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A statistical method utilizing information of imported cases to estimate the transmissibility for an influenza pandemic
BACKGROUND: In a new influenza pandemic, travel data such as arrival times of cases seeded by the originating country can be regarded as a combination of the epidemic size and the mobility networks of infections connecting the originating country with other regions. It can be a complete and timely s...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5320693/ https://www.ncbi.nlm.nih.gov/pubmed/28222682 http://dx.doi.org/10.1186/s12874-017-0300-1 |
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author | Chong, Ka Chun Zee, Benny Chung Ying Wang, Maggie Haitian |
author_facet | Chong, Ka Chun Zee, Benny Chung Ying Wang, Maggie Haitian |
author_sort | Chong, Ka Chun |
collection | PubMed |
description | BACKGROUND: In a new influenza pandemic, travel data such as arrival times of cases seeded by the originating country can be regarded as a combination of the epidemic size and the mobility networks of infections connecting the originating country with other regions. It can be a complete and timely source for estimating the basic reproduction number (R (0)), a key indicator of disease transmissibility. METHOD: In this study, we developed a likelihood-based method using arrival times of infected cases in different countries to estimate R (0) for influenza pandemics. A simulation was conducted to assess the performance of the proposed method. We further applied the method to the outbreak of the influenza pandemic A/H1N1 in Mexico. RESULTS: In the numerical application, the estimated R (0) was equal to 1.69 with a 95% confidence interval (1.65, 1.73). For the simulation results, the estimations were robust to the decline of travel rate and other parameter assumptions. Nevertheless, the estimates were moderately sensitive to the assumption of infectious duration. Generally, the findings were in line with other relevant studies. CONCLUSIONS: Our approach as well as the estimate is potential to assist officials in planning control and prevention measures. Improved coordination to streamline or even centralize surveillance of imported cases among countries will thus be beneficial to public health. |
format | Online Article Text |
id | pubmed-5320693 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-53206932017-02-24 A statistical method utilizing information of imported cases to estimate the transmissibility for an influenza pandemic Chong, Ka Chun Zee, Benny Chung Ying Wang, Maggie Haitian BMC Med Res Methodol Research Article BACKGROUND: In a new influenza pandemic, travel data such as arrival times of cases seeded by the originating country can be regarded as a combination of the epidemic size and the mobility networks of infections connecting the originating country with other regions. It can be a complete and timely source for estimating the basic reproduction number (R (0)), a key indicator of disease transmissibility. METHOD: In this study, we developed a likelihood-based method using arrival times of infected cases in different countries to estimate R (0) for influenza pandemics. A simulation was conducted to assess the performance of the proposed method. We further applied the method to the outbreak of the influenza pandemic A/H1N1 in Mexico. RESULTS: In the numerical application, the estimated R (0) was equal to 1.69 with a 95% confidence interval (1.65, 1.73). For the simulation results, the estimations were robust to the decline of travel rate and other parameter assumptions. Nevertheless, the estimates were moderately sensitive to the assumption of infectious duration. Generally, the findings were in line with other relevant studies. CONCLUSIONS: Our approach as well as the estimate is potential to assist officials in planning control and prevention measures. Improved coordination to streamline or even centralize surveillance of imported cases among countries will thus be beneficial to public health. BioMed Central 2017-02-21 /pmc/articles/PMC5320693/ /pubmed/28222682 http://dx.doi.org/10.1186/s12874-017-0300-1 Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Chong, Ka Chun Zee, Benny Chung Ying Wang, Maggie Haitian A statistical method utilizing information of imported cases to estimate the transmissibility for an influenza pandemic |
title | A statistical method utilizing information of imported cases to estimate the transmissibility for an influenza pandemic |
title_full | A statistical method utilizing information of imported cases to estimate the transmissibility for an influenza pandemic |
title_fullStr | A statistical method utilizing information of imported cases to estimate the transmissibility for an influenza pandemic |
title_full_unstemmed | A statistical method utilizing information of imported cases to estimate the transmissibility for an influenza pandemic |
title_short | A statistical method utilizing information of imported cases to estimate the transmissibility for an influenza pandemic |
title_sort | statistical method utilizing information of imported cases to estimate the transmissibility for an influenza pandemic |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5320693/ https://www.ncbi.nlm.nih.gov/pubmed/28222682 http://dx.doi.org/10.1186/s12874-017-0300-1 |
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