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 Infection Simulation based on Proposed Human Behavior Models derived from SNS and Press Data #11
Infection Simulation based on Proposed Human Behavior Models derived from SNS and Press Data #11
 Date
 2021.09.07
 Researcher
 Satoshi Kurihara
 Organization
 Faculty of Science and Technology, Keio University
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Faculty of Science and Technology, Keio University
Summary
■The introduction of vaccine passport is highly effective
■Even with the introduction of a vaccine passport, 3rd vaccination is still required
■However, there is no problem with the 3rd vaccination 6 months after the 2nd vaccination
■Without the introduction of a vaccine passport, even if the 3rd vaccination is given 3 months after the 2nd vaccination, the effect is temporary
3 scenarios based on the effect of vaccination
We simulated the number of positive cases according to the vaccination rate and the number of vaccinations.
In this simulation, the following 3 scenarios were assumed.
1.2 vaccinations
Assuming that the effect on the prevention drops to 0.5 in 6 months
Assuming that the effect is 0.85 times against Delta variant than conventional variant
2.3rd vaccination 6 months after the 2nd vaccination
3.3rd vaccination 3 months after the 2nd vaccination
Assuming that the effect on the prevention drops to 0.75 in 6 months after 3rd vaccination
Estimation of the effect of vaccine passport
The effect of implementing vaccine passport policy from October 1 was simulated based on the following estimates.
*Specific implementation strategies to achieve 50% and 20% are to be considered
Simulation conditions
The specific conditions for the simulation were set as follows.
➡︎The effect of the 4th state of emergency is between that of priority measures to prevent the spread of infectious disease and that of the 3rd state of emergency.
✔️The 4th state of emergency 2021/07/12〜2021/09/12
✔️Priority measures to prevent the spread of infectious disease: 2021/09/13〜2021/09/30
➡︎Maintain the current telework rate.
➡︎Vaccine passport policy will commence from 2021/10/01.
➡︎Final vaccination rate will be analyzed under each of the following conditions.
✔️60%，70%，80%，90%
Number of new positive cases in Tokyo: 20% of unvaccinated people behave the same as before COVID19
If a vaccine passport is introduced, the number of new positive cases next year will fluctuate depending on the final vaccination rate, but the spread of infection will be significantly reduced.
Number of new positive cases in Tokyo: 20% of unvaccinated people behave the same as before COVID19
Vaccination alone is unlikely to sufficiently reduce new positive cases. On the other hand, the introduction of a vaccine passport along with low vaccination rates will have limited effect. Achieving 8090% vaccination rate, implementing 3rd vaccination 3 months after the 2nd vaccination, and introducing a vaccine passport in parallel, will keep the number of positive cases low.
Number of new positive cases in Tokyo: 50% of unvaccinated people behave the same as before COVID19
If the introduction of a vaccine passport is less effective and a large number of unvaccinated people do not refrain from travel, the number of positive cases will increase in the coming year.
Number of new positive cases in Tokyo: 50% of unvaccinated people behave the same as before COVID19
If vaccination rate is low, the number of positive cases is expected to increase as of late March 2022, even with the introduction of a vaccine passport. It is advisable to implement 3rd vaccination as soon as possible.
Number of new positive cases by age in Tokyo: 20% of unvaccinated people behave the same as before COVID19
When analyzed by age group, the introduction of a vaccine passport will limit the increase in the number of positive cases towards the end of the year for every age group.
Number of new positive cases by age in Tokyo: 50% of unvaccinated people behave the same as before COVID19
If the effectiveness of a vaccine passport is relatively weak, the number of positive cases is expected to increase from 2022 in all age groups. The increase is particularly large in the 1564 age group.
Number of seriously ill patients in Tokyo: 20% of unvaccinated people behave the same as before COVID19
Based on the number of new positive cases, it is assumed that the number of seriously ill patients in Tokyo will decrease with the introduction of a vaccine passport. The decrease in the actual measured value on the graph is thought to be due to weather and other factors.
