Evidence map›Paper›PMID 28716087›Full record

ArticleMalaria journal2017

Explaining variation in adult Anopheles indoor resting abundance: the relative effects of larval habitat proximity and insecticide-treated bed net use.

Robert S McCann, Joseph P Messina, David W MacFarlane, M Nabie Bayoh, John E Gimnig, Emanuele Giorgi, Edward D Walker

Abstract read
In one paragraph

Article in Malaria journal, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

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  9. IdentifyingeLife · 2021
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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.

Robert S McCannDepartment of Entomology, Michigan State University, East Lansing, MI, USA.
Joseph P MessinaDepartment of Geography, Environment, and Spatial Sciences, Michigan State University, East Lansing, MI, USA.
David W MacFarlaneDepartment of Forestry, Michigan State University, East Lansing, MI, USA.
M Nabie BayohCentre for Global Health Research, Kenya Medical Research Institute/Centers for Disease Control and Prevention, Kisumu, Kenya.
John E GimnigDivision of Parasitic Diseases and Malaria, Centers for Disease Control and Prevention, Atlanta, GA, USA.
Emanuele GiorgiLancaster Medical School, Lancaster University, Lancaster, UK.
Edward D WalkerDepartment of Microbiology and Molecular Genetics, Michigan State University, 567 Wilson Road, 2215 Biomedical Physical Sciences Building, East Lansing, MI, 48824-4320, USA. walker@msu.edu.

Funding

Medical Research Council MR/M015297/1
6 · The paper itself

Abstract

backgroundSpatial determinants of malaria risk within communities are associated with heterogeneity of exposure to vector mosquitoes. The abundance of adult malaria vectors inside people's houses, where most transmission takes place, should be associated with several factors: proximity of houses to larval habitats, structural characteristics of houses, indoor use of vector control tools containing insecticides, and human behavioural and environmental factors in and near houses. While most previous studies have assessed the association of larval habitat proximity in landscapes with relatively low densities of larval habitats, in this study these relationships were analysed in a region of rural, lowland western Kenya with high larval habitat density.

methods525 houses were sampled for indoor-resting mosquitoes across an 8 by 8 km study area using the pyrethrum spray catch method. A predictive model of larval habitat location in this landscape, previously verified, provided derivations of indices of larval habitat proximity to houses. Using geostatistical regression models, the association of larval habitat proximity, long-lasting insecticidal nets (LLIN) use, house structural characteristics (wall type, roof type), and peridomestic variables (cooking in the house, cattle near the house, number of people sleeping in the house) with mosquito abundance in houses was quantified.

resultsVector abundance was low (mean, 1.1 adult Anopheles per house). Proximity of larval habitats was a strong predictor of Anopheles abundance. Houses without an LLIN had more female Anopheles gambiae s.s., Anopheles arabiensis and Anopheles funestus than houses where some people used an LLIN (rate ratios, 95% CI 0.87, 0.85-0.89; 0.84, 0.82-0.86; 0.38, 0.37-0.40) and houses where everyone used an LLIN (RR, 95% CI 0.49, 0.48-0.50; 0.39, 0.39-0.40; 0.60, 0.58-0.61). Cooking in the house also reduced Anopheles abundance across all species. The number of people sleeping in the house, presence of cattle near the house, and house structure modulated Anopheles abundance, but the effect varied with Anopheles species and sex.

conclusionsVariation in the abundance of indoor-resting Anopheles in rural houses of western Kenya varies with clearly identifiable factors. Results suggest that LLIN use continues to function in reducing vector abundance, and that larval source management in this region could lead to further reductions in malaria risk by reducing the amount of an obligatory resource for mosquitoes near people's homes.

Indexed as

Animal DistributionEcosystemAnimalsAnophelesFemaleInsecticide-Treated BednetsKenyaLarvaMaleMosquito VectorsPopulation DensityAnopheles arabiensisAnopheles funestusAnopheles gambiaeGeneralized linear modelsGeostatistical modelsLarval habitatsMalaria vectorsSpatial heterogeneity

Identifiers

PMID28716087
PMCPMC5514485

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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.