Mao BMC Public Health 2011, 11:522 http://www.biomedcentral.com/1471-2458/11/522 non-pharmaceutical strategies remains an actively pur- sued topic in public health. This paper proposes a new type of non-pharmaceuti- cal strategies that extended the regular two-day weekend for the purposes of interrupting influenza transmission and mitigating disease impacts, referred to as ‘weekend- extension strategies’. In the current literature, few miti- gation strategies have considered the reductive effect of weekend on influenza transmission, although this effect has been widely reported [8-10]. For example, the study by Hens et al. in eight European countries estimated a 10~20% reduction in influenza infections during week- end when compared to weekdays [10]. Research by both Lee et al. and Cooley et al. attributes the variability of influenza incidence to the weekday-weekend effect [8,9]. A primary reason is that most workplaces and schools are closed simultaneously during weekend, and thus fewer human contacts take place as opposed to week- days. For instance, a survey by McCaw et al. indicated that an individual has 2~4 more personal contacts dur- ing weekend than weekdays[11]. A study of university students by Edmunds et al. also found that individuals made 26 contacts per day during weekdays, but only 19 per day during weekend[12]. These studies imply that extending the weekend period might be an effective strategy to mitigate influenza outbreaks. To test the effectiveness of weekend-extension strate- gies, an established agent-based spatially-explicit model was developed for the urbanized area of Buffalo, New York, US. The model simulated these strategies and pro- duced epidemic outcomes for evaluation. The remainder of this article is organized into following sections. The second section introduces the study area and methods, including the design of weekend-extension strategies and the agent-based simulation model. The third section presents simulation results and compares the effective- ness between strategies. The fourth section discusses model outcomes and implications, and the final section concludes the article. Methods Design of weekend-extension strategies Two dimensions were involved in the design of weekend- extension strategies. One dimension concerned the length of extensions, i.e., how long the regular Saturday and Sun- day weekend should be extended. The other dimension specified the pattern of extensions, i.e., in which manner the extensions should be applied. A continuous pattern means that the additional weekend follows right after the regular weekend and lasts continuously, e.g., Saturday + Sunday+ (Monday +Tuesday). A discontinuous pattern separately arranges the additional weekend within a week, for instance, Saturday + Sunday + (Tuesday +Thursday). The continuous extensions produce longer and less Page 2 of 10 frequent interruptions on influenza transmission, while the discontinuous extensions cause shorter and more fre- quent interruptions. In this research, three lengths of extensions were investigated, including one, two and three days, in combination with the two patterns of extensions (continuous and discontinuous). The combination of the two dimensions (3 lengths × 2 patterns) resulted in six strategies to be evaluated (Table 1). During the additional weekend, all businesses (including schools) were closed except for service-oriented places, such as utility compa- nies, health facilities, restaurants, and grocery stores. Indi- viduals were assumed to follow activity patterns of either Saturday or Sunday, e.g., staying at home, visiting service places, or meeting with friends in neighbor households. Study area and data collection The six proposed strategies were investigated in the urbanized area of Buffalo, New York, US. This study area was chosen because an influenza simulation model had been previously established [13]. The input data included the information about 985,001 individuals and 400,870 households from US Census 2000 [14], as well as a database of 36,839 business locations in year 2009 [15]. Individuals were assumed to travel through a local transportation system, take their daily activities at homes and business locations, have contact with one another, and expose themselves to influenza infection. Agent-based influenza model The established agent-based model first simulated a contact network in the study area, which provided a basis for influenza transmission [13]. The network con- sists of 985,001 discrete individuals as nodes and their daily contacts as links. Individual contacts were assumed to take place during three time periods in a day and at four types of locations. The three time periods included: daytime, pastime and nighttime, while the four types of locations referred to homes, workplaces (schools, finan- cial offices, administrative units, industrial factories, etc.), service places (utility companies, health facilities, grocery stores, etc.), and neighbor households (house- holds in the same census block group). Modeled indivi- duals traveled between time and location, and had contact with different groups of individuals, such as family members, co-workers, clerks, and friends. These spatiotemporally varying contacts linked all individuals into a city-wide network. To construct such a contact network, three popula- tions of daytime, nighttime and pastime were synthe- sized respectively and then linked together [13]. The census data was used to build the nighttime population of individuals and households that matched the real age and household structures. The nighttime population was assigned to business locations to create the daytime