Evaluating temporal factors in combined interventions of workforce shift and school closure for mitigating the spread of influenza

• Published in: PloS one 2012-03, Vol.7 (3), p.e32203
• Main Authors: Zhang, Tianyou, Fu, Xiuju, Ma, Stefan, Xiao, Gaoxi, Wong, Limsoon, Kwoh, Chee Keong, Lees, Michael, Lee, Gary Kee Khoon, Hung, Terence
• Format: Article
• Language: English
• Subjects: Adult; Biology; Child; Communicable Disease Control - methods; Computer Science; Computer simulation; Data processing; Disease control; Epidemics; Epidemics - prevention & control; Humans; Infectious diseases; Influenza; Influenza, Human - epidemiology; Influenza, Human - transmission; Intervention; Labor force; Mathematical models; Pandemics; Policy making; Population; Public health; Quantitative analysis; Running; School closures; Schools; Simulation; Social structure; Teams; Time; Time Factors; Work; Workforce
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0032203

It is believed that combined interventions may be more effective than individual interventions in mitigating epidemic. However there is a lack of quantitative studies on performance of the combination of individual interventions under different temporal settings. To better understand the problem, we develop an individual-based simulation model running on top of contact networks based on real-life contact data in Singapore. We model and evaluate the spread of influenza epidemic with intervention strategies of workforce shift and its combination with school closure, and examine the impacts of temporal factors, namely the trigger threshold and the duration of an intervention. By comparing simulation results for intervention scenarios with different temporal factors, we find that combined interventions do not always outperform individual interventions and are more effective only when the duration is longer than 6 weeks or school closure is triggered at the 5% threshold; combined interventions may be more effective if school closure starts first when the duration is less than 4 weeks or workforce shift starts first when the duration is longer than 4 weeks. We therefore conclude that identifying the appropriate timing configuration is crucial for achieving optimal or near optimal performance in mitigating the spread of influenza epidemic. The results of this study are useful to policy makers in deliberating and planning individual and combined interventions.