Evidence map›Paper›PMID 38863023›Full record

ArticleParasites & vectors2024

Spatial and temporal analysis on the impact of ultra-low volume indoor insecticide spraying on Aedes aegypti household density.

Anna B Kawiecki, Amy C Morrison, Christopher M Barker

Abstract read
In one paragraph

Article in Parasites & vectors, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Anna B KawieckiUniversity of California Davis, Davis, CA, USA. akawiecki@ucdavis.edu.
Amy C MorrisonUniversity of California Davis, Davis, CA, USA.
Christopher M BarkerUniversity of California Davis, Davis, CA, USA. cmbarker@ucdavis.edu.

Funding

Surveillance Core (B)P01AI098670 · NIAID · UNIVERSITY OF CALIFORNIA AT DAVIS · PI SCOTT, THOMAS WALLACE · 2014 to 2018
$7.9M
CDC HHS 1U01CK000516National Science Foundation RTG/DMS - 1246991NIH HHS 5P01AI098670
6 · The paper itself

Abstract

backgroundAedes aegypti is the primary mosquito vector for several arboviruses, such as dengue, chikungunya and Zika viruses, which cause frequent outbreaks of human disease in tropical and subtropical regions. Control of these outbreaks relies on vector control, commonly in the form of insecticide sprays that target adult female mosquitoes. However, the spatial coverage and frequency of sprays needed to optimize effectiveness are unclear. In this study, we characterize the effect of ultra-low-volume (ULV) indoor spraying of pyrethroid insecticides on Ae. aegypti abundance within households. We also evaluate the effects of spray events during recent time periods or in neighboring households. Improved understanding of the duration and distance of the impact of a spray intervention on Ae. aegypti populations can inform vector control interventions, in addition to modeling efforts that contrast vector control strategies.

methodsThis project analyzes data from two large-scale experiments that involved six cycles of indoor pyrethroid spray applications in 2 years in the Amazonian city of Iquitos, Peru. We developed spatial multi-level models to disentangle the reduction in Ae. aegypti abundance that resulted from (i) recent ULV treatment within households and (ii) ULV treatment of adjacent or nearby households. We compared fits of models across a range of candidate weighting schemes for the spray effect, based on different temporal and spatial decay functions to understand lagged ULV effects.

resultsOur results suggested that the reduction of Ae. aegypti in a household was mainly due to spray events occurring within the same household, with no additional effect of sprays that occurred in neighboring households. Effectiveness of a spray intervention should be measured based on time since the most recent spray event, as we found no cumulative effect of sequential sprays. Based on our model, we estimated the spray effect is reduced by 50% approximately 28 days after the spray event.

conclusionsThe reduction of Ae. aegypti in a household was mainly determined by the number of days since the last spray intervention in that same household, highlighting the importance of spray coverage in high-risk areas with a spray frequency determined by local viral transmission dynamics.

Indexed as

AedesFamily CharacteristicsInsecticidesMosquito ControlMosquito VectorsPyrethrinsSpatio-Temporal AnalysisAnimalsDengueFemaleHumansPeruPopulation DensityInsecticidesPyrethrinsAedes aegyptiDengueInsect controlInsecticideMosquitoPeruVector-borne diseases

Identifiers

PMID38863023
PMCPMC11165869

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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.