Number of seriously ill patients in Tokyo: 50% of unvaccinated people behave the same as before COVID19
Based on the number of new positive cases, it is assumed that the number of seriously ill patients in Tokyo will decrease with the introduction of a vaccine passport. The decrease in the actual measured value on the graph is thought to be due to weather and other factors.
Number of new positive cases nationwide: 20% of unvaccinated people behave the same as before COVID19
We were able to confirm that the number of new positive cases would be significantly reduced in a nationwide simulation if a vaccine passport was introduced.
Number of new positive cases nationwide: 50% of unvaccinated people behave the same as before COVID19
The introduction of a vaccine passport along with low vaccination rates will have limited effect according to the nationwide simulation as well.
Number of seriously ill patients nationwide: 20% of unvaccinated people behave the same as before COVID19
Based on the number of new positive cases, it is assumed that the number of seriously ill patients nationwide will decrease with the introduction of a vaccine passport and remain below 500 by next March.
Number of seriously ill patients nationwide: 50% of unvaccinated people behave the same as before COVID19
Based on the number of new positive cases, it is assumed that the number of seriously ill patients will significantly decrease even with a relatively weak effect of a vaccine passport.
SNS (Twitter) Analysis
An analysis of Twitter tweets shows a gradual rise in feelings of fear, though not on par with the 1st state of emergency, suggesting a growing sense of crisis among younger people. As a result, it may lead to a level of selfrestraint comparable to the 1st state of emergency.
Mobile Spatial Statistics (Population Change)
During the 4th state of emergency and priority measures to prevent the spread of infectious disease, we have confirmed a decrease in human flow in all regions.
・Mobile spatial statistics were used to identify changes in the population flow in downtown areas within the region where the state of emergency was declared.
・During past state of emergency, we have seen a significant reduction in human flow in each of the areas where the state of emergency was declared. The effect (reduction in the number of people in the region) was strongest at the time of the 1st declaration, with no significant difference in effect between the 2nd and 3rd.
・In the areas where the 4th state of emergency was declared, there is a tendency for the human flow to increase in a Vshape, although it has not yet recovered to the former level.
Mobile Spatial Statistics (Population Change)
Kabukicho, Tokyo (Number of people in the area by time axis)
Mobile Spatial Statistics (Population Change)
Shibuya Center Street, Tokyo (Number of people in the area by time axis)
Mobile Spatial Statistics (Population Change)
Ikebukuro, Tokyo (Number of people in the area by time axis)
Mobile Spatial Statistics (Population Change)
Harajuku, Tokyo (Number of people in the area by time axis)
Mobile Spatial Statistics (Population Change)
Ueno Ameyoko, Tokyo (Number of people in the area by time axis)
Mobile Spatial Statistics (Population Change)
South side of Shinagawa Station, Tokyo (Number of people in the area by time axis)
Mobile Spatial Statistics (Population Change)
Tokyo Station, Tokyo (Number of people in the area by time axis)
Mobile Spatial Statistics (Population Change)
Odaiba Tokyo Teleport, Tokyo (Number of people in the area by time axis)
Mobile Spatial Statistics (Population Change)
Yokohama Station, Kanagawa (Number of people in the area by time axis)
Mobile Spatial Statistics (Population Change)
Kawasaki Station, Kanagawa (Number of people in the area by time axis)
Mobile Spatial Statistics (Population Change)
Hiyoshi Station, Kanagawa (Number of people in the area by time axis)
Mobile Spatial Statistics (Population Change)
Kitashinchi, Osaka (Number of people in the area by time axis)
Mobile Spatial Statistics (Population Change)
Kawaramachi, Kyoto (Number of people in the area by time axis)
Mobile Spatial Statistics (Population Change)
NakasuKawabata, Fukuoka (Number of people in the area by time axis)
Mobile Spatial Statistics (Population Change)
Susukino, Hokkaido (Number of people in the area by time axis)
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