Evidence map›Paper›PMID 31370901›Full record

ArticleMalaria journal2019

Models of effectiveness of interventions against malaria transmitted by Anopheles albimanus.

Olivier J T Briët, Daniel E Impoinvil, Nakul Chitnis, Emilie Pothin, Jean Frantz Lemoine, Joseph Frederic, Thomas A Smith

Abstract read
In one paragraph

Article in Malaria journal, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 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

16 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Estimating mosquito bionomics parameters with a hierarchical Bayesian model.Current research in parasitology & vector-borne diseases · 2026
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  9. The Importance of Local Context in National Malaria Elimination Efforts.The American journal of tropical medicine and hygiene · 2023
    Article
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  11. Spatial, environmental, and individual associations withFrontiers in cellular and infection microbiology · 2022
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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

7 authors.

Olivier J T BriëtDepartment of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, 4051, Basel, Switzerland.ORCID http://orcid.org/0000-0003-1186-2688
Daniel E ImpoinvilCenters for Disease Control and Prevention, Division of Parasitic Diseases and Malaria/Entomology Branch, 1600 Clifton Road, Mail Stop-G49, Atlanta, GA, 30329, USA.
Nakul ChitnisDepartment of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, 4051, Basel, Switzerland.
Emilie PothinDepartment of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, 4051, Basel, Switzerland.
Jean Frantz LemoineProgramme National de Contrôle de la Malaria, Port-au-Prince, Haiti.
Joseph FredericProgramme National de Contrôle de la Malaria, Port-au-Prince, Haiti.
Thomas A SmithDepartment of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, 4051, Basel, Switzerland. thomas-a.smith@unibas.ch.

Funding

Bill and Melinda Gates Foundation OPP1032350
6 · The paper itself

Abstract

backgroundMost impact prediction of malaria vector control interventions has been based on African vectors. Anopheles albimanus, the main vector in Central America and the Caribbean, has higher intrinsic mortality, is more zoophilic and less likely to rest indoors. Therefore, relative impact among interventions may be different. Prioritizing interventions, in particular for eliminating Plasmodium falciparum from Haiti, should consider local vector characteristics.

methodsField bionomics data of An. albimanus from Hispaniola and intervention effect data from southern Mexico were used to parameterize mathematical malaria models. Indoor residual spraying (IRS), insecticide-treated nets (ITNs), and house-screening were analysed by inferring their impact on the vectorial capacity in a difference-equation model. Impact of larval source management (LSM) was assumed linear with coverage. Case management, mass drug administration and vaccination were evaluated by estimating their effects on transmission in a susceptible-infected-susceptible model. Analogous analyses were done for Anopheles gambiae parameterized with data from Tanzania, Benin and Nigeria.

resultsWhile LSM was equally effective against both vectors, impact of ITNs on transmission by An. albimanus was much lower than for An. gambiae. Assuming that people are outside until bedtime, this was similar for the impact of IRS with dichlorodiphenyltrichloroethane (DDT) or bendiocarb, and impact of IRS was less than that of ITNs. However, assuming people go inside when biting starts, IRS had more impact on An. albimanus than ITNs. While house-screening had less impact than ITNs or IRS on An. gambiae, it had more impact on An. albimanus than ITNs or IRS. The impacts of chemoprevention and chemotherapy were comparable in magnitude to those of strategies against An. albimanus. Chemo-prevention impact increased steeply as coverage approached 100%, whilst clinical-case management impact saturated because of remaining asymptomatic infections.

conclusionsHouse-screening and repellent IRS are potentially highly effective against An. albimanus if people are indoors during the evening. This is consistent with historical impacts of IRS with DDT, which can be largely attributed to excito-repellency. It also supports the idea that housing improvements have played a critical role in malaria control in North America. For elimination planning, impact estimates need to be combined with feasibility and cost-analysis.

Indexed as

AnophelesMosquito VectorsAfricaAnimalsCase ManagementCommunicable Disease ControlHaitiHumansLarvaMalariaMalaria VaccinesMass Drug AdministrationModels, TheoreticalMosquito ControlSpecies SpecificityVaccinationMalaria VaccinesAnophelesEliminationHaitiMalariaPlasmodium falciparum

Identifiers

PMID31370901
PMCPMC6670173

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.