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The impact of regular school closure on seasonal influenza epidemics: a data-driven spatial transmission model for Belgium

Overview of attention for article published in BMC Infectious Diseases, January 2018
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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (95th percentile)
  • High Attention Score compared to outputs of the same age and source (98th percentile)

Mentioned by

news
1 news outlet
blogs
1 blog
policy
1 policy source
twitter
43 tweeters

Citations

dimensions_citation
17 Dimensions

Readers on

mendeley
66 Mendeley
citeulike
1 CiteULike
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Title
The impact of regular school closure on seasonal influenza epidemics: a data-driven spatial transmission model for Belgium
Published in
BMC Infectious Diseases, January 2018
DOI 10.1186/s12879-017-2934-3
Pubmed ID
Authors

Giancarlo De Luca, Kim Van Kerckhove, Pietro Coletti, Chiara Poletto, Nathalie Bossuyt, Niel Hens, Vittoria Colizza

Abstract

School closure is often considered as an option to mitigate influenza epidemics because of its potential to reduce transmission in children and then in the community. The policy is still however highly debated because of controversial evidence. Moreover, the specific mechanisms leading to mitigation are not clearly identified. We introduced a stochastic spatial age-specific metapopulation model to assess the role of holiday-associated behavioral changes and how they affect seasonal influenza dynamics. The model is applied to Belgium, parameterized with country-specific data on social mixing and travel, and calibrated to the 2008/2009 influenza season. It includes behavioral changes occurring during weekend vs. weekday, and holiday vs. school-term. Several experimental scenarios are explored to identify the relevant social and behavioral mechanisms. Stochastic numerical simulations show that holidays considerably delay the peak of the season and mitigate its impact. Changes in mixing patterns are responsible for the observed effects, whereas changes in travel behavior do not alter the epidemic. Weekends are important in slowing down the season by periodically dampening transmission. Christmas holidays have the largest impact on the epidemic, however later school breaks may help in reducing the epidemic size, stressing the importance of considering the full calendar. An extension of the Christmas holiday of 1 week may further mitigate the epidemic. Changes in the way individuals establish contacts during holidays are the key ingredient explaining the mitigating effect of regular school closure. Our findings highlight the need to quantify these changes in different demographic and epidemic contexts in order to provide accurate and reliable evaluations of closure effectiveness. They also suggest strategic policies in the distribution of holiday periods to minimize the epidemic impact.

Twitter Demographics

The data shown below were collected from the profiles of 43 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 66 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 66 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 14 21%
Researcher 9 14%
Student > Ph. D. Student 8 12%
Other 4 6%
Student > Bachelor 4 6%
Other 12 18%
Unknown 15 23%
Readers by discipline Count As %
Medicine and Dentistry 6 9%
Mathematics 6 9%
Agricultural and Biological Sciences 6 9%
Psychology 4 6%
Physics and Astronomy 3 5%
Other 20 30%
Unknown 21 32%

Attention Score in Context

This research output has an Altmetric Attention Score of 50. 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 05 May 2020.
All research outputs
#427,440
of 15,418,155 outputs
Outputs from BMC Infectious Diseases
#66
of 5,643 outputs
Outputs of similar age
#18,005
of 406,175 outputs
Outputs of similar age from BMC Infectious Diseases
#13
of 651 outputs
Altmetric has tracked 15,418,155 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,643 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.9. This one has done particularly well, scoring higher than 98% of its peers.
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 406,175 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 95% of its contemporaries.
We're also able to compare this research output to 651 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 98% of its contemporaries.