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Estimating transmission probability in schools for the 2009 H1N1 influenza pandemic in Italy

Overview of attention for article published in Theoretical Biology and Medical Modelling, October 2016
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Title
Estimating transmission probability in schools for the 2009 H1N1 influenza pandemic in Italy
Published in
Theoretical Biology and Medical Modelling, October 2016
DOI 10.1186/s12976-016-0045-2
Pubmed ID
Authors

Valentina Clamer, Ilaria Dorigatti, Laura Fumanelli, Caterina Rizzo, Andrea Pugliese

Abstract

Epidemic models are being extensively used to understand the main pathways of spread of infectious diseases, and thus to assess control methods. Schools are well known to represent hot spots for epidemic spread; hence, understanding typical patterns of infection transmission within schools is crucial for designing adequate control strategies. The attention that was given to the 2009 A/H1N1pdm09 flu pandemic has made it possible to collect detailed data on the occurrence of influenza-like illness (ILI) symptoms in two primary schools of Trento, Italy. The data collected in the two schools were used to calibrate a discrete-time SIR model, which was designed to estimate the probabilities of influenza transmission within the classes, grades and schools using Markov Chain Monte Carlo (MCMC) methods. We found that the virus was mainly transmitted within class, with lower levels of transmission between students in the same grade and even lower, though not significantly so, among different grades within the schools. We estimated median values of R 0 from the epidemic curves in the two schools of 1.16 and 1.40; on the other hand, we estimated the average number of students infected by the first school case to be 0.85 and 1.09 in the two schools. The discrepancy between the values of R 0 estimated from the epidemic curve or from the within-school transmission probabilities suggests that household and community transmission played an important role in sustaining the school epidemics. The high probability of infection between students in the same class confirms that targeting within-class transmission is key to controlling the spread of influenza in school settings and, as a consequence, in the general population.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 43 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 43 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 26%
Student > Ph. D. Student 9 21%
Other 5 12%
Professor 2 5%
Student > Master 2 5%
Other 6 14%
Unknown 8 19%
Readers by discipline Count As %
Medicine and Dentistry 11 26%
Mathematics 5 12%
Social Sciences 4 9%
Nursing and Health Professions 2 5%
Agricultural and Biological Sciences 2 5%
Other 6 14%
Unknown 13 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 11 March 2020.
All research outputs
#17,823,285
of 22,896,955 outputs
Outputs from Theoretical Biology and Medical Modelling
#210
of 287 outputs
Outputs of similar age
#228,389
of 319,867 outputs
Outputs of similar age from Theoretical Biology and Medical Modelling
#2
of 2 outputs
Altmetric has tracked 22,896,955 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 287 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.4. This one is in the 25th percentile – i.e., 25% of its peers scored the same or lower than it.
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