Summary
■Scenario estimation of the effect of 7/12 state of emergency
The number of new positive patients and the number of severely ill inpatients (Tokyo standard) were estimated in 2 scenarios: the effect of the 4th state of emergency in Tokyo after 7/12 and the equivalent of the 2nd declaration (2021/1).
1.Equivalent to the current 4th state of emergency, more than 15,000 new positive cases will occur
The effect of the 4th state of emergency declaration in July 2021 is low, and there is a risk that the number of new positive patients will exceed 15,000 per day (weekly average), and up to 1,200 severely ill inpatients will occur in early September.
2.Even if the effect is similar to that of the 2nd state of emergency, more than 10,000 new positive cases will occur
If the effect is similar to that of the 2nd state of emergency in January 2021, the number of new positive patients will exceed 10,000 per day in early September, and 760 severely ill inpatients may occur.
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.Proposed Control Scenario: Implementation of a temporary closure from 8/9 to 8/22 could curb the number of positive cases to 7,000
Emergency medical crisis is at hand, thus in addition to requesting restaurants to shorten hours and suspend the provision of alcohol, by taking action cooperatively among all citizens of Tokyo, such as temporary summer closure for two weeks, telework rate of 70% or more in companies, refraining from long-distance travel (e.g., 10 km), and refraining from going out with more than four people, in order to encourage behavioral changes, the number of new positive cases can be reduced to 7,000 and the number of patients hospitalized with severe illness to 540.
Scenario Analysis of New Positives including Delta Variant
➡︎7/12 The effect of the state of emergency is low and in early September, the number of positive patients might be 14,000 (15,400*)
➡︎Possibility of 6,500 (7,100*) by implementing temporary simultaneous closure from 8/9 to 8/22 and suppressing to the intermediate equivalent of 1st and 2nd declarations
State of emergency and vaccination acceleration effect on 7/12 (base 1.0% / day) Simultaneous parallel vaccination for 15-59 years old
Effect of the current 4th declaration continues
Suppressing to equivalent of the 2nd declaration in January
Effect of temporary summer closure (temporary simultaneous closure from 8/9 to 8/22 to control infection to the intermediate equivalent of the 1st and 2nd declarations)
* All are positive patients aged 15 and over, and when 14 and under are added, it increases by about 1.1 times
Red: 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 or older)
Solid line: Actual number / Wavy line: Estimated number
* Numbers are 7-day moving averages for persons aged 15 or older
Scenario analysis of the number of severely ill inpatients caused by Delta variant
➡︎The effect of the 4th state of emergency is low and in early September, the number of severely ill inpatients might be 1,180
➡︎Possibility of 540 by implementing temporary simultaneous closure from 8/9 to 8/22 and suppressing to the intermediate equivalent of 1st and 2nd declarations
State of emergency and vaccination acceleration effect on 7/12 (base 1.0% / day) Simultaneous parallel vaccination for 15-59 years old
1.Effect of the current 4th declaration continues
2.Suppressing to equivalent of the 2nd declaration in January
3.Effect of temporary summer closure (temporary simultaneous closure from 8/9 to 8/22 to control infection to the intermediate equivalent of the 1st and 2nd declarations)
Red: Number of severely ill inpatients (15 years old or older)
Green: Number of severely ill inpatients (15-39 years old)
Blue: Number of severely ill inpatients (40-64 years old)
Red: Number of severely ill inpatients (65 years old or older)
Solid line: Actual number / Wavy line: Estimated number
* Numbers are 7-day moving averages
Model Settings
1.Infection model by SEIR mathematical model and AI optimization method
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.
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. Actual figures are used for changes in the effective reproduction numbers and population flow from 3/1 to 8/1. After 8/2 onward, the most recent 7-day moving average Rt and the average Rt as of the same day in 2020 were used; after 8/30, the 3-day moving average and the average Rt as of the same day in 2020 were assumed to be the same. This 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
