Measures against transmission of pandemic H1N1 influenza in Japan in 2009: simulation model

Abstract

The first outbreak of pandemic H1N1 influenza in Japan was contained in the Kansai region in May 2009 by social distancing measures. Modelling methods are needed to estimate the validity of these measures before their implementation on a large scale. We estimated the transmission coefficient from outbreaks of pandemic H1N1 influenza among school children in Japan in summer 2009; using this transmission coefficient, we simulated the spread of pandemic H1N1 influenza in a virtual community called the virtual Chuo Line which models an area to the west of metropolitan Tokyo. Measures evaluated in our simulation included: isolation at home, school closure, post-exposure prophylaxis and mass vaccinations of school children. We showed that post-exposure prophylaxis combined with isolation at home and school closure significantly decreases the total number of cases in the community and can mitigate the spread of pandemic H1N1 influenza, even when there is a delay in the availability of vaccine.

Membrane System-Based Models for Specifying Dynamical Population Systems

“…Although the experiments carried out in this chapter refer to a virtual population, the results obtained by our simulations match the tendencies reported in the literature using classical SIR models [37][38][39].…”

“…The number of communities and families has been given as input parameters. These parameters have been obtained from [37]. The example depicted in Fig.…”

Models and modelling practices for assessing the impact of outbreak response interventions to human vaccine-preventable diseases (1970-2019) - A systematic review

“…Among the studies that modelled vaccination as a single intervention for comparison with other single non-vaccination interventions, vaccination was found to be the most impactful intervention in 82% of the studies. Four studies out of the 23 that modelled influenza found case isolation [20][21][22] and antiviral prophylaxis and/or therapeutics [23] to be more impactful than vaccination assuming those interventions could be implemented immediately, given significantly efficient isolation and large antiviral stockpiles before the outbreak/pandemic. Among these four studies, some common assumptions that influenced how vaccination was implemented included: the late arrival of effective vaccines [20], low versus high vaccination rates [21], the use of partially effective pre-existing vaccines against the current strain reactively [24] or pre-emptively [25].…”

“…Four studies out of the 23 that modelled influenza found case isolation [20][21][22] and antiviral prophylaxis and/or therapeutics [23] to be more impactful than vaccination assuming those interventions could be implemented immediately, given significantly efficient isolation and large antiviral stockpiles before the outbreak/pandemic. Among these four studies, some common assumptions that influenced how vaccination was implemented included: the late arrival of effective vaccines [20], low versus high vaccination rates [21], the use of partially effective pre-existing vaccines against the current strain reactively [24] or pre-emptively [25]. In all four studies, it was, however, recommended that, vaccination be used in combination with the alternative interventions.…”

The Impact of Community Structure of Social Contact Network on Epidemic Outbreak and Effectiveness of Non-pharmaceutical Interventions

“…Studying real-world outbreaks through epidemiological and case studies can reveal critical insights to help understand the dynamics of disease transmission and identify risk factors [11][12][13][14]. These insights can also serve as the base for the follow-up analytical modeling and computational simulation work and facilitate an understanding of the impact of various public health responses [15,16]. However, using case studies and real-world observations alone cannot guide the selection of the optimal control or response strategies because of lack of support for comparing various alternative measures.…”