Graduate School of Business Sciences, University of Tsukuba
1.7/12 Scenario estimation of the effect of the state of emergency
The effect of the declaration of State of Emergency in Tokyo after 7/12 are shown in three scenarios: equivalent to the 2nd declaration (2021/1), equivalent to the 3rd declaration (2021/4), equivalent to the 3rd declaration + accelerated vaccination. The number of new positive patients and the number of severely ill patients (Tokyo standard) were estimated.
* 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 2nd state of emergency, more than 2,100 new positive patients occurred
If the effect is similar to that of the 2nd state of emergency in January 2021, the number of new positive patients will exceed 2,100 per day in early August, and 210 seriously ill patients may occur in early September. Based on the current flow of human traffic, it seems that the situation is close to this.
3.About 1,200 new positive patients were generated with regard to the equivalent of the 3rd state of emergency
If the effect is similar to that of the 3rd state of emergency declaration in April 2021, the number of new positive patients will reach 1,230 per day in early August and then decrease afterwards, but 147 severely ill patients may occur in early September. Infection may continue until April 2022.
4.Acceleration of vaccination and vaccination under 39 years of age can suppress infection after autumn
Accelerate the vaccination rate 1.2%/day after August 15 and raise the vaccination rate for those 15-39 years old (0.7 for 15-39 years, 0.3 for 40-64 years). In this way, the infection control effect after autumn will be enhanced, and it may end in March 2022.
Scenario Analysis of New Positives including Delta Variant
➡︎7/12 The strength of the state of emergency is equivalent to the 3rd, and in early August, the number of positive patients was 1,230 and the number of severely ill patients was 147.
➡︎Acceleration of vaccination and strengthening of vaccination under 39 years old will enable infection control after autumn and termination in March next year
State of emergency and vaccination acceleration effect on 7/12 (base 1.0%/day)
1. Effect equivalent to the 2nd declaration, 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 3rd declaration, 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 after 8/15 1.2%/day, vaccination rate by age: 0.7 for 15-39 years, 0.3 for 40-59 years
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)
Dark purple wavy line: Number of severely ill people
Solid line: Measured number / Wavy line: Estimated number
* Numbers are 7-day moving averages
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.* The estimated influx of positive patients from outside Tokyo was incorporated into the model, and the model was trained from the number of positive patients from June 21 to July 15, 2021. The number of severely ill patients was estimated from the transition of the number of positive patients in each age group by constructing a statistical model from the data of the past 3 months. 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.
2.Estimating circuit breaker strength and vaccination effectiveness
For the Alpha variant (remaining conventional variant) and Delta variant, the strength of emergency declaration mitigation was set between the 1st and 2nd emergency declarations.
3.Vaccine Effect Settings
•It was assumed that the Delta variant will increase the effective reproduction number by 50% relative to the Alpha variant.
The vaccine effect was 57% for the Alpha variant, 94% for the 2nd dose, and 0.9 times for the Delta variant. Measured values were used for changes in the number of effective reproductions and the number of population flow from March 1 to June 22. From June 23 to July 22, the latest 7-day moving average Rt was used, and it was assumed that July 23 and later are equivalent to July 23, 2020 and later. The decrease after the 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 or 1.2 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.
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.