title: Modeling the effect of school closures in a pandemic scenario: exploring two different contact matrices.
abstract: BACKGROUND
  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.
  
  
  METHODS
  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.
  
  
  RESULTS
  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.
  
  
  CONCLUSIONS
  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.
authors: Department of Epidemiology, Jiann-Ping Hsu College of Public Health, Georgia Southern University, Statesboro Centers for Disease Control and Prevention, and.
authors: Isaac Chun-Hai
authors: IC
authors: Fung
authors: Centers for Disease Control and Prevention, and IHRC, Inc, Atlanta, Georgia Epidemiological Modelling Unit, Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Australia;
authors: Manoj
authors: M
authors: Gambhir
authors: Centers for Disease Control and Prevention, and.
authors: John W
authors: JW
authors: Glasser
authors: Centers for Disease Control and Prevention, and.
authors: Hongjiang
authors: H
authors: Gao
authors: Centers for Disease Control and Prevention, and Division of Preparedness and Emerging Infections, National Center for Emerging and Zoonotic Infectious Diseases, Atlanta, Georgia.
authors: Michael L
authors: ML
authors: Washington
authors: Centers for Disease Control and Prevention, and.
authors: Amra
authors: A
authors: Uzicanin
authors: Centers for Disease Control and Prevention, and Division of Preparedness and Emerging Infections, National Center for Emerging and Zoonotic Infectious Diseases, Atlanta, Georgia.
authors: Martin I
authors: MI
authors: Meltzer
mesh_terms: D000293:Adolescent; D002648:Child; D002675:Child, Preschool; D004189:Disaster Planning / Q000379:methods*; D004196:Disease Outbreaks / Q000517:prevention & control; D005260:Female; D006801:Humans; D007251:Influenza, Human / Q000453:epidemiology / Q000517:prevention & control* / Q000635:transmission; D008297:Male; D008962:Models, Theoretical; D058873:Pandemics / Q000517:prevention & control*; D011322:Primary Prevention / Q000379:methods; D011634:Public Health / Q000379:methods; D012574:Schools / Q000331:legislation & jurisprudence*; D014481:United States / Q000453:epidemiology
keywords: influenza; mathematical model; social distancing