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Status: Bibliographieeintrag

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Verfasst von:Knoblauch, Steffen [VerfasserIn]   i
 Li, Hao [VerfasserIn]   i
 Lautenbach, Sven [VerfasserIn]   i
 Elshiaty, Yara [VerfasserIn]   i
 Rocha, Antônio A. de A. [VerfasserIn]   i
 Resch, Bernd [VerfasserIn]   i
 Arifi, Dorian [VerfasserIn]   i
 Jänisch, Thomas [VerfasserIn]   i
 Morales, Ivonne [VerfasserIn]   i
 Zipf, Alexander [VerfasserIn]   i
Titel:Semi-supervised water tank detection to support vector control of emerging infectious diseases transmitted by Aedes Aegypti
Verf.angabe:Steffen Knoblauch, Hao Li, Sven Lautenbach, Yara Elshiaty, Antônio A. de A. Rocha, Bernd Resch, Dorian Arifi, Thomas Jänisch, Ivonne Morales, Alexander Zipf
E-Jahr:2023
Jahr:19 April 2023
Umfang:11 S.
Fussnoten:Gesehen am 21.06.2023
Titel Quelle:Enthalten in: International journal of applied earth observation and geoinformation
Ort Quelle:Amsterdam [u.a.] : Elsevier Science, 1999
Jahr Quelle:2023
Band/Heft Quelle:119(2023) vom: Apr., Artikel-ID 103304, Seite 1-11
ISSN Quelle:1872-826X
Abstract:The disease transmitting mosquito Aedes Aegypti is an increasing global threat. It breeds in small artificial containers such as rainwater tanks and can be characterized by a short flight range. The resulting high spatial variability of abundance is challenging to model. Therefore, we tested an approach to map water tank density as a spatial proxy for urban Aedes Aegypti habitat suitability. Water tank density mapping was performed by a semi-supervised self-training approach based on open accessible satellite imagery for the city of Rio de Janeiro. We ran a negative binomial generalized linear regression model to evaluate the statistical significance of water tank density for modeling inner-urban Aedes Aegypti distribution measured by an entomological surveillance system between January 2019 and December 2021. Our proposed semi-supervised model outperformed a supervised model for water tank detection with respect to the F1-score by 22%. Water tank density was a significant predictor for the mean eggs per trap rate of Aedes Aegypti. This shows the potential of the proposed indicator to enrich urban entomological surveillance systems to plan more targeted vector control interventions, presumably leading to less infectious rates of dengue, Zika, and chikungunya in the future.
DOI:doi:10.1016/j.jag.2023.103304
URL:Bitte beachten Sie: Dies ist ein Bibliographieeintrag. Ein Volltextzugriff für Mitglieder der Universität besteht hier nur, falls für die entsprechende Zeitschrift/den entsprechenden Sammelband ein Abonnement besteht oder es sich um einen OpenAccess-Titel handelt.

Volltext: https://doi.org/10.1016/j.jag.2023.103304
 Volltext: https://www.sciencedirect.com/science/article/pii/S1569843223001267
 DOI: https://doi.org/10.1016/j.jag.2023.103304
Datenträger:Online-Ressource
Sprache:eng
Sach-SW:Aedes Aegypti
 Eco-epidemiology
 GeoAI
 Object detection
 Ovitrap
 Rio de Janeiro
 Semi-supervised self-training
 Urban health
 Vector control
 Water tank
K10plus-PPN:1850735204
Verknüpfungen:→ Zeitschrift

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