Mao BMC Public Health 2011, 11:522 http://www.biomedcentral.com/1471-2458/11/522 R E S E A R C H A R T I C L E Open Access Agent-based simulation for weekend-extension strategies to mitigate influenza outbreaks Liang Mao 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. Conclusion: 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. Background Despite advances in medical sciences, influenza (com- monly known as flu) remains a remarkable threat to the public health and socio-economy as a whole. Seasonal flu typically infects 10%~20% of the US population every year [1]. The pandemic H1N1 influenza (the 2009 swine flu) was recently reported to be responsible for 274,000 hospitalizations and 12,470 deaths in the US[2]. Due to the rapid mutation and swift spread of flu virus, prepa- redness for imminent pandemics is now a top priority of public health[3]. Among the core issues of prepared- ness is the study of mitigation strategies that can mini- mize impacts of influenza on human society. Non-pharmaceutical mitigation strategies, such as the household quarantine, workplace/school closure, and travel restriction, had been embedded within the latest Correspondence: liangmao@ufl.edu Department of Geography, University of Florida, Gainesville, Florida, 32611, USA framework of influenza prevention and control recom- mended by the CDC’s Advisory Committee on Immuni- zation Practices [4]. These strategies are critical because they represent the only type of intervention measure guaranteed to be available against a novel strain of influ- enza in the early phases of a pandemic [5]. Their ulti- mate goals are to reduce infections and delay transmission, thereby allowing time to implement phar- maceutical strategies, such as vaccination and antiviral prophylaxis. Many studies, however, have pointed out that the non-pharmaceutical strategies are often difficult to put into practice, since their effectiveness is highly dependent on the compliance of population [6]. Further- more, these strategies may infringe on human rights and involve psychological, ethical and legal issues, e.g., limit- ing free movement of individuals. A recent evaluation had concluded that there was a general lack of scientific evidence or expert consensus for implementing these strategies[7]. Due to these drawbacks, the exploration of © 2011 Mao; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.