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Environmental determinants predicting population vulnerability to high yellow fever incidence
Yellow fever (YF) is an endemic mosquito-borne disease in Brazil, though many locations have not observed cases in recent decades. Some locations with low disease burden may resemble locations with higher disease burden through environmental and ecohydrological characteristics, which are known to im...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Royal Society
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8889195/ https://www.ncbi.nlm.nih.gov/pubmed/35316947 http://dx.doi.org/10.1098/rsos.220086 |
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author | Servadio, Joseph L. Muñoz-Zanzi, Claudia Convertino, Matteo |
author_facet | Servadio, Joseph L. Muñoz-Zanzi, Claudia Convertino, Matteo |
author_sort | Servadio, Joseph L. |
collection | PubMed |
description | Yellow fever (YF) is an endemic mosquito-borne disease in Brazil, though many locations have not observed cases in recent decades. Some locations with low disease burden may resemble locations with higher disease burden through environmental and ecohydrological characteristics, which are known to impact YF burden, motivating increased or continued prevention measures such as vaccination, mosquito control or surveillance. This study aimed to use environmental characteristics to estimate vulnerability to observing high YF burden among all Brazilian municipalities. Vulnerability was defined in three categories based on yearly incidence between 2000 and 2017: minimal, low and high vulnerability. A cumulative logit model was fit to these categories using environmental and ecohydrological predictors, selecting those that provided the most accurate model fit. Per cent of days with precipitation, mean temperature, biome, population density, elevation, vegetation and nearby disease occurrence were included in best-fitting models. Model results were applied to estimate vulnerability nationwide. Municipalities with highest probability of observing high vulnerability was found in the North and Central-West (2000–2016) as well as the Southeast (2017) regions. Results of this study serve to identify specific locations to prioritize new or ongoing surveillance and prevention of YF based on underlying ecohydrological conditions. |
format | Online Article Text |
id | pubmed-8889195 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | The Royal Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-88891952022-03-21 Environmental determinants predicting population vulnerability to high yellow fever incidence Servadio, Joseph L. Muñoz-Zanzi, Claudia Convertino, Matteo R Soc Open Sci Ecology, Conservation and Global Change Biology Yellow fever (YF) is an endemic mosquito-borne disease in Brazil, though many locations have not observed cases in recent decades. Some locations with low disease burden may resemble locations with higher disease burden through environmental and ecohydrological characteristics, which are known to impact YF burden, motivating increased or continued prevention measures such as vaccination, mosquito control or surveillance. This study aimed to use environmental characteristics to estimate vulnerability to observing high YF burden among all Brazilian municipalities. Vulnerability was defined in three categories based on yearly incidence between 2000 and 2017: minimal, low and high vulnerability. A cumulative logit model was fit to these categories using environmental and ecohydrological predictors, selecting those that provided the most accurate model fit. Per cent of days with precipitation, mean temperature, biome, population density, elevation, vegetation and nearby disease occurrence were included in best-fitting models. Model results were applied to estimate vulnerability nationwide. Municipalities with highest probability of observing high vulnerability was found in the North and Central-West (2000–2016) as well as the Southeast (2017) regions. Results of this study serve to identify specific locations to prioritize new or ongoing surveillance and prevention of YF based on underlying ecohydrological conditions. The Royal Society 2022-03-02 /pmc/articles/PMC8889195/ /pubmed/35316947 http://dx.doi.org/10.1098/rsos.220086 Text en © 2022 The Authors. https://creativecommons.org/licenses/by/4.0/Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, provided the original author and source are credited. |
spellingShingle | Ecology, Conservation and Global Change Biology Servadio, Joseph L. Muñoz-Zanzi, Claudia Convertino, Matteo Environmental determinants predicting population vulnerability to high yellow fever incidence |
title | Environmental determinants predicting population vulnerability to high yellow fever incidence |
title_full | Environmental determinants predicting population vulnerability to high yellow fever incidence |
title_fullStr | Environmental determinants predicting population vulnerability to high yellow fever incidence |
title_full_unstemmed | Environmental determinants predicting population vulnerability to high yellow fever incidence |
title_short | Environmental determinants predicting population vulnerability to high yellow fever incidence |
title_sort | environmental determinants predicting population vulnerability to high yellow fever incidence |
topic | Ecology, Conservation and Global Change Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8889195/ https://www.ncbi.nlm.nih.gov/pubmed/35316947 http://dx.doi.org/10.1098/rsos.220086 |
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