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Modeling the effect of school closures in a pandemic scenario: exploring two different contact matrices

tetano

Editor, Senior Moderator
Clin Infect Dis. 2015 May 1;60 Suppl 1:S58-63. doi: 10.1093/cid/civ086.
[h=1]Modeling the effect of school closures in a pandemic scenario: exploring two different contact matrices.[/h] Fung IC[SUP]1[/SUP], Gambhir M[SUP]2[/SUP], Glasser JW[SUP]3[/SUP], Gao H[SUP]3[/SUP], Washington ML[SUP]4[/SUP], Uzicanin A[SUP]3[/SUP], Meltzer MI[SUP]4[/SUP].
[h=3]Author information[/h]

[h=3]Abstract[/h] [h=4]BACKGROUND:[/h] School closures may delay the epidemic peak of the next influenza pandemic, but whether school closure can delay the peak until pandemic vaccine is ready to be deployed is uncertain.
[h=4]METHODS:[/h] To study the effect of school closures on the timing of epidemic peaks, we built a deterministic susceptible-infected-recovered model of influenza transmission. We stratified the U.S. population into 4 age groups (0-4, 5-19, 20-64, and ≥65 years), and used contact matrices to model the average number of potentially disease transmitting, nonphysical contacts.
[h=4]RESULTS:[/h] For every week of school closure at day 5 of introduction and a 30% clinical attack rate scenario, epidemic peak would be delayed by approximately 5 days. For a 15% clinical attack rate scenario, 1 week closure would delay the peak by 9 days. Closing schools for less than 84 days (12 weeks) would not, however, reduce the estimated total number of cases.
[h=4]CONCLUSIONS:[/h] Unless vaccine is available early, school closure alone may not be able to delay the peak until vaccine is ready to be deployed. Conversely, if vaccination begins quickly, school closure may be helpful in providing the time to vaccinate school-aged children before the pandemic peaks.
Published by Oxford University Press on behalf of the Infectious Diseases Society of America 2015. This work is written by (a) US Government employee(s) and is in the public domain in the US.


[h=4]KEYWORDS:[/h] influenza; mathematical model; social distancing

PMID: 25878302 [PubMed - in process]
 
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