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Modeling and Predicting Dengue Incidence in Highly Vulnerable Countries using Panel Data Approach

The spread of dengue has become a major public health concern in recent times due to alarming climate change. Using country level panel data over the 2000–2017 period, this paper examines the effects of climate change and socio-economic variables on the incidence of dengue-borne diseases in some of...

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Autores principales: Anwar, Asim, Khan, Noman, Ayub, Muhammad, Nawaz, Faisal, Shah, Asim, Flahault, Antoine
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6650977/
https://www.ncbi.nlm.nih.gov/pubmed/31261672
http://dx.doi.org/10.3390/ijerph16132296
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author Anwar, Asim
Khan, Noman
Ayub, Muhammad
Nawaz, Faisal
Shah, Asim
Flahault, Antoine
author_facet Anwar, Asim
Khan, Noman
Ayub, Muhammad
Nawaz, Faisal
Shah, Asim
Flahault, Antoine
author_sort Anwar, Asim
collection PubMed
description The spread of dengue has become a major public health concern in recent times due to alarming climate change. Using country level panel data over the 2000–2017 period, this paper examines the effects of climate change and socio-economic variables on the incidence of dengue-borne diseases in some of the most highly vulnerable countries. Empirical analysis shows a positive association between climate change and socio-economic conditions in the advent of dengue-borne diseases. We find that climate change, as measured by temperature, is proactively contributing to the spread of dengue-borne diseases. However, redressing the contributive factor behind climate change, via better awareness through education and improved public health facilitation, can assist in managing the occurrences and spread of dengue-borne diseases.
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spelling pubmed-66509772019-08-07 Modeling and Predicting Dengue Incidence in Highly Vulnerable Countries using Panel Data Approach Anwar, Asim Khan, Noman Ayub, Muhammad Nawaz, Faisal Shah, Asim Flahault, Antoine Int J Environ Res Public Health Article The spread of dengue has become a major public health concern in recent times due to alarming climate change. Using country level panel data over the 2000–2017 period, this paper examines the effects of climate change and socio-economic variables on the incidence of dengue-borne diseases in some of the most highly vulnerable countries. Empirical analysis shows a positive association between climate change and socio-economic conditions in the advent of dengue-borne diseases. We find that climate change, as measured by temperature, is proactively contributing to the spread of dengue-borne diseases. However, redressing the contributive factor behind climate change, via better awareness through education and improved public health facilitation, can assist in managing the occurrences and spread of dengue-borne diseases. MDPI 2019-06-28 2019-07 /pmc/articles/PMC6650977/ /pubmed/31261672 http://dx.doi.org/10.3390/ijerph16132296 Text en © 2019 by the authors. 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 (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Anwar, Asim
Khan, Noman
Ayub, Muhammad
Nawaz, Faisal
Shah, Asim
Flahault, Antoine
Modeling and Predicting Dengue Incidence in Highly Vulnerable Countries using Panel Data Approach
title Modeling and Predicting Dengue Incidence in Highly Vulnerable Countries using Panel Data Approach
title_full Modeling and Predicting Dengue Incidence in Highly Vulnerable Countries using Panel Data Approach
title_fullStr Modeling and Predicting Dengue Incidence in Highly Vulnerable Countries using Panel Data Approach
title_full_unstemmed Modeling and Predicting Dengue Incidence in Highly Vulnerable Countries using Panel Data Approach
title_short Modeling and Predicting Dengue Incidence in Highly Vulnerable Countries using Panel Data Approach
title_sort modeling and predicting dengue incidence in highly vulnerable countries using panel data approach
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6650977/
https://www.ncbi.nlm.nih.gov/pubmed/31261672
http://dx.doi.org/10.3390/ijerph16132296
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