Tropical and Public Health Institute (Swiss TPH), Allschwil, Switzerland.
Emilie PothinSwiss Tropical and Public Health Institute (Swiss TPH), Allschwil, Switzerland.
Tom SmithSwiss Tropical and Public Health Institute (Swiss TPH), Allschwil, Switzerland.ORCID 0000-0002-3650-9381

Funding

Bill & Melinda Gates Foundation, United States INV-030449Bill & Melinda Gates Foundation, United States INV-068864Bill & Melinda Gates Foundation, United States OPP1032350
6 · The paper itself

Abstract

In recent decades, field and semi-field studies of malaria transmission have gathered geographic-specific information about mosquito ecology, behaviour and their sensitivity to interventions. Mathematical models of malaria transmission can incorporate such data to infer the likely impact of vector control interventions and hence guide malaria control strategies in various geographies. To facilitate this process and make model predictions of intervention impact available for different geographical regions, we developed AnophelesModel. AnophelesModel is an online, open-access R package that quantifies the impact of vector control interventions depending on mosquito species and location-specific characteristics. In addition, it includes a previously published, comprehensive, curated database of field entomological data from over 50 Anopheles species, field data on mosquito and human behaviour, and estimates of vector control effectiveness. Using the input data, the package parameterizes a discrete-time, state transition model of the mosquito oviposition cycle and infers species-specific impacts of various interventions on vectorial capacity. In addition, it offers formatted outputs ready to use in downstream analyses and by other models of malaria transmission for accurate representation of the vector-specific components. Using AnophelesModel, we show how the key implications for intervention impact change for various vectors and locations. The package facilitates quantitative comparisons of likely intervention impacts in different geographical settings varying in vector compositions, and can thus guide towards more robust and efficient malaria control recommendations. The AnophelesModel R package is available under a GPL-3.0 license at https://github.com/SwissTPH/AnophelesModel.

Indexed as

AnophelesMalariaMosquito ControlMosquito VectorsSoftwareAnimalsComputational BiologyHumansModels, Biological

Identifiers

PMID39269993
PMCPMC11424000

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.