title: Agent-based simulation for weekend-extension strategies to mitigate influenza outbreaks.
abstract: BACKGROUND
  Non-pharmaceutical strategies are vital in curtailing impacts of influenza and have been intensively studied in public health. However, few strategies have explicitly utilized the weekend effect, which has been widely reported to be capable of reducing influenza infections. This study aims to explore six weekend-extension strategies against seasonal and pandemic flu outbreaks.
  
  
  METHODS
  The weekend-extension strategies were designed to extend regular two-day weekend by one, two and three days, respectively, and in combination with either a continuous or discontinuous pattern. Their effectiveness was evaluated using an established agent-based spatially explicit simulation model in the urbanized area of Buffalo, NY, US.
  
  
  RESULTS
  If the extensions last more than two days, the weekend-extension strategies can remarkably reduce the overall disease attack rate of seasonal flu. Particularly, a three-day continuous extension is sufficient to suppress the epidemic and confine the spread of disease. For the pandemic flu, the weekend-extension strategies only produce a few mitigation effects until the extensions exceed three days. Sensitivity analysis indicated that a compliance level above 75% is necessary for the weekend-extension strategies to take effects.
  
  
  CONCLUSIONS
  This research is the first attempt to incorporate the weekend effect into influenza mitigation strategies. The results suggest that appropriate extensions of the regular two-day weekend can be a potential measure to fight against influenza outbreaks, while minimizing interruptions on normal rhythms of socio-economy. The concept of weekend extension would be particularly useful if there were a lack of vaccine stockpiles, e.g., in countries with limited health resources, or in the case of unknown emerging infectious diseases.
authors: Department of Geography, University of Florida, Gainesville, Florida, 32611, USA. liangmao@ufl.edu
authors: Liang
authors: L
authors: Mao
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D004196:Disease Outbreaks / Q000517:prevention & control*; D006293:Health Promotion / Q000379:methods*; D006801:Humans; D015994:Incidence; D007251:Influenza, Human / Q000453:epidemiology* / Q000821:virology; D008875:Middle Aged; D008962:Models, Theoretical; D009518:New York / Q000453:epidemiology; D015397:Program Evaluation; D011634:Public Health; D013997:Time Factors; D014505:Urban Population; D055815:Young Adult