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A global model for predicting the arrival of imported dengue infections
With approximately half of the world’s population at risk of contracting dengue, this mosquito-borne disease is of global concern. International travellers significantly contribute to dengue’s rapid and large-scale spread by importing the disease from endemic into non-endemic countries. To prevent f...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6892502/ https://www.ncbi.nlm.nih.gov/pubmed/31800583 http://dx.doi.org/10.1371/journal.pone.0225193 |
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author | Liebig, Jessica Jansen, Cassie Paini, Dean Gardner, Lauren Jurdak, Raja |
author_facet | Liebig, Jessica Jansen, Cassie Paini, Dean Gardner, Lauren Jurdak, Raja |
author_sort | Liebig, Jessica |
collection | PubMed |
description | With approximately half of the world’s population at risk of contracting dengue, this mosquito-borne disease is of global concern. International travellers significantly contribute to dengue’s rapid and large-scale spread by importing the disease from endemic into non-endemic countries. To prevent future outbreaks and dengue from establishing in non-endemic countries, knowledge about the arrival time and location of infected travellers is crucial. We propose a network model that predicts the monthly number of dengue-infected air passengers arriving at any given airport. We consider international air travel volumes to construct weighted networks, representing passenger flows between airports. We further calculate the probability of passengers, who travel through the international air transport network, being infected with dengue. The probability of being infected depends on the destination, duration and timing of travel. Our findings shed light onto dengue importation routes and reveal country-specific reporting rates that have been until now largely unknown. This paper provides important new knowledge about the spreading dynamics of dengue that is highly beneficial for public health authorities to strategically allocate the often limited resources to more efficiently prevent the spread of dengue. |
format | Online Article Text |
id | pubmed-6892502 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-68925022019-12-14 A global model for predicting the arrival of imported dengue infections Liebig, Jessica Jansen, Cassie Paini, Dean Gardner, Lauren Jurdak, Raja PLoS One Research Article With approximately half of the world’s population at risk of contracting dengue, this mosquito-borne disease is of global concern. International travellers significantly contribute to dengue’s rapid and large-scale spread by importing the disease from endemic into non-endemic countries. To prevent future outbreaks and dengue from establishing in non-endemic countries, knowledge about the arrival time and location of infected travellers is crucial. We propose a network model that predicts the monthly number of dengue-infected air passengers arriving at any given airport. We consider international air travel volumes to construct weighted networks, representing passenger flows between airports. We further calculate the probability of passengers, who travel through the international air transport network, being infected with dengue. The probability of being infected depends on the destination, duration and timing of travel. Our findings shed light onto dengue importation routes and reveal country-specific reporting rates that have been until now largely unknown. This paper provides important new knowledge about the spreading dynamics of dengue that is highly beneficial for public health authorities to strategically allocate the often limited resources to more efficiently prevent the spread of dengue. Public Library of Science 2019-12-04 /pmc/articles/PMC6892502/ /pubmed/31800583 http://dx.doi.org/10.1371/journal.pone.0225193 Text en © 2019 Liebig et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Liebig, Jessica Jansen, Cassie Paini, Dean Gardner, Lauren Jurdak, Raja A global model for predicting the arrival of imported dengue infections |
title | A global model for predicting the arrival of imported dengue infections |
title_full | A global model for predicting the arrival of imported dengue infections |
title_fullStr | A global model for predicting the arrival of imported dengue infections |
title_full_unstemmed | A global model for predicting the arrival of imported dengue infections |
title_short | A global model for predicting the arrival of imported dengue infections |
title_sort | global model for predicting the arrival of imported dengue infections |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6892502/ https://www.ncbi.nlm.nih.gov/pubmed/31800583 http://dx.doi.org/10.1371/journal.pone.0225193 |
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