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Epidemiology and policy
P1-323 Evaluation of strategies for pandemic influenza (H1N1) control and prevention in Japan based on a total number survey in a closed area simulated by mathematical models
  1. T Sato1,2,
  2. T Akita1,
  3. J Tanaka1
  1. 1Hiroshima University, Graduate School of Biomedical Sciences, Hiroshima, Japan
  2. 2Kounu Clinic, Miyoshi, Japan

Abstract

Introduction In 2009, we observed worldwide epidemics of pdmH1N1-flu. We made an almost complete survey of epidemic of pdmH1N1-flu in Kounu town which is isolated from others. All the children with influenza should be reported in Japan for the School-Health-Law preventing their attendance in the infectious period. We applied this epidemic to mathematical models and suggested some strategies to control infection.

Methods Subjects were children of nursery, elementary, and junior high school living in Kounu town. We estimated this epidemic by applying to Kermack-McKendrick model and Multitype epidemic models, selected the most suitable model, and changed the parameters to analyse from three preventing strategies; shortening of virus seeding by 1 day, decreasing of infectivity by 30%, and decreasing the infectivity in especially high infectivity areas to nearly other's one.

Results We estimated R0=1.44–6.95 for the basic reproduction number. The model of assumed subpopulation of school and community was the most suitable, and we found a “super spreader area” on N area in this model. All the strategies could reduce total infectious population. Only when virus seeding was shortened, epidemic was also shortened. Peak infectious population was much reduced when we intervened in especially high infectivity areas.

Conclusion Most patients were treated with anti-virus and school closure was carried out. This caused the actual epidemic curve shortened and total patients were less than the estimated epidemic model. Therefore, we suggest that particularly where there is a super spreader, to isolate the patients and interruption to infectious roots are effective.

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