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Spatio-temporal analysis of the main dengue vector populations in Singapore

BACKGROUND: Despite the licensure of the world’s first dengue vaccine and the current development of additional vaccine candidates, successful Aedes control remains critical to the reduction of dengue virus transmission. To date, there is still limited literature that attempts to explain the spatio-...

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Autores principales: Sun, Haoyang, Dickens, Borame L, Richards, Daniel, Ong, Janet, Rajarethinam, Jayanthi, Hassim, Muhammad E. E., Lim, Jue Tao, Carrasco, L. Roman, Aik, Joel, Yap, Grace, Cook, Alex R., Ng, Lee Ching
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7802191/
https://www.ncbi.nlm.nih.gov/pubmed/33430945
http://dx.doi.org/10.1186/s13071-020-04554-9
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author Sun, Haoyang
Dickens, Borame L
Richards, Daniel
Ong, Janet
Rajarethinam, Jayanthi
Hassim, Muhammad E. E.
Lim, Jue Tao
Carrasco, L. Roman
Aik, Joel
Yap, Grace
Cook, Alex R.
Ng, Lee Ching
author_facet Sun, Haoyang
Dickens, Borame L
Richards, Daniel
Ong, Janet
Rajarethinam, Jayanthi
Hassim, Muhammad E. E.
Lim, Jue Tao
Carrasco, L. Roman
Aik, Joel
Yap, Grace
Cook, Alex R.
Ng, Lee Ching
author_sort Sun, Haoyang
collection PubMed
description BACKGROUND: Despite the licensure of the world’s first dengue vaccine and the current development of additional vaccine candidates, successful Aedes control remains critical to the reduction of dengue virus transmission. To date, there is still limited literature that attempts to explain the spatio-temporal population dynamics of Aedes mosquitoes within a single city, which hinders the development of more effective citywide vector control strategies. Narrowing this knowledge gap requires consistent and longitudinal measurement of Aedes abundance across the city as well as examination of relationships between variables on a much finer scale. METHODS: We utilized a high-resolution longitudinal dataset generated from Singapore’s islandwide Gravitrap surveillance system over a 2-year period and built a Bayesian hierarchical model to explain the spatio-temporal dynamics of Aedes aegypti and Aedes albopictus in relation to a wide range of environmental and anthropogenic variables. We also created a baseline during our model assessment to serve as a benchmark to be compared with the model’s out-of-sample prediction/forecast accuracy as measured by the mean absolute error. RESULTS: For both Aedes species, building age and nearby managed vegetation cover were found to have a significant positive association with the mean mosquito abundance, with the former being the strongest predictor. We also observed substantial evidence of a nonlinear effect of weekly maximum temperature on the Aedes abundance. Our models generally yielded modest but statistically significant reductions in the out-of-sample prediction/forecast error relative to the baseline. CONCLUSIONS: Our findings suggest that public residential estates with older buildings and more nearby managed vegetation should be prioritized for vector control inspections and community advocacy to reduce the abundance of Aedes mosquitoes and the risk of dengue transmission. [Image: see text]
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spelling pubmed-78021912021-01-13 Spatio-temporal analysis of the main dengue vector populations in Singapore Sun, Haoyang Dickens, Borame L Richards, Daniel Ong, Janet Rajarethinam, Jayanthi Hassim, Muhammad E. E. Lim, Jue Tao Carrasco, L. Roman Aik, Joel Yap, Grace Cook, Alex R. Ng, Lee Ching Parasit Vectors Research BACKGROUND: Despite the licensure of the world’s first dengue vaccine and the current development of additional vaccine candidates, successful Aedes control remains critical to the reduction of dengue virus transmission. To date, there is still limited literature that attempts to explain the spatio-temporal population dynamics of Aedes mosquitoes within a single city, which hinders the development of more effective citywide vector control strategies. Narrowing this knowledge gap requires consistent and longitudinal measurement of Aedes abundance across the city as well as examination of relationships between variables on a much finer scale. METHODS: We utilized a high-resolution longitudinal dataset generated from Singapore’s islandwide Gravitrap surveillance system over a 2-year period and built a Bayesian hierarchical model to explain the spatio-temporal dynamics of Aedes aegypti and Aedes albopictus in relation to a wide range of environmental and anthropogenic variables. We also created a baseline during our model assessment to serve as a benchmark to be compared with the model’s out-of-sample prediction/forecast accuracy as measured by the mean absolute error. RESULTS: For both Aedes species, building age and nearby managed vegetation cover were found to have a significant positive association with the mean mosquito abundance, with the former being the strongest predictor. We also observed substantial evidence of a nonlinear effect of weekly maximum temperature on the Aedes abundance. Our models generally yielded modest but statistically significant reductions in the out-of-sample prediction/forecast error relative to the baseline. CONCLUSIONS: Our findings suggest that public residential estates with older buildings and more nearby managed vegetation should be prioritized for vector control inspections and community advocacy to reduce the abundance of Aedes mosquitoes and the risk of dengue transmission. [Image: see text] BioMed Central 2021-01-11 /pmc/articles/PMC7802191/ /pubmed/33430945 http://dx.doi.org/10.1186/s13071-020-04554-9 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Sun, Haoyang
Dickens, Borame L
Richards, Daniel
Ong, Janet
Rajarethinam, Jayanthi
Hassim, Muhammad E. E.
Lim, Jue Tao
Carrasco, L. Roman
Aik, Joel
Yap, Grace
Cook, Alex R.
Ng, Lee Ching
Spatio-temporal analysis of the main dengue vector populations in Singapore
title Spatio-temporal analysis of the main dengue vector populations in Singapore
title_full Spatio-temporal analysis of the main dengue vector populations in Singapore
title_fullStr Spatio-temporal analysis of the main dengue vector populations in Singapore
title_full_unstemmed Spatio-temporal analysis of the main dengue vector populations in Singapore
title_short Spatio-temporal analysis of the main dengue vector populations in Singapore
title_sort spatio-temporal analysis of the main dengue vector populations in singapore
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7802191/
https://www.ncbi.nlm.nih.gov/pubmed/33430945
http://dx.doi.org/10.1186/s13071-020-04554-9
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