Deriving the infection-prevention effect of vaccination from the number of new positive cases in Tokyo
Deriving the infection-prevention effect of vaccination from the number of new positive cases per day and the vaccination condition in Tokyo
*For Twitter and vaccination's effectiveness, the three-day average (±1 day) is shown
For the period in the blue frame (12/31 to 1/18), confirmed a decline from the substantial vaccination's effectiveness (reddish brown solid line)
-> Decline of the vaccination effect = Defined as Infection-prevention effect of vaccination based on observation - Effective infection-prevention effect of vaccination
For the Twitter data, see past materials
https://www.covid19-ai.jp/ja-jp/presentation/2021_rq3_countermeasures_simulation/articles/article232/
Relationship between the decline in the infection-prevention effect of vaccination, and SNS (drinking party) and nighttime retention population
Relationship between a temporary decline in the vaccination's effectiveness observed between 12/31 and 1/18, and Twitter (drinking party + Year-end/New Year party) and the nighttime retention population (21:00)
The decline in the vaccination's effectiveness tends to be associated with an increase in Twitter. Not correlated with the nighttime retention population.
For Twitter and the nighttime retention population, a three-day average value considering one day before and after the day.
The delay from the impact on behavioral changes through infection to the inspection result is assumed to be seven days (the result is almost the same with a delay of 5–8 days)
Number of new positive cases of Tokyo: Prediction
If behaviors are controlled to the same extent as the last year by the declaration of a state of emergency (blue) and if the current behaviors are kept (reddish brown), for two weeks from February 1 to 14, it is assumed that the number of asymptomatic infected people will be 4 times larger than the number of new positive cases and the reinfection-prevention effect will be 50% and then decrease linearly.
Number of new positive cases in Aichi: Prediction
If behaviors are controlled to the same extent as the last year by the declaration of a state of emergency (blue) and if the current behaviors are kept (reddish brown), for two weeks from February 1 to 14, it is assumed that the number of asymptomatic infected people will be 4 times larger than the number of new positive cases and the reinfection-prevention effect will be 50% and then decrease linearly.
Summary
- It is suggested that the vaccination effect decreased due to great exposure to the virus during periods when infection is easy to occur due to the three C’s (closed spaces, crowded places, and close-contact settings), etc. (This is the first long vacation like the year-end and new-year holidays after the start of vaccination)
- Correlated with the keyword related to risky behaviors in SNS (drinking party)
- An analysis example of a calculation result considered in learning (four times the number of asymptomatic infected people) is shown above. (The peak is early February (may be delayed to mid-February.) It is assumed to be 10 times larger in the last week)
- If almost the same details as those in the declaration of a state of emergency of the last year are assumed using the number of new positive cases as the indicator (two weeks), there will be almost no decrease. This shall not apply if there is a strong reaction from citizens. If the declaration of a state of emergency is to be considered, its social aspects must be different.
