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A data fusion approach to the estimation of temporary populations: An application to Australia
This study establishes a new method for estimating the monthly Average Population Present (APP) in Australian regions. Conventional population statistics, which enumerate people where they usually live, ignore the significant spatial mobility driving short term shifts in population numbers. Estimate...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8584718/ https://www.ncbi.nlm.nih.gov/pubmed/34762671 http://dx.doi.org/10.1371/journal.pone.0259377 |
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author | Charles-Edwards, Elin Corcoran, Jonathan Loginova, Julia Panczak, Radoslaw White, Gentry Whitehead, Alexander |
author_facet | Charles-Edwards, Elin Corcoran, Jonathan Loginova, Julia Panczak, Radoslaw White, Gentry Whitehead, Alexander |
author_sort | Charles-Edwards, Elin |
collection | PubMed |
description | This study establishes a new method for estimating the monthly Average Population Present (APP) in Australian regions. Conventional population statistics, which enumerate people where they usually live, ignore the significant spatial mobility driving short term shifts in population numbers. Estimates of the temporary or ambient population of a region have several important applications including the provision of goods and services, emergency preparedness and serve as more appropriate denominators for a range of social statistics. This paper develops a flexible modelling framework to generate APP estimates from an integrated suite of conventional and novel data sources. The resultant APP estimates reveal the considerable seasonality in small area populations across Australia’s regions alongside the contribution of domestic and international visitors as well as absent residents to the observed monthly variations. The modelling framework developed in the paper is conceived in a manner such that it can be adapted and re-deployed both for use with alternative data sources as well as other situational contexts for the estimation of temporary populations. |
format | Online Article Text |
id | pubmed-8584718 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-85847182021-11-12 A data fusion approach to the estimation of temporary populations: An application to Australia Charles-Edwards, Elin Corcoran, Jonathan Loginova, Julia Panczak, Radoslaw White, Gentry Whitehead, Alexander PLoS One Research Article This study establishes a new method for estimating the monthly Average Population Present (APP) in Australian regions. Conventional population statistics, which enumerate people where they usually live, ignore the significant spatial mobility driving short term shifts in population numbers. Estimates of the temporary or ambient population of a region have several important applications including the provision of goods and services, emergency preparedness and serve as more appropriate denominators for a range of social statistics. This paper develops a flexible modelling framework to generate APP estimates from an integrated suite of conventional and novel data sources. The resultant APP estimates reveal the considerable seasonality in small area populations across Australia’s regions alongside the contribution of domestic and international visitors as well as absent residents to the observed monthly variations. The modelling framework developed in the paper is conceived in a manner such that it can be adapted and re-deployed both for use with alternative data sources as well as other situational contexts for the estimation of temporary populations. Public Library of Science 2021-11-11 /pmc/articles/PMC8584718/ /pubmed/34762671 http://dx.doi.org/10.1371/journal.pone.0259377 Text en © 2021 Charles-Edwards et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://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 Charles-Edwards, Elin Corcoran, Jonathan Loginova, Julia Panczak, Radoslaw White, Gentry Whitehead, Alexander A data fusion approach to the estimation of temporary populations: An application to Australia |
title | A data fusion approach to the estimation of temporary populations: An application to Australia |
title_full | A data fusion approach to the estimation of temporary populations: An application to Australia |
title_fullStr | A data fusion approach to the estimation of temporary populations: An application to Australia |
title_full_unstemmed | A data fusion approach to the estimation of temporary populations: An application to Australia |
title_short | A data fusion approach to the estimation of temporary populations: An application to Australia |
title_sort | data fusion approach to the estimation of temporary populations: an application to australia |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8584718/ https://www.ncbi.nlm.nih.gov/pubmed/34762671 http://dx.doi.org/10.1371/journal.pone.0259377 |
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