Evidence map›Paper›PMID 41457278›Full record

ArticleParasites & vectors2025

Assessment of mosquito species communities biting humans and their livestock in the forest hills of Karen state, Myanmar: a cross-sectional survey in six villages.

Victor Chaumeau, Thithiwarada Kularbkeeree, Naw Gloria, Naw Jaruwan, Sunisa Sawasdichai, Chanapat Pateekhum, Florian Girond, Vincent Herbreteau, François Nosten

Abstract read
In one paragraph

Article in Parasites & vectors, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Victor ChaumeauShoklo Malaria Research Unit, Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Mae Ramat, Thailand. victor@tropmedres.ac.
Thithiwarada KularbkeereeShoklo Malaria Research Unit, Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Mae Ramat, Thailand.
Naw GloriaShoklo Malaria Research Unit, Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Mae Ramat, Thailand.
Naw JaruwanShoklo Malaria Research Unit, Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Mae Ramat, Thailand.
Sunisa SawasdichaiShoklo Malaria Research Unit, Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Mae Ramat, Thailand.
Chanapat PateekhumShoklo Malaria Research Unit, Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Mae Ramat, Thailand.
Florian GirondCommunicable Disease Control Department, Ministry of Health, Phnom Penh, Cambodia.
Vincent HerbreteauInstitut de Recherche pour le Développement, UMR 228 Espace-Dev, Phnom Penh, Cambodia.
François NostenShoklo Malaria Research Unit, Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Mae Ramat, Thailand.

Funding

Wellcome Trust
6 · The paper itself

Abstract

backgroundMosquito-borne diseases cause significant burdens in rural areas of Southeast Asia. The lack of data on vector bionomics hinders disease control and elimination. The objectives of this study were to assess the diversity and biting behaviours of mosquito species biting humans and their livestock in the forest hills of Karen state, Myanmar, and to assess the patterns of species co-occurrence and the effects of the environment on vector abundance.

methodsMosquitoes were captured over 24-h diel cycles in six villages in September 2019 using the human landing catch and cow-baited trap collection methods. Collected specimens were identified to the species level using dichotomous morphological keys. Environmental data were acquired through remote sensing. The analysis of biting times was performed with circular statistics. Species co-occurrence patterns and the effects of environmental variables on species abundance were assessed with a generalized linear latent variable model.

resultsA total of 36,607 mosquitoes were captured, and 96 species in 16 genera were identified. The most abundant genera were Anopheles, Culex and Downsiomyia. Multiple malaria, arboviruses and lymphatic filariasis vector species were detected, and their biting behaviours were reported. Generalized linear latent variable modelling revealed two clusters of species that were positively correlated with one another. The first cluster included many Culex and Anopheles species, and Mansonia annulata, which breed in shallow, stagnant or slow-moving water, such as marshes, swamps, rice fields and the margins of streams and puddles. These species were negatively associated with elevation, slopes and forests and positively associated with grasslands, shrubs and crop fields. The second cluster included many rainforest mosquitoes of the genera Armigeres, Heizmannia, Downsiomyia, Anopheles dirus, An. jeyporiensis, Culex bitaeniorhynchus and Aedes pseudoalbopictus, which breed in tree canopies and in natural surface water and containers such as bamboo stumps, tree holes and rainwater pools. These species were positively associated with elevation, slope, dense forests, surface water and wetlands and negatively associated with crop fields, grasslands and shrubs.

conclusionsTransmission dynamics are particularly complex in this setting where people are exposed to bites of numerous vector species throughout the diel cycle. Environmental factors shape the assembly of mosquito species communities and largely determine the risk of exposure to vector bites.

Indexed as

CulicidaeInsect Bites and StingsLivestockMosquito VectorsAnimalsAnophelesBiodiversityCattleCross-Sectional StudiesFeeding BehaviorFemaleForestsHumansMyanmarBiodiversityCulicidaeForestGeneralized linear latent variable modelMosquito-borne diseasesRemote sensingSoutheast AsiaSpecies community

Identifiers

PMID41457278
PMCPMC12860035

What Socratic 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 Socratic graph.