title: The impact of mass gatherings and holiday traveling on the course of an influenza pandemic: a computational model.
abstract: BACKGROUND
  During the 2009 H1N1 influenza pandemic, concerns arose about the potential negative effects of mass public gatherings and travel on the course of the pandemic. Better understanding the potential effects of temporal changes in social mixing patterns could help public officials determine if and when to cancel large public gatherings or enforce regional travel restrictions, advisories, or surveillance during an epidemic.
  
  
  METHODS
  We develop a computer simulation model using detailed data from the state of Georgia to explore how various changes in social mixing and contact patterns, representing mass gatherings and holiday traveling, may affect the course of an influenza pandemic. Various scenarios with different combinations of the length of the mass gatherings or traveling period (range: 0.5 to 5 days), the proportion of the population attending the mass gathering events or on travel (range: 1% to 50%), and the initial reproduction numbers R0 (1.3, 1.5, 1.8) are explored.
  
  
  RESULTS
  Mass gatherings that occur within 10 days before the epidemic peak can result in as high as a 10% relative increase in the peak prevalence and the total attack rate, and may have even worse impacts on local communities and travelers' families. Holiday traveling can lead to a second epidemic peak under certain scenarios. Conversely, mass traveling or gatherings may have little effect when occurring much earlier or later than the epidemic peak, e.g., more than 40 days earlier or 20 days later than the peak when the initial R0 = 1.5.
  
  
  CONCLUSIONS
  Our results suggest that monitoring, postponing, or cancelling large public gatherings may be warranted close to the epidemic peak but not earlier or later during the epidemic. Influenza activity should also be closely monitored for a potential second peak if holiday traveling occurs when prevalence is high.
authors.affiliation: Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, 755 Ferst Drive, Atlanta, Georgia, USA.
authors.forename: Pengyi
authors.initials: P
authors.lastname: Shi
authors.forename: Pinar
authors.initials: P
authors.lastname: Keskinocak
authors.forename: Julie L
authors.initials: JL
authors.lastname: Swann
authors.forename: Bruce Y
authors.initials: BY
authors.lastname: Lee
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D002648:Child; D002675:Child, Preschool; D003198:Computer Simulation; D004196:Disease Outbreaks; D005260:Female; D005845:Georgia / Q000453:epidemiology; D006693:Holidays; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D053118:Influenza A Virus, H1N1 Subtype; D007251:Influenza, Human / Q000453:epidemiology*; D008297:Male; D008875:Middle Aged; D008962:Models, Theoretical; D014195:Travel; D055815:Young Adult