## Summary

1.7/12 Scenario estimation of the effect of the state of emergency

The number of new positive patients, and the number of severely ill patients, and the number of inpatients (Tokyo standard) were estimated in 3 scenarios: the effect of the fourth state of emergency in Tokyo after 7/12, the equivalent to the second declaration (2021/1), and the equivalent to the third declaration (2021/4).

*Severely ill patients (Tokyo standard): Patients requiring respiratory support and/or using ECMO. (In Tokyo, this standard is effective as of April 27, 2020.)

2.Regarding the scenario equivalent to the current fourth state of emergency, more than 3,100 new positive cases have occurred

If the effects of the fourth state of emergency in July 2021 continue until early August, there is a risk that the number of new positive patients will exceed 3,100 per day, and about 300* severely ill patients will occur in mid-August. * Peak value.

3.Regarding the scenario equivalent to the second state of emergency, more than 2,600 new positive patients occurred

If the effect is similar to that of the second state of emergency in January 2021, the number of new positive patients will exceed 2,600 per day in early August, and 250* severely ill patients may occur in mid-August.

4.Regarding the scenario equivalent to the third state of emergency, about 1,200 new positive patients occurred

If the effect is similar to that of the third state of emergency in April 2021, the number of new positive patients may reach 1,200 per day in early August and then decrease, but 160* severely ill patients may occur in early August.

## Scenario Analysis of New Positives including Delta Variant

➡︎During the fourth state of emergency on 7/12, the number of positive patients was 3,180* in early August, and then gradually decreased if the level of effective reproduction number and the floating population were equivalent as the level in August 2020.

➡︎The number of positive patients was 2,620* in early August, equivalent to the second declaration, and 1,270* at the end of July, equivalent to the third declaration.

State of emergency and vaccination acceleration effect on 7/12 (base 1.0% / day) Simultaneous parallel vaccination for 15-59 years old or younger

1.Effect equivalent to the 4th declaration vaccination rate (human flow approx. 5% decrease), vaccination rate: 1.0%/day, vaccination rate by age: 0.5 for 15-39 years, 0.5 for 40-59 years

2.Effect equivalent to the 2nd declaration vaccination rate (effective reproduction number 7% decrease), vaccination rate: 1.0%/day, vaccination rate by age: 0.5 for 15-39 years, 0.5 for 40-59 years

3. Effect equivalent to the 3rd declaration vaccination rate (effective reproduction number 7% decrease), vaccination rate: 1.0%/day, vaccination rate by age: 0.5 for 15-39 years, 0.5 for 40-59 years

* All are positive patients aged 15 and over, and when 14 and under are added, it increases by about 1.1 times.

Red: Total number of new positives (15 years old or older)

Green: Number of new positives (15-39 years old)

Blue: Number of new positives (40-64 years old)

Purple: Number of new positives (65 years old and above)

Solid line: Measured number / Wavy line: Estimated number

* Numbers are 7-day moving averages

## Scenario Analysis of New Positives including Delta Variant (numbers of severely ill patients & inpatients)

➡︎State of emergency and vaccination acceleration effect on 7/12 (base 1.0% / day) Simultaneous parallel vaccination for 15-59 years old and younger

➡︎Under the fourth declaration of emergency (7/12-), the number of severely ill patients was 310 in early August. It would gradually decrease if the level of effective reproduction number and the floating population were equivalent as the level in August 2020.

➡︎The number of positive patients was 250 in mid-August, equivalent to the second declaration, and 160 at the end of July, equivalent to the third declaration

State of emergency and vaccination acceleration effect on 7/12 (base 1.0% / day) Simultaneous parallel vaccination for 15-59 years old or younger

1. Effect equivalent to the 4th declaration vaccination rate (human flow approx. 5% decrease), vaccination rate: 1.0%/day, vaccination rate by age: 0.5 for 15-39 years, 0.5 for 40-59 years

2. Effect equivalent to the 2nd declaration vaccination rate (effective reproduction number 7% decrease), vaccination rate: 1.0%/day, vaccination rate by age: 0.5 for 15-39 years, 0.5 for 40-59 years

3. Effect equivalent to the 3rd declaration vaccination rate (effective reproduction number 7% decrease), vaccination rate: 1.0%/day, vaccination rate by age: 0.5 for 15-39 years, 0.5 for 40-59 years

Red: Number of severely ill patients

Orange: Number of inpatients

Solid line: Measured number / Wavy line: Estimated number

* Numbers are 7-day moving averages

## 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 (15-39 years, 40-59 years, and 65 years or older) with an accuracy of 2.6 persons/day.* Estimates of positive patient influx from outside Tokyo were incorporated into the model, and the model was trained from the data of the past 3 months. The number of severely ill patients and the number of inpatients were estimated from the transition of the number of positive patients by age group by constructing a statistical model from the data from March 1 to July 24, 2021. In addition, assuming that there was a behavior change of the citizens of Tokyo that was equivalent to the cancellation of the 1st state of emergency last year, a simulation was conducted by applying the effective reproduction number since last summer and the data of the floating population in Tokyo. The Delta variant was assumed to have 10 infected individuals on June 1, and was assumed to have 1.5 times the infectivity (basic regeneration arithmetic) of the estimated Alpha variant.

2.Estimating circuit breaker strength and vaccination effectiveness

The strength of the relaxation of the state of emergency was set for the Alpha variant (remaining conventional variant) and the Delta variant.

3.Vaccine Effect Settings

•The vaccine effect was 57% for the Alpha variant, 94% for the 2nd dose, 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 March 1 to July 24. July 25 to July 30 uses the most recent 7-day moving average Rt, July 31 to August 3 uses a 3-day moving average, and thereafter it was assumed to be equivalent to the same day in 2020, and the decrease after peak was attributed to changes in the behavior of residents such as refraining from going out due to the spread of infection.

https://www3.nhk.or.jp/news/html/20210610/k10013077751000.html

https://www.mhlw.go.jp/content/10900000/000787862.pdf

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 1.0 times

•The number of new positive patients was about 10% lower than the total number of positive patients because the number of new positive patients aged 15 years or older (publication date) was set.

## Model Details

Age-specific Vaccine Effect SEIR Model

Infection Transition Probability by Age

(Propagate from right to left)

Y is 15 to 39 years old, M is 40 to 64 years old, and E is 65 years old or older.

Infections between the ages of 15 and 39 are 97% from the same age group (15 to 39 years old), 3% from 40 to 64 years old, and 0% from 65 years old or older.

The same applies to infections between the ages of 40 and 64 and those aged 65 or older.

Inverse Simulation Model