Evidence map›Paper›PMID 39107395›Full record

ArticleScientific reports2024

High-resolution mapping of urban Aedes aegypti immature abundance through breeding site detection based on satellite and street view imagery.

Steffen Knoblauch, Myat Su Yin, Krittin Chatrinan, Antonio Augusto de Aragão Rocha, Peter Haddawy, Filip Biljecki, Sven Lautenbach, Bernd Resch, Dorian Arifi, Thomas Jänisch and 2 more

Erratum issuedAbstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

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

  1. Pooled it
  2. Article
  3. Article
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  5. Article
  6. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors.

Steffen KnoblauchGIScience Chair, Heidelberg University, 69120, Heidelberg, Germany. steffen.knoblauch@uni-heidelberg.de.ORCID https://orcid.org/0000-0003-3077-8094
Myat Su YinFaculty of ICT, Mahidol University, 73170, Nakhon Pathom, Thailand.
Krittin ChatrinanFaculty of ICT, Mahidol University, 73170, Nakhon Pathom, Thailand.
Antonio Augusto de Aragão RochaInstitute of Computing, Fluminense Federal University, 24210-240, Niterói, Brazil.
Peter HaddawyFaculty of ICT, Mahidol University, 73170, Nakhon Pathom, Thailand.
Filip BiljeckiDepartment of Architecture, National University of Singapore, 117566, Singapore, Singapore.
Sven LautenbachHeidelberg Institute for Geoinformation Technology, 69118, Heidelberg, Germany.
Bernd ReschGeo-social Analytics Lab, Paris Lodron University of Salzburg, 5020, Salzburg, Austria.
Dorian ArifiGeo-social Analytics Lab, Paris Lodron University of Salzburg, 5020, Salzburg, Austria.
Thomas JänischColorado School of Public Health, University of Colorado Anschutz Medical Campus, 80045, Aurora, USA.
Ivonne MoralesColorado School of Public Health, University of Colorado Anschutz Medical Campus, 80045, Aurora, USA.
Alexander ZipfGIScience Chair, Heidelberg University, 69120, Heidelberg, Germany.

Funding

Deutsche Forschungsgemeinschaft (German Research Foundation) 451956976
6 · The paper itself

Abstract

Identification of Aedes aegypti breeding hotspots is essential for the implementation of targeted vector control strategies and thus the prevention of several mosquito-borne diseases worldwide. Training computer vision models on satellite and street view imagery in the municipality of Rio de Janeiro, we analyzed the correlation between the density of common breeding grounds and Aedes aegypti infestation measured by ovitraps on a monthly basis between 2019 and 2022. Our findings emphasized the significance (p ≤ 0.05) of micro-habitat proxies generated through object detection, allowing to explain high spatial variance in urban abundance of Aedes aegypti immatures. Water tanks, non-mounted car tires, plastic bags, potted plants, and storm drains positively correlated with Aedes aegypti egg and larva counts considering a 1000 m mosquito flight range buffer around 2700 ovitrap locations, while dumpsters, small trash bins, and large trash bins exhibited a negative association. This complementary application of satellite and street view imagery opens the pathway for high-resolution interpolation of entomological surveillance data and has the potential to optimize vector control strategies. Consequently it supports the mitigation of emerging infectious diseases transmitted by Aedes aegypti, such as dengue, chikungunya, and Zika, which cause thousands of deaths each year.

Indexed as

AedesMosquito VectorsAnimalsBrazilBreedingCitiesEcosystemLarvaMosquito ControlSatellite ImageryAedes aegyptiObject detectionOvitrapRio de JaneiroSatelliteStreet view

Identifiers

PMID39107395
PMCPMC11303731

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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.