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

dc.contributor.authorAlawieh, Ali Mostafa
dc.contributor.authorSabra, Zahraa
dc.contributor.authorLangley, E. Farris
dc.contributor.authorBizri, Abdul Rahman N.
dc.contributor.authorHamadeh, Randa Sami
dc.contributor.authorZaraket, Fadi A.
dc.contributor.departmentDepartment of Electrical and Computer Engineering
dc.contributor.departmentInternal Medicine
dc.contributor.facultyMaroun Semaan Faculty of Engineering and Architecture (MSFEA)
dc.contributor.facultyFaculty of Medicine (FM)
dc.contributor.institutionAmerican University of Beirut
dc.date.accessioned2025-01-24T11:29:22Z
dc.date.available2025-01-24T11:29:22Z
dc.date.issued2017
dc.description.abstractBackground: 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. © 2017 The Author(s).
dc.identifier.doihttps://doi.org/10.1186/s12889-017-4909-0
dc.identifier.eid2-s2.0-85035080314
dc.identifier.pmid29178859
dc.identifier.urihttp://hdl.handle.net/10938/27200
dc.language.isoen
dc.publisherBioMed Central Ltd.
dc.relation.ispartofBMC Public Health
dc.sourceScopus
dc.subjectPoliomyelitis
dc.subjectStatistical model
dc.subjectSyrian war
dc.subjectVaccination campaign
dc.subjectVaccine
dc.subjectComputer simulation
dc.subjectDisease outbreaks
dc.subjectHumans
dc.subjectImmunization programs
dc.subjectLebanon
dc.subjectPoliovirus vaccines
dc.subjectPopulation surveillance
dc.subjectProgram evaluation
dc.subjectRefugees
dc.subjectSyria
dc.subjectPoliomyelitis vaccine
dc.subjectEpidemic
dc.subjectEthnology
dc.subjectHealth survey
dc.subjectHuman
dc.subjectPreventive health service
dc.subjectRefugee
dc.subjectStatistics and numerical data
dc.subjectSyrian arab republic
dc.titleAssessing the impact of the Lebanese National Polio Immunization Campaign using a population-based computational model
dc.typeArticle

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