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
- 1Citations
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
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Metrics Details
- Citations1
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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.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85152525394&origin=inward; http://dx.doi.org/10.1007/978-3-031-29126-5_11; https://link.springer.com/10.1007/978-3-031-29126-5_11; https://dx.doi.org/10.1007/978-3-031-29126-5_11; https://link.springer.com/chapter/10.1007/978-3-031-29126-5_11
Springer Science and Business Media LLC
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