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Validation of the Gravity Model in Predicting the Global Spread of Influenza
The gravity model is often used in predicting the spread of influenza. We use the data of influenza A (H1N1) to check the model’s performance and validation, in order to determine the scope of its application. In this article, we proposed to model the pattern of global spread of the virus via a few...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Molecular Diversity Preservation International (MDPI)
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3166731/ https://www.ncbi.nlm.nih.gov/pubmed/21909295 http://dx.doi.org/10.3390/ijerph8083134 |
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author | Li, Xinhai Tian, Huidong Lai, Dejian Zhang, Zhibin |
author_facet | Li, Xinhai Tian, Huidong Lai, Dejian Zhang, Zhibin |
author_sort | Li, Xinhai |
collection | PubMed |
description | The gravity model is often used in predicting the spread of influenza. We use the data of influenza A (H1N1) to check the model’s performance and validation, in order to determine the scope of its application. In this article, we proposed to model the pattern of global spread of the virus via a few important socio-economic indicators. We applied the epidemic gravity model for modelling the virus spread globally through the estimation of parameters of a generalized linear model. We compiled the daily confirmed cases of influenza A (H1N1) in each country as reported to the WHO and each state in the USA, and established the model to describe the relationship between the confirmed cases and socio-economic factors such as population size, per capita gross domestic production (GDP), and the distance between the countries/states and the country where the first confirmed case was reported (i.e., Mexico). The covariates we selected for the model were all statistically significantly associated with the global spread of influenza A (H1N1). However, within the USA, the distance and GDP were not significantly associated with the number of confirmed cases. The combination of the gravity model and generalized linear model provided a quick assessment of pandemic spread globally. The gravity model is valid if the spread period is long enough for estimating the model parameters. Meanwhile, the distance between donor and recipient communities has a good gradient. Besides, the spread should be at the early stage if a single source is taking into account. |
format | Online Article Text |
id | pubmed-3166731 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | Molecular Diversity Preservation International (MDPI) |
record_format | MEDLINE/PubMed |
spelling | pubmed-31667312011-09-09 Validation of the Gravity Model in Predicting the Global Spread of Influenza Li, Xinhai Tian, Huidong Lai, Dejian Zhang, Zhibin Int J Environ Res Public Health Article The gravity model is often used in predicting the spread of influenza. We use the data of influenza A (H1N1) to check the model’s performance and validation, in order to determine the scope of its application. In this article, we proposed to model the pattern of global spread of the virus via a few important socio-economic indicators. We applied the epidemic gravity model for modelling the virus spread globally through the estimation of parameters of a generalized linear model. We compiled the daily confirmed cases of influenza A (H1N1) in each country as reported to the WHO and each state in the USA, and established the model to describe the relationship between the confirmed cases and socio-economic factors such as population size, per capita gross domestic production (GDP), and the distance between the countries/states and the country where the first confirmed case was reported (i.e., Mexico). The covariates we selected for the model were all statistically significantly associated with the global spread of influenza A (H1N1). However, within the USA, the distance and GDP were not significantly associated with the number of confirmed cases. The combination of the gravity model and generalized linear model provided a quick assessment of pandemic spread globally. The gravity model is valid if the spread period is long enough for estimating the model parameters. Meanwhile, the distance between donor and recipient communities has a good gradient. Besides, the spread should be at the early stage if a single source is taking into account. Molecular Diversity Preservation International (MDPI) 2011-08 2011-07-25 /pmc/articles/PMC3166731/ /pubmed/21909295 http://dx.doi.org/10.3390/ijerph8083134 Text en © 2011 by the authors; licensee MDPI, Basel, Switzerland. http://creativecommons.org/licenses/by/3.0 This article is an open-access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/). |
spellingShingle | Article Li, Xinhai Tian, Huidong Lai, Dejian Zhang, Zhibin Validation of the Gravity Model in Predicting the Global Spread of Influenza |
title | Validation of the Gravity Model in Predicting the Global Spread of Influenza |
title_full | Validation of the Gravity Model in Predicting the Global Spread of Influenza |
title_fullStr | Validation of the Gravity Model in Predicting the Global Spread of Influenza |
title_full_unstemmed | Validation of the Gravity Model in Predicting the Global Spread of Influenza |
title_short | Validation of the Gravity Model in Predicting the Global Spread of Influenza |
title_sort | validation of the gravity model in predicting the global spread of influenza |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3166731/ https://www.ncbi.nlm.nih.gov/pubmed/21909295 http://dx.doi.org/10.3390/ijerph8083134 |
work_keys_str_mv | AT lixinhai validationofthegravitymodelinpredictingtheglobalspreadofinfluenza AT tianhuidong validationofthegravitymodelinpredictingtheglobalspreadofinfluenza AT laidejian validationofthegravitymodelinpredictingtheglobalspreadofinfluenza AT zhangzhibin validationofthegravitymodelinpredictingtheglobalspreadofinfluenza |