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

Overview of attention for article published in BMC Public Health, November 2017
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Title
Assessing the impact of the Lebanese National Polio Immunization Campaign using a population-based computational model
Published in
BMC Public Health, November 2017
DOI 10.1186/s12889-017-4909-0
Pubmed ID
Authors

Ali Alawieh, Zahraa Sabra, E. Farris Langley, Abdul Rahman Bizri, Randa Hamadeh, Fadi A. Zaraket

Abstract

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. 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. 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. 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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The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 65 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 65 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 14 22%
Student > Ph. D. Student 10 15%
Student > Bachelor 7 11%
Researcher 7 11%
Other 4 6%
Other 6 9%
Unknown 17 26%
Readers by discipline Count As %
Nursing and Health Professions 13 20%
Medicine and Dentistry 11 17%
Social Sciences 5 8%
Immunology and Microbiology 3 5%
Computer Science 2 3%
Other 13 20%
Unknown 18 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 29 November 2017.
All research outputs
#14,959,314
of 23,009,818 outputs
Outputs from BMC Public Health
#10,993
of 14,991 outputs
Outputs of similar age
#251,302
of 438,191 outputs
Outputs of similar age from BMC Public Health
#124
of 166 outputs
Altmetric has tracked 23,009,818 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 14,991 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.0. This one is in the 23rd percentile – i.e., 23% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 438,191 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 39th percentile – i.e., 39% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 166 others from the same source and published within six weeks on either side of this one. This one is in the 22nd percentile – i.e., 22% of its contemporaries scored the same or lower than it.