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Entomo-Virological Aedes aegypti Surveillance Applied for Prediction of Dengue Transmission: A Spatio-Temporal Modeling Study

Currently, DENV transmitted primarily by Aedes aegypti affects approximately one in three people annually. The spatio-temporal heterogeneity of vector infestation and the intensity of arbovirus transmission require surveillance capable of predicting an outbreak. In this work, we used data from 4 yea...

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Autores principales: Leandro, André de Souza, Ayala, Mario J. C., Lopes, Renata Defante, Martins, Caroline Amaral, Maciel-de-Freitas, Rafael, Villela, Daniel A. M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9861664/
https://www.ncbi.nlm.nih.gov/pubmed/36678352
http://dx.doi.org/10.3390/pathogens12010004
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author Leandro, André de Souza
Ayala, Mario J. C.
Lopes, Renata Defante
Martins, Caroline Amaral
Maciel-de-Freitas, Rafael
Villela, Daniel A. M.
author_facet Leandro, André de Souza
Ayala, Mario J. C.
Lopes, Renata Defante
Martins, Caroline Amaral
Maciel-de-Freitas, Rafael
Villela, Daniel A. M.
author_sort Leandro, André de Souza
collection PubMed
description Currently, DENV transmitted primarily by Aedes aegypti affects approximately one in three people annually. The spatio-temporal heterogeneity of vector infestation and the intensity of arbovirus transmission require surveillance capable of predicting an outbreak. In this work, we used data from 4 years of reported dengue cases and entomological indicators of adult Aedes collected from approximately 3500 traps installed in the city of Foz do Iguaçu, Brazil, to evaluate the spatial and temporal association between vector infestation and the occurrence of dengue cases. Entomological (TPI, ADI and MII) and entomo-virological (EVI) indexes were generated with the goal to provide local health managers with a transmission risk stratification that allows targeting areas for vector control activities. We observed a dynamic pattern in the evaluation; however, it was a low spatio-temporal correlation of Ae. aegypti and incidence of dengue. Independent temporal and spatial effects capture a significant portion of the signal given by human arbovirus cases. The entomo-virological index (EVI) significantly signaled risk in a few areas, whereas entomological indexes were not effective in providing dengue risk alert. Investigating the variation of biotic and abiotic factors between areas with and without correlation should provide more information about the local epidemiology of dengue.
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spelling pubmed-98616642023-01-22 Entomo-Virological Aedes aegypti Surveillance Applied for Prediction of Dengue Transmission: A Spatio-Temporal Modeling Study Leandro, André de Souza Ayala, Mario J. C. Lopes, Renata Defante Martins, Caroline Amaral Maciel-de-Freitas, Rafael Villela, Daniel A. M. Pathogens Article Currently, DENV transmitted primarily by Aedes aegypti affects approximately one in three people annually. The spatio-temporal heterogeneity of vector infestation and the intensity of arbovirus transmission require surveillance capable of predicting an outbreak. In this work, we used data from 4 years of reported dengue cases and entomological indicators of adult Aedes collected from approximately 3500 traps installed in the city of Foz do Iguaçu, Brazil, to evaluate the spatial and temporal association between vector infestation and the occurrence of dengue cases. Entomological (TPI, ADI and MII) and entomo-virological (EVI) indexes were generated with the goal to provide local health managers with a transmission risk stratification that allows targeting areas for vector control activities. We observed a dynamic pattern in the evaluation; however, it was a low spatio-temporal correlation of Ae. aegypti and incidence of dengue. Independent temporal and spatial effects capture a significant portion of the signal given by human arbovirus cases. The entomo-virological index (EVI) significantly signaled risk in a few areas, whereas entomological indexes were not effective in providing dengue risk alert. Investigating the variation of biotic and abiotic factors between areas with and without correlation should provide more information about the local epidemiology of dengue. MDPI 2022-12-20 /pmc/articles/PMC9861664/ /pubmed/36678352 http://dx.doi.org/10.3390/pathogens12010004 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Leandro, André de Souza
Ayala, Mario J. C.
Lopes, Renata Defante
Martins, Caroline Amaral
Maciel-de-Freitas, Rafael
Villela, Daniel A. M.
Entomo-Virological Aedes aegypti Surveillance Applied for Prediction of Dengue Transmission: A Spatio-Temporal Modeling Study
title Entomo-Virological Aedes aegypti Surveillance Applied for Prediction of Dengue Transmission: A Spatio-Temporal Modeling Study
title_full Entomo-Virological Aedes aegypti Surveillance Applied for Prediction of Dengue Transmission: A Spatio-Temporal Modeling Study
title_fullStr Entomo-Virological Aedes aegypti Surveillance Applied for Prediction of Dengue Transmission: A Spatio-Temporal Modeling Study
title_full_unstemmed Entomo-Virological Aedes aegypti Surveillance Applied for Prediction of Dengue Transmission: A Spatio-Temporal Modeling Study
title_short Entomo-Virological Aedes aegypti Surveillance Applied for Prediction of Dengue Transmission: A Spatio-Temporal Modeling Study
title_sort entomo-virological aedes aegypti surveillance applied for prediction of dengue transmission: a spatio-temporal modeling study
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9861664/
https://www.ncbi.nlm.nih.gov/pubmed/36678352
http://dx.doi.org/10.3390/pathogens12010004
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