Simulation suggests that rapid activation of social distancing can arrest epidemic development due to a novel strain of Influenza

School of Computer Science and Software Engineering, University of Western Australia, Perth, WA, Australia.
BMC Public Health (Impact Factor: 2.26). 05/2009; 9(1):117. DOI: 10.1186/1471-2458-9-117
Source: PubMed


Social distancing interventions such as school closure and prohibition of public gatherings are present in pandemic influenza preparedness plans. Predicting the effectiveness of intervention strategies in a pandemic is difficult. In the absence of other evidence, computer simulation can be used to help policy makers plan for a potential future influenza pandemic. We conducted simulations of a small community to determine the magnitude and timing of activation that would be necessary for social distancing interventions to arrest a future pandemic.
We used a detailed, individual-based model of a real community with a population of approximately 30,000. We simulated the effect of four social distancing interventions: school closure, increased isolation of symptomatic individuals in their household, workplace nonattendance, and reduction of contact in the wider community. We simulated each of the intervention measures in isolation and in several combinations; and examined the effect of delays in the activation of interventions on the final and daily attack rates.
For an epidemic with an R0 value of 1.5, a combination of all four social distancing measures could reduce the final attack rate from 33% to below 10% if introduced within 6 weeks from the introduction of the first case. In contrast, for an R0 of 2.5 these measures must be introduced within 2 weeks of the first case to achieve a similar reduction; delays of 2, 3 and 4 weeks resulted in final attack rates of 7%, 21% and 45% respectively. For an R0 of 3.5 the combination of all four measures could reduce the final attack rate from 73% to 16%, but only if introduced without delay; delays of 1, 2 or 3 weeks resulted in final attack rates of 19%, 35% or 63% respectively. For the higher R0 values no single measure has a significant impact on attack rates.
Our results suggest a critical role of social distancing in the potential control of a future pandemic and indicate that such interventions are capable of arresting influenza epidemic development, but only if they are used in combination, activated without delay and maintained for a relatively long period.

Download full-text


Available from: Joel Kelso
  • Source
    • "In particular, the co-evolution of information diffusion as a proxy for effective preventive behavioural changes and epidemiological contagion has been investigated by Funk and colleagues, (e.g., see Funk et al., 2009, 2010 for a review on different investigations on the impacts behavioural changes on epidemiological dynamics). However , these models, as in other deterministic game-theoretical formulation, rely on a rational construction of agents utilizing payoff maximization (e.g., homo-economicus perspective) to trigger preventive behaviours including vaccinations (Fu et al., 2010; Ndeffo Mbah et al., 2012; Perisic and Bauch, 2009; Epstein et al., 2008; Kelso et al., 2009). In Fu et al. (2010) and Ndeffo Mbah et al. (2012), the authors used game-theoretic approach within an in silico to explore the effect of cost-benefit of imitation of vaccination patterns. "

    Full-text · Dataset · Oct 2015
  • Source
    • "Along the same vein, Zanette and Risau-Gusman[33]allow susceptible nodes to either permanently sever a connection with an infectious node, or rewire to another randomly chosen (and possibly infectious) node. Del Valle et al.[8]assume some individuals lower their contact rates once an epidemic is detected, whereas Glass et al.[34]and Kelso et al.[9]use complex contact networks which include families, schools, and workplaces to test differing social distancing methods such as school closures and the effects of staying at home while infectious. Hence, disease-behaviour models studying either vaccinating behaviour or NPI behaviour separately from one another are relatively abundant, but models incorporating both types behaviour are rare, to our knowledge. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Theoretical models of disease dynamics on networks can aid our understanding of how infectious diseases spread through a population. Models that incorporate decision-making mechanisms can furthermore capture how behaviour-driven aspects of transmission such as vaccination choices and the use of non-pharmaceutical interventions (NPIs) interact with disease dynamics. However, these two interventions are usually modelled separately. Here, we construct a simulation model of influenza transmission through a contact network, where individuals can choose whether to become vaccinated and/or practice NPIs. These decisions are based on previous experience with the disease, the current state of infection amongst one's contacts, and the personal and social impacts of the choices they make. We find that the interventions interfere with one another: because of negative feedback between intervention uptake and infection prevalence, it is difficult to simultaneously increase uptake of all interventions by changing utilities or perceived risks. However, on account of vaccine efficacy being higher than NPI efficacy, measures to expand NPI practice have only a small net impact on influenza incidence due to strongly mitigating feedback from vaccinating behaviour, whereas expanding vaccine uptake causes a significant net reduction in influenza incidence, despite the reduction of NPI practice in response. As a result, measures that support expansion of only vaccination (such as reducing vaccine cost), or measures that simultaneously support vaccination and NPIs (such as emphasizing harms of influenza infection, or satisfaction from preventing infection in others through both interventions) can significantly reduce influenza incidence, whereas measures that only support expansion of NPI practice (such as making hand sanitizers more available) have little net impact on influenza incidence. (However, measures that improve NPI efficacy may fare better.) We conclude that the impact of interference on programs relying on multiple interventions should be more carefully studied, for both influenza and other infectious diseases.
    Full-text · Article · Jun 2015 · PLoS Computational Biology
  • Source
    • "At the national level, the most universally recommended two-set measures were frequent hand-washing and availability and use of alcohol-based hand sanitizers; as well as covering sneezes/coughs, and the use of masks, all widely advocated through extensive print, audio, video campaigns conducted throughout virtually all public spaces, airwaves and outlets. Recent theoretical models confirm the legitimacy of these early, sustained, and non-pharmaceutical interventions for influenza containment[7]–[12]. However, there is a severely lacking amount of information about the potential indirect impact of this international crisis on other prevalent diseases. "
    [Show abstract] [Hide abstract]
    ABSTRACT: The 2009 A/H1N1 influenza pandemic has received a great deal of attention from public health authorities. Our study examines whether this pandemic and the resulting public health measures could have impacted acute diarrhea, a prevalent, highly transmissible and historically monitored disease. Using augmentation procedures of national data for the previous five years (2004-2009), we estimated the expected timing and incidence of acute diarrhea in France in 2009-2010 and evaluated differences with the observed. We also reviewed national hand gels for the same period. Number of episodes of acute diarrhea in France in 2009-2010 was significantly lower than expected until the third week of December (-24%, 95% CI [-36%; -9%]), then significantly higher (+40%, 95% CI [22%; 62%]), leading to a surplus of 574,440 episodes. The epidemic was delayed by 5 weeks with a peak 1.3 times higher than expected. Hand-gels sales inversely correlated with incidence of both influenza-like illness and acute diarrheal disease. Among individuals >65 yo, no excess cases of influenza and no excess rebound in acute diarrhea were observed, despite similar delay in the onset of the seasonal diarrheal epidemic. Our results suggest that at least one endemic disease had an unexpected behavior in 2009-2010. Acute diarrhea seems to have been controlled during the beginning of the pandemic in all age groups, but later peaked higher than expected in the younger population. The all-age delay in seasonal onset seems partly attributable to hand-gels use, while the differential magnitude of the seasonal epidemic between young and old, concurrent for both influenza and acute diarrhea, is compatible with disease interaction.
    Full-text · Article · Oct 2013 · PLoS ONE
Show more