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A Research of Infectivity Rate of Seasonal Influenza from Pre-infectious Person for Data Driven Simulation

Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, ISSN: 1867-822X, Vol: 477 LNICST, Page: 131-143
2023
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Conference Paper Description

I had proposed a discrete mathematical SEPIR (Susceptible – Exposed - Pre-infectious – Infectious - Recovered stage) model for seasonal influenza. In a subsequent previously study, focusing on infections by a pre-infectious person using pre-existing data, I showed that there super-spreading of seasonal influenza occurred before D-day that the first patients are discovered at Japan Coast Guard Academy. In this study, I found that the infectivity rate from pre-infectious people is 0.041 when the surrounding people don’t take counter-measures against the infection. After D-day in the community, the countermeasures taken reduce the infectivity rate to 0.002 in working spaces and 0.013 in living spaces. And the number of infectious people can be estimated simply by the summing up each group in the community.

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