Evidence map›Paper›PMID 25102062›Full record

ArticlePLoS neglected tropical diseases2014

Shifting patterns of Aedes aegypti fine scale spatial clustering in Iquitos, Peru.

Genevieve LaCon, Amy C Morrison, Helvio Astete, Steven T Stoddard, Valerie A Paz-Soldan, John P Elder, Eric S Halsey, Thomas W Scott, Uriel Kitron, Gonzalo M Vazquez-Prokopec

Abstract read
In one paragraph

Article in PLoS neglected tropical diseases, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers.

0numbers the graph read from it
0cells of the map it votes in
49citing 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

49 citing papers in PubMed.

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  9. Role of Non-Residential Larval Habitats inLife (Basel, Switzerland) · 2024
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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

10 authors.

Genevieve LaConDepartment of Environmental Sciences, Emory University, Atlanta, Georgia, United States of America.
Amy C MorrisonDepartment of Entomology, University of California Davis, Davis, California, United States of America.
Helvio AsteteU.S. Naval Medical Research Unit No. 6, Lima and Iquitos, Peru.
Steven T StoddardDepartment of Entomology, University of California Davis, Davis, California, United States of America; Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America.
Valerie A Paz-SoldanDepartment of Global Health Systems and Development, Tulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana, United States of America.
John P ElderGraduate School of Public Health, San Diego State University, San Diego, California, United States of America.
Eric S HalseyU.S. Naval Medical Research Unit No. 6, Lima and Iquitos, Peru.
Thomas W ScottDepartment of Entomology, University of California Davis, Davis, California, United States of America; Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America.
Uriel KitronDepartment of Environmental Sciences, Emory University, Atlanta, Georgia, United States of America; Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America.
Gonzalo M Vazquez-ProkopecDepartment of Environmental Sciences, Emory University, Atlanta, Georgia, United States of America; Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America.

Funding

Measuring Entomological Risk for DengueR01AI069341 · NIAID · UNIVERSITY OF CALIFORNIA AT DAVIS · PI SCOTT, THOMAS WALLACE · 2006 to 2010
$2.3M
NIAID NIH HHS R01 AI069341NIAID NIH HHS R01 AI069341-01
6 · The paper itself

Abstract

backgroundEmpiric evidence shows that Aedes aegypti abundance is spatially heterogeneous and that some areas and larval habitats produce more mosquitoes than others. There is a knowledge gap, however, with regards to the temporal persistence of such Ae. aegypti abundance hotspots. In this study, we used a longitudinal entomologic dataset from the city of Iquitos, Peru, to (1) quantify the spatial clustering patterns of adult Ae. aegypti and pupae counts per house, (2) determine overlap between clusters, (3) quantify the temporal stability of clusters over nine entomologic surveys spaced four months apart, and (4) quantify the extent of clustering at the household and neighborhood levels. METHODOLOGIES/PRINCIPAL

findingsData from 13,662 household entomological visits performed in two Iquitos neighborhoods differing in Ae. aegypti abundance and dengue virus transmission was analyzed using global and local spatial statistics. The location and extent of Ae. aegypti pupae and adult hotspots (i.e., small groups of houses with significantly [p<0.05] high mosquito abundance) were calculated for each of the 9 entomologic surveys. The extent of clustering was used to quantify the probability of finding spatially correlated populations. Our analyses indicate that Ae. aegypti distribution was highly focal (most clusters do not extend beyond 30 meters) and that hotspots of high vector abundance were common on every survey date, but they were temporally unstable over the period of study. CONCLUSIONS/SIGNIFICANCE: Our findings have implications for understanding Ae. aegypti distribution and for the design of surveillance and control activities relying on household-level data. In settings like Iquitos, where there is a relatively low percentage of Ae. aegypti in permanent water-holding containers, identifying and targeting key premises will be significantly challenged by shifting hotspots of Ae. aegypti infestation. Focusing efforts in large geographic areas with historically high levels of transmission may be more effective than targeting Ae. aegypti hotspots.

Indexed as

AedesInsect VectorsAnimalsCluster AnalysisDemographyDengueEcosystemEntomologyFamily CharacteristicsFemaleMalePeru

Identifiers

PMID25102062
PMCPMC4125221

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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.