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Urbanization affects peak timing, prevalence, and bimodality of influenza pandemics in Australia: Results of a census-calibrated model
We examine salient trends of influenza pandemics in Australia, a rapidly urbanizing nation. To do so, we implement state-of-the-art influenza transmission and progression models within a large-scale stochastic computer simulation, generated using comprehensive Australian census datasets from 2006, 2...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Association for the Advancement of Science
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6291314/ https://www.ncbi.nlm.nih.gov/pubmed/30547086 http://dx.doi.org/10.1126/sciadv.aau5294 |
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author | Zachreson, Cameron Fair, Kristopher M. Cliff, Oliver M. Harding, Nathan Piraveenan, Mahendra Prokopenko, Mikhail |
author_facet | Zachreson, Cameron Fair, Kristopher M. Cliff, Oliver M. Harding, Nathan Piraveenan, Mahendra Prokopenko, Mikhail |
author_sort | Zachreson, Cameron |
collection | PubMed |
description | We examine salient trends of influenza pandemics in Australia, a rapidly urbanizing nation. To do so, we implement state-of-the-art influenza transmission and progression models within a large-scale stochastic computer simulation, generated using comprehensive Australian census datasets from 2006, 2011, and 2016. Our results offer a simulation-based investigation of a population’s sensitivity to pandemics across multiple historical time points and highlight three notable trends in pandemic patterns over the years: increased peak prevalence, faster spreading rates, and decreasing spatiotemporal bimodality. We attribute these pandemic trends to increases in two key quantities indicative of urbanization: the population fraction residing in major cities and international air traffic. In addition, we identify features of the pandemic’s geographic spread that we attribute to changes in the commuter mobility network. The generic nature of our model and the ubiquity of urbanization trends around the world make it likely for our results to be applicable in other rapidly urbanizing nations. |
format | Online Article Text |
id | pubmed-6291314 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | American Association for the Advancement of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-62913142018-12-13 Urbanization affects peak timing, prevalence, and bimodality of influenza pandemics in Australia: Results of a census-calibrated model Zachreson, Cameron Fair, Kristopher M. Cliff, Oliver M. Harding, Nathan Piraveenan, Mahendra Prokopenko, Mikhail Sci Adv Research Articles We examine salient trends of influenza pandemics in Australia, a rapidly urbanizing nation. To do so, we implement state-of-the-art influenza transmission and progression models within a large-scale stochastic computer simulation, generated using comprehensive Australian census datasets from 2006, 2011, and 2016. Our results offer a simulation-based investigation of a population’s sensitivity to pandemics across multiple historical time points and highlight three notable trends in pandemic patterns over the years: increased peak prevalence, faster spreading rates, and decreasing spatiotemporal bimodality. We attribute these pandemic trends to increases in two key quantities indicative of urbanization: the population fraction residing in major cities and international air traffic. In addition, we identify features of the pandemic’s geographic spread that we attribute to changes in the commuter mobility network. The generic nature of our model and the ubiquity of urbanization trends around the world make it likely for our results to be applicable in other rapidly urbanizing nations. American Association for the Advancement of Science 2018-12-12 /pmc/articles/PMC6291314/ /pubmed/30547086 http://dx.doi.org/10.1126/sciadv.aau5294 Text en Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC). http://creativecommons.org/licenses/by-nc/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial license (http://creativecommons.org/licenses/by-nc/4.0/) , which permits use, distribution, and reproduction in any medium, so long as the resultant use is not for commercial advantage and provided the original work is properly cited. |
spellingShingle | Research Articles Zachreson, Cameron Fair, Kristopher M. Cliff, Oliver M. Harding, Nathan Piraveenan, Mahendra Prokopenko, Mikhail Urbanization affects peak timing, prevalence, and bimodality of influenza pandemics in Australia: Results of a census-calibrated model |
title | Urbanization affects peak timing, prevalence, and bimodality of influenza pandemics in Australia: Results of a census-calibrated model |
title_full | Urbanization affects peak timing, prevalence, and bimodality of influenza pandemics in Australia: Results of a census-calibrated model |
title_fullStr | Urbanization affects peak timing, prevalence, and bimodality of influenza pandemics in Australia: Results of a census-calibrated model |
title_full_unstemmed | Urbanization affects peak timing, prevalence, and bimodality of influenza pandemics in Australia: Results of a census-calibrated model |
title_short | Urbanization affects peak timing, prevalence, and bimodality of influenza pandemics in Australia: Results of a census-calibrated model |
title_sort | urbanization affects peak timing, prevalence, and bimodality of influenza pandemics in australia: results of a census-calibrated model |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6291314/ https://www.ncbi.nlm.nih.gov/pubmed/30547086 http://dx.doi.org/10.1126/sciadv.aau5294 |
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