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- Date of lifting the declaration, increase in human flow, vaccine effect, booster vaccination, vaccination rate, restriction on vaccination certificate – their estimated effects (Tokyo)
Date of lifting the declaration, increase in human flow, vaccine effect, booster vaccination, vaccination rate, restriction on vaccination certificate – their estimated effects (Tokyo)
- Date
- 2021.09.14
- Researcher
- Setsuya Kurahashi
- Organization
- Graduate School of Business Sciences, University of Tsukuba
/
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Graduate School of Business Sciences, University of Tsukuba
筑波大学大学院ビジネス科学研究科
Summary
・Estimates of the number of new positive cases and the number of seriously ill patients were made for each of the following settings: The date of lifting the declaration, increase in human flow, vaccine effect, booster vaccination, vaccination rate, vaccination certificate restrictions.
・Assuming a declining vaccine effect on infection control, the results suggest that the combination of booster vaccination and restriction of entry to workplaces, restaurants, and events by vaccination certificate is most effective.
Simulation Settings
➡︎Estimates of the number of new positive cases and the number of serious illness were conducted for 19 combinations of set values (details on the next page) for each of the following: the date of lifting the declaration, increase in human flow, vaccine effect, booster vaccination, vaccination rate, vaccination certificate restrictions.

Summary of Simulation Results


Prerequisites (see also the Simulation Setting slide):
*1 Date of lifting the declaration, 25% increase in the population staying downtown at 19:00 after lifting
*2 Vaccine effect 1st dose, 2nd dose: L (55%. 65%), M (65%, 75%), H (70%, 95%)
*3 Rate of decline 180 days after the 2nd dose, 240 days after the 2nd dose: 0% (0%, 0%), 30% (30%, 50%), 10% (BS) (10%, 10%)
*4 Vaccination rates for total population (aged 39 years and younger, aged 40-59, aged 60 and older)
*5 Rate of restriction on admission/use for persons without vaccination certificate or proof of negative PCR/antigen test results
※Thereafter, unless otherwise stated, dates refer to the year 2022.
※Because the number of combinations of all the setting values is enormous, 19 main combinations were used.
Reference: Reverse Lookup of Scenario No from Conditions

1. Comparison of the number of positive cases
1.Impact of vaccine effect (no vaccine decline) Scenarios 1, 2, 3
2.Impact of vaccine effect (no vaccine decline) Scenarios 2, 4, 5
3.State of emergency is lifted on October 15 (no vaccine decline) Scenarios 6, 7
4.Impact of vaccine effect (with vaccine decline) Scenarios 8, 9, 10
5.Impact of vaccination rate (with vaccine decline) Scenarios 9, 11, 12
6.State of emergency is lifted on October 15 (with vaccine decline) Scenarios 13, 14
7.Introduction of vaccination certificate restrictions Scenarios 11, 16, 17
8.Introduction of booster vaccination Scenarios 15, 18, 19
1-1. Estimation of the Number of Positive Cases: Impact of vaccine effect (no vaccine decline) Scenarios 1, 2, 3
➡When vaccine decline is not taken into account, there is no difference in infection suppression between high and low vaccine effect.


1-2. Estimation of the Number of Positive Cases: Impact of vaccination rate (no vaccine decline) Scenarios 2, 4, 5
➡If vaccine decline is not taken into account, the spread of infections after 2022 can be controlled as vaccination rates increase.


1-3. Estimation of the Number of Positive Cases: State of emergency is lifted on October 15 (no vaccine decline) Scenarios 6, 7
➡Extending the state of emergency declaration until October 15 would curb the spread of infections in 2022, compared with lifting on October 1.


1-4. Estimation of the Number of Positive Cases: Impact of vaccine effect (with vaccine decline) Scenarios 8, 9, 10
➡Even vaccine decline is taken into account, there is no difference in infection suppression between high and low vaccine effect.


1-5. Estimation of the Number of Positive Cases: Impact of vaccination rate (with vaccine decline) Scenarios 9, 11, 12
➡Even vaccine decline is taken into account, the spread of infections after 2022 can be controlled as vaccination rates increase.


1-6. Estimation of the Number of Positive Cases: State of emergency is lifted on October 15 (with vaccine decline) Scenarios 13, 14
➡Extending the state of emergency declaration until October 15 would curb the spread of infections in 2022, compared with lifting on October 1.


1-7. Estimation of the Number of Positive Cases: Introduction of vaccination certificate restrictions Scenarios 11, 16, 17
➡By introducing vaccination certificate restrictions, it was suggested that the spread of infections after the spring of 2022 can be effectively contained.
➡However, even with a restriction rate of 70% based on vaccination certificate, the number of cases exceeds 1,000 at peak and cannot be completely controlled.


1-8. Estimation of the Number of Positive Cases: Introduction of booster vaccination Scenarios 15, 18, 19
➡The combination of booster vaccination and vaccination certification restrictions will most effectively control the spread of infections in 2022.


2. Comparison of the number of seriously ill patients
1.Impact of vaccine effect (no vaccine decline) Scenarios 1, 2, 3
2.Impact of vaccine effect (no vaccine decline) Scenarios 2, 4, 5
3.State of emergency is lifted on October 15 (no vaccine decline) Scenarios 6, 7
4.Impact of vaccine effect (with vaccine decline) Scenarios 8, 9, 10
5.Impact of vaccination rate (with vaccine decline) Scenarios 9, 11, 12
6.State of emergency is lifted on October 15 (with vaccine decline) Scenarios 13, 14
7.Introduction of vaccination certificate restrictions Scenarios 11, 16, 17
8.Introduction of booster vaccination Scenarios 15, 18, 19
2-1. Estimation of the Number of seriously ill patients: Impact of vaccine effect (no vaccine decline) Scenarios 1, 2, 3
➡When vaccine decline is not taken into account, there is no difference in suppression of the number of seriously ill patients between high and low vaccine effect.


