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School closure policies at municipality level for mitigating influenza spread: a model-based evaluation

Overview of attention for article published in BMC Infectious Diseases, October 2016
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (97th percentile)
  • High Attention Score compared to outputs of the same age and source (98th percentile)

Mentioned by

news
6 news outlets
blogs
1 blog
twitter
60 X users
facebook
1 Facebook page

Citations

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24 Dimensions

Readers on

mendeley
72 Mendeley
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Title
School closure policies at municipality level for mitigating influenza spread: a model-based evaluation
Published in
BMC Infectious Diseases, October 2016
DOI 10.1186/s12879-016-1918-z
Pubmed ID
Authors

Constanze Ciavarella, Laura Fumanelli, Stefano Merler, Ciro Cattuto, Marco Ajelli

Abstract

Nearly every year Influenza affects most countries worldwide and the risk of a new pandemic is always present. Therefore, influenza is a major concern for public health. School-age individuals are often the most affected group, suggesting that the inclusion in preparedness plans of school closure policies may represent an option for influenza mitigation. However, their applicability remains uncertain and their implementation should carefully be weighed on the basis of cost-benefit considerations. We developed an individual-based model for influenza transmission integrating data on sociodemography and time use of the Italian population, face-to-face contacts in schools, and influenza natural history. The model was calibrated on the basis of epidemiological data from the 2009 influenza pandemic and was used to evaluate the effectiveness of three reactive school closure strategies, all based on school absenteeism. In the case of a new influenza pandemic sharing similar features with the 2009 H1N1 pandemic, gradual school closure strategies (i.e., strategies closing classes first, then grades or the entire school) could lead to attack rate reduction up to 20-25 % and to peak weekly incidence reduction up to 50-55 %, at the cost of about three school weeks lost per student. Gradual strategies are quite stable to variations in the start of policy application and to the threshold on student absenteeism triggering class (and school) closures. In the case of a new influenza pandemic showing different characteristics with respect to the 2009 H1N1 pandemic, we found that the most critical features determining the effectiveness of school closure policies are the reproduction number and the age-specific susceptibility to infection, suggesting that these two epidemiological quantities should be estimated early on in the spread of a new pandemic for properly informing response planners. Our results highlight a potential beneficial effect of reactive gradual school closure policies in mitigating influenza spread, conditioned on the effort that decision makers are willing to afford. Moreover, the suggested strategies are solely based on routinely collected and easily accessible data (such as student absenteeism irrespective of the cause and ILI incidence) and thus they appear to be applicable in real world situations.

X Demographics

X Demographics

The data shown below were collected from the profiles of 60 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 72 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 1%
Unknown 71 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 18 25%
Researcher 13 18%
Student > Master 10 14%
Student > Bachelor 6 8%
Student > Postgraduate 3 4%
Other 8 11%
Unknown 14 19%
Readers by discipline Count As %
Medicine and Dentistry 17 24%
Social Sciences 7 10%
Nursing and Health Professions 5 7%
Agricultural and Biological Sciences 5 7%
Mathematics 4 6%
Other 15 21%
Unknown 19 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 99. 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 October 2020.
All research outputs
#430,695
of 25,550,333 outputs
Outputs from BMC Infectious Diseases
#109
of 8,653 outputs
Outputs of similar age
#8,264
of 324,471 outputs
Outputs of similar age from BMC Infectious Diseases
#4
of 225 outputs
Altmetric has tracked 25,550,333 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,653 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.7. 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 324,471 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 97% of its contemporaries.
We're also able to compare this research output to 225 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.