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Assessing the impact of the Lebanese National Polio Immunization Campaign using a population-based computational model

BACKGROUND: After the re-introduction of poliovirus to Syria in 2013, Lebanon was considered at high transmission risk due to its proximity to Syria and the high number of Syrian refugees. However, after a large-scale national immunization initiative, Lebanon was able to prevent a potential outbreak...

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Autores principales: Alawieh, Ali, Sabra, Zahraa, Langley, E. Farris, Bizri, Abdul Rahman, Hamadeh, Randa, Zaraket, Fadi A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5702188/
https://www.ncbi.nlm.nih.gov/pubmed/29178859
http://dx.doi.org/10.1186/s12889-017-4909-0
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author Alawieh, Ali
Sabra, Zahraa
Langley, E. Farris
Bizri, Abdul Rahman
Hamadeh, Randa
Zaraket, Fadi A.
author_facet Alawieh, Ali
Sabra, Zahraa
Langley, E. Farris
Bizri, Abdul Rahman
Hamadeh, Randa
Zaraket, Fadi A.
author_sort Alawieh, Ali
collection PubMed
description BACKGROUND: After the re-introduction of poliovirus to Syria in 2013, Lebanon was considered at high transmission risk due to its proximity to Syria and the high number of Syrian refugees. However, after a large-scale national immunization initiative, Lebanon was able to prevent a potential outbreak of polio among nationals and refugees. In this work, we used a computational individual-simulation model to assess the risk of poliovirus threat to Lebanon prior and after the immunization campaign and to quantitatively assess the healthcare impact of the campaign and the required standards that need to be maintained nationally to prevent a future outbreak. METHODS: Acute poliomyelitis surveillance in Lebanon was along with the design and coverage rate of the recent national polio immunization campaign were reviewed from the records of the Lebanese Ministry of Public Health. Lebanese population demographics including Syrian and Palestinian refugees were reviewed to design individual-based models that predicts the consequences of polio spread to Lebanon and evaluate the outcome of immunization campaigns. The model takes into account geographic, demographic and health-related features. RESULTS: Our simulations confirmed the high risk of polio outbreaks in Lebanon within 10 days of case introduction prior to the immunization campaign, and showed that the current immunization campaign significantly reduced the speed of the infection in the event poliomyelitis cases enter the country. A minimum of 90% national immunization coverage was found to be required to prevent exponential propagation of potential transmission. CONCLUSIONS: Both surveillance and immunization efforts should be maintained at high standards in Lebanon and other countries in the area to detect and limit any potential outbreak. The use of computational population simulation models can provide a quantitative approach to assess the impact of immunization campaigns and the burden of infectious diseases even in the context of population migration.
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spelling pubmed-57021882017-12-04 Assessing the impact of the Lebanese National Polio Immunization Campaign using a population-based computational model Alawieh, Ali Sabra, Zahraa Langley, E. Farris Bizri, Abdul Rahman Hamadeh, Randa Zaraket, Fadi A. BMC Public Health Research Article BACKGROUND: After the re-introduction of poliovirus to Syria in 2013, Lebanon was considered at high transmission risk due to its proximity to Syria and the high number of Syrian refugees. However, after a large-scale national immunization initiative, Lebanon was able to prevent a potential outbreak of polio among nationals and refugees. In this work, we used a computational individual-simulation model to assess the risk of poliovirus threat to Lebanon prior and after the immunization campaign and to quantitatively assess the healthcare impact of the campaign and the required standards that need to be maintained nationally to prevent a future outbreak. METHODS: Acute poliomyelitis surveillance in Lebanon was along with the design and coverage rate of the recent national polio immunization campaign were reviewed from the records of the Lebanese Ministry of Public Health. Lebanese population demographics including Syrian and Palestinian refugees were reviewed to design individual-based models that predicts the consequences of polio spread to Lebanon and evaluate the outcome of immunization campaigns. The model takes into account geographic, demographic and health-related features. RESULTS: Our simulations confirmed the high risk of polio outbreaks in Lebanon within 10 days of case introduction prior to the immunization campaign, and showed that the current immunization campaign significantly reduced the speed of the infection in the event poliomyelitis cases enter the country. A minimum of 90% national immunization coverage was found to be required to prevent exponential propagation of potential transmission. CONCLUSIONS: Both surveillance and immunization efforts should be maintained at high standards in Lebanon and other countries in the area to detect and limit any potential outbreak. The use of computational population simulation models can provide a quantitative approach to assess the impact of immunization campaigns and the burden of infectious diseases even in the context of population migration. BioMed Central 2017-11-25 /pmc/articles/PMC5702188/ /pubmed/29178859 http://dx.doi.org/10.1186/s12889-017-4909-0 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
Alawieh, Ali
Sabra, Zahraa
Langley, E. Farris
Bizri, Abdul Rahman
Hamadeh, Randa
Zaraket, Fadi A.
Assessing the impact of the Lebanese National Polio Immunization Campaign using a population-based computational model
title Assessing the impact of the Lebanese National Polio Immunization Campaign using a population-based computational model
title_full Assessing the impact of the Lebanese National Polio Immunization Campaign using a population-based computational model
title_fullStr Assessing the impact of the Lebanese National Polio Immunization Campaign using a population-based computational model
title_full_unstemmed Assessing the impact of the Lebanese National Polio Immunization Campaign using a population-based computational model
title_short Assessing the impact of the Lebanese National Polio Immunization Campaign using a population-based computational model
title_sort assessing the impact of the lebanese national polio immunization campaign using a population-based computational model
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5702188/
https://www.ncbi.nlm.nih.gov/pubmed/29178859
http://dx.doi.org/10.1186/s12889-017-4909-0
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