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Effects of reactive social distancing on the 1918 influenza pandemic
The 1918 influenza pandemic was characterized by multiple epidemic waves. We investigated reactive social distancing, a form of behavioral response where individuals avoid potentially infectious contacts in response to available information on an ongoing epidemic or pandemic. We modelled its effects...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5507503/ https://www.ncbi.nlm.nih.gov/pubmed/28704460 http://dx.doi.org/10.1371/journal.pone.0180545 |
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author | Yu, Duo Lin, Qianying Chiu, Alice PY He, Daihai |
author_facet | Yu, Duo Lin, Qianying Chiu, Alice PY He, Daihai |
author_sort | Yu, Duo |
collection | PubMed |
description | The 1918 influenza pandemic was characterized by multiple epidemic waves. We investigated reactive social distancing, a form of behavioral response where individuals avoid potentially infectious contacts in response to available information on an ongoing epidemic or pandemic. We modelled its effects on the three influenza waves in the United Kingdom. In previous studies, human behavioral response was modelled by a Power function of the proportion of recent influenza mortality in a population, and by a Hill function, which is a function of the number of recent influenza mortality. Using a simple epidemic model with a Power function and one common set of parameters, we provided a good model fit for the observed multiple epidemic waves in London boroughs, Birmingham and Liverpool. We further applied the model parameters from these three cities to all 334 administrative units in England and Wales and including the population sizes of individual administrative units. We computed the Pearson’s correlation between the observed and simulated for each administrative unit. We found a median correlation of 0.636, indicating that our model predictions are performing reasonably well. Our modelling approach is an improvement from previous studies where separate models are fitted to each city. With the reduced number of model parameters used, we achieved computational efficiency gain without over-fitting the model. We also showed the importance of reactive behavioral distancing as a potential non-pharmaceutical intervention during an influenza pandemic. Our work has both scientific and public health significance. |
format | Online Article Text |
id | pubmed-5507503 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-55075032017-07-25 Effects of reactive social distancing on the 1918 influenza pandemic Yu, Duo Lin, Qianying Chiu, Alice PY He, Daihai PLoS One Research Article The 1918 influenza pandemic was characterized by multiple epidemic waves. We investigated reactive social distancing, a form of behavioral response where individuals avoid potentially infectious contacts in response to available information on an ongoing epidemic or pandemic. We modelled its effects on the three influenza waves in the United Kingdom. In previous studies, human behavioral response was modelled by a Power function of the proportion of recent influenza mortality in a population, and by a Hill function, which is a function of the number of recent influenza mortality. Using a simple epidemic model with a Power function and one common set of parameters, we provided a good model fit for the observed multiple epidemic waves in London boroughs, Birmingham and Liverpool. We further applied the model parameters from these three cities to all 334 administrative units in England and Wales and including the population sizes of individual administrative units. We computed the Pearson’s correlation between the observed and simulated for each administrative unit. We found a median correlation of 0.636, indicating that our model predictions are performing reasonably well. Our modelling approach is an improvement from previous studies where separate models are fitted to each city. With the reduced number of model parameters used, we achieved computational efficiency gain without over-fitting the model. We also showed the importance of reactive behavioral distancing as a potential non-pharmaceutical intervention during an influenza pandemic. Our work has both scientific and public health significance. Public Library of Science 2017-07-12 /pmc/articles/PMC5507503/ /pubmed/28704460 http://dx.doi.org/10.1371/journal.pone.0180545 Text en © 2017 Yu 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 Yu, Duo Lin, Qianying Chiu, Alice PY He, Daihai Effects of reactive social distancing on the 1918 influenza pandemic |
title | Effects of reactive social distancing on the 1918 influenza pandemic |
title_full | Effects of reactive social distancing on the 1918 influenza pandemic |
title_fullStr | Effects of reactive social distancing on the 1918 influenza pandemic |
title_full_unstemmed | Effects of reactive social distancing on the 1918 influenza pandemic |
title_short | Effects of reactive social distancing on the 1918 influenza pandemic |
title_sort | effects of reactive social distancing on the 1918 influenza pandemic |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5507503/ https://www.ncbi.nlm.nih.gov/pubmed/28704460 http://dx.doi.org/10.1371/journal.pone.0180545 |
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