2-2. Estimation of the Number of seriously ill patients: Impact of vaccination rate (no vaccine decline) Scenarios 2, 4, 5
➡If vaccine decline is not taken into account, the number of seriously ill patients after 2022 can be controlled as vaccination rates increase.


2-3. Estimation of the Number of seriously ill patients: State of emergency is lifted on October 15 (no vaccine decline) Scenarios 6, 7
➡Extending the state of emergency declaration until October 15 would curb the number of seriously ill patients in 2022, compared with lifting on October 1.


2-4. Estimation of the Number of seriously ill patients: Impact of vaccine effect (with vaccine decline) Scenarios 8, 9, 10
➡Even vaccine decline is taken into account, there is no difference in suppression of the number of seriously ill patients between high and low vaccine effect.


2-5. Estimation of the Number of seriously ill patients: Impact of vaccination rate (with vaccine decline) Scenarios 9, 11, 12
➡Even vaccine decline is taken into account, the number of seriously ill patients after 2022 can be controlled as vaccination rates increase.


2-6. Estimation of the Number of seriously ill patients: State of emergency is lifted on October 15 (with vaccine decline) Scenarios 13, 14
➡Extending the state of emergency declaration until October 15 would curb the number of seriously ill patients in 2022, compared with lifting on October 1.


2-7. Estimation of the Number of seriously ill patients: Introduction of vaccination certificate restrictions Scenarios 11, 16, 17
➡By introducing vaccination certificate restrictions, it was suggested that the number of seriously ill patients can be effectively contained in 2022.
➡However, even with a restriction rate of 70% based on vaccination certificate, the number cannot be completely controlled.


2-8. Estimation of the Number of seriously ill patients: Introduction of booster vaccination Scenarios 15, 18, 19
➡The combination of booster vaccination and vaccination certification restrictions will most effectively control the number of seriously ill patients in 2022.


Model Settings
1.Infection model by SEIR mathematical model and AI optimization method
The SEIR model, which takes into account population flow and AI technology (evolutionary optimization + quasi-Newton method), were used to optimize infection model estimation within and between three age groups (0-39 years, 40-59 years, and 60 years or older). The positive patient influx from outside the prefecture was estimated from mobile spatial statistics data (NTT DOCOMO) and LocationMind xPop*1, and incorporated into the model, and the model was trained from the data from March 1 to September 12, 2021.
2.Estimating circuit breaker strength and vaccination effectiveness
The rate of increase in human flow was set for Delta variant. Setting was that the suppression of human flow will be eased after 9/20.
3.Effects of vaccine and behavior change
・The vaccine effect was 57% for the 1st dose, 94% for the 2nd dose for the Alpha variant to prevent the infection, and 0.9 times for the Delta variant.
Measured values are used for changes in the number of effective reproductions and the number of population flows from 3/1 to 9/12. After 9/13, the latest 7-day moving average was used, and after 10/1, the latest 2 days and the average of last year's infection change rate were used.
・Vaccination rate setting
After 3/5 0.05% of the population (1st measured number of medical staff)
After 3/27 0.032%, 0.033% (number of 1st and 2nd medical staff measurements)
After 4/12 0.069%, 0.030% (1st and 2nd actual measurements of medical staff) 0.01% (1st actual measurement of elderly people)
After 5/4 0.064%, 0.078% (1st and 2nd actual measurements of medical staff) 0.065%, 0.006% (1st and 2nd actual measurements of elderly people)
After 6/1 0.064%, 0.078% (1st and 2nd expected medical staff) 0.08%, 0.065% (1st and 2nd expected elderly)
After 6/21 k/2%, k/2% (1st and 2nd expected medical staff) k/2%, k/2% (1st and 2nd expected elderly) k = 1.0%
After 8/15 1.3%
・Vaccine decline effect
Assumed were a 15% decline at 120 days, a 30% decline at 180 days, and a 45% decline at 240 days (lower limit 50%), referring to reports that the infection control effect declines to 64% at 180 days (Israel Ministry of Health), 78% at 90 days (Oxford, Nature), and 65.5% at 90 days (NEJM) after the 2nd vaccination. Immunity effect (serious illness rate) was estimated by a statistical model from measured numbers of seriously ill in Tokyo.
・■https://www.gov.il/en/departments/news/05072021-03, ■https://www.gov.il/en/departments/news/06072021-04
・Resurgence of SARS-CoV-2 Infection in a Highly Vaccinated Health System Workforce, DOI: 10.1056/NEJMc2112981, The new England journal of medicine
・COVID vaccines protect against Delta, but their effectiveness wanes, doi: ■https://doi.org/10.1038/d41586-021-02261-8, Nature
*1 "LocationMind xPop" data is data that NTT DOCOMO collectively and statistically processes from mobile phone location information sent with permission from users of applications* provided by NTT DOCOMO. Location information is GPS data (latitude and longitude information) that is measured at a minimum of every five minutes, and does not contain information that identifies an individual. * DOCOMO Map Navi Service (map application, local guide) and some other applications
Model Details

Tokyo suburbs individual base model
・The model is expressed by 1348 agents composed of two cities based on the household composition in the suburbs of Tokyo
・Rate of change in Rt from 500 trials was measured based on entry restrictions of 20% to 100% for workplaces, restaurants, and event venues based on use of vaccination certificates (food and drink is restricted to friend networks)
・Number of infected people 20/100,000 (≒ 3,000/Tokyo)

Estimation model of the infection change rate by the population flow in Tokyo
