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 Prevention of infection per population by the third vaccination scenario
Prevention of infection per population by the third vaccination scenario
 Date
 2021.12.07
 Researcher
 Akimasa Hirata
 Organization
 Center of Biomedical Physics and Information Technology
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Center of Biomedical Physics and Information Technology
Model of the infectionprevention effect of vaccination (past report: delta variant)
Based on the medium model (infectionprevention effects of the 1 and 2nd vaccinations: 65% and 75%, respectively) and the report of 10/5, it is assumed that the prevention effect of the 3rd vaccination will be 95% and the prevention effects of the 2nd and 3rd vaccinations of half a year later will be 35% and 55%, respectively (decrease linearly). The vaccination effect is assumed to keep its peak for 14 days after vaccination and then attenuate (Reference：https://doi.org/10.1038/d41586021022618）。
First/Second Cabinet Secretariat COVID AI simulation material (medium model)
Zeng B, Gao L, Zhou Q, Yu K, Sun F. Effectiveness of COVID19 vaccines against SARSCoV2 variants of concern: a systematic review and metaanalysis. medRxiv. 2021.
Aran D. Estimating realworld COVID19 vaccine effectiveness in Israel using aggregated counts. MedRxiv. 2021.
Populationlevel infectionprevention effectiveness of vaccination
Calculated (3) the populationlevel infectionprevention effectiveness of vaccination (effective population) from (1) the model of the prevention effect of vaccination and (2) the number of people vaccinated per day
About the basis (calculated from the ADB material)
From the breakdown of unvaccinated and vaccinated people in the number of new positive cases in the whole of Japan
Process of derivation
Calculated the population with insufficient infectionprevention effect of vaccination considering the decline in the vaccination's effectiveness
・High First: 70%, Second: 95%, Attenuation effects of the prevention effects of vaccination of half a year later: 25% and 40%, respectively
・Medium First: 65%, Second: 75%, Attenuation effects of the prevention effects of vaccination of half a year later: 25% and 40%, respectively
Process of derivation
Calculated the number of new positive cases per 100,000 people with insufficient infectionprevention effect of vaccination in each period. Compared with the number of infected people per 100,000 people to unvaccinated people
Process and result of derivation
Calculated the population without the infectionprevention effect of vaccination considering the decline in the vaccination's effectiveness
・High First: 70%, Second: 95%, Attenuation effects of the prevention effects of vaccination of half a year later: 25% and 40%, respectively
・ Medium First: 65%, Second: 75%, Attenuation effects of the prevention effects of vaccination of half a year later: 25% and 40%, respectively
※The closer to 1 the inclination is, the closer the simulated infection condition is to that of unvaccinated people
・For people under 65, there is no significant difference caused by the difference in the attenuation rate (evaluation is difficult because the period from the second vaccination is short)
・For people aged 65 or older, the high model with the attenuation rate of half a year late being 25% can simulate the infection condition of unvaccinated people the best
＊The plot in the figure is equivalent to processing statistical information of ADB materials for one week
Model of the infectionprevention effect of vaccination (from Japanese data)
Based on the high model (infectionprevention effects of the 1 and 2nd vaccinations: 70% and 95%, respectively) and the report of 10/5, it is assumed that the prevention effect of the 3rd vaccination will be 95% and the prevention effect decreases by 25% half a year later (decreases linearly up to 70%). The vaccination effect is assumed to keep its peak for 14 days after vaccination and then attenuate (Reference:https://doi.org/10.1038/d41586021022618）。
First/Second Cabinet Secretariat COVID AI simulation material (high and medium models)
Zeng B, Gao L, Zhou Q, Yu K, Sun F. Effectiveness of COVID19 vaccines against SARSCoV2 variants of concern: a systematic review and metaanalysis. medRxiv. 2021.
Aran D. Estimating realworld COVID19 vaccine effectiveness in Israel using aggregated counts. MedRxiv. 2021.
S. Y. Tartof et al., “Effectiveness of mRNA BNT162b2 COVID1 vaccine upto 6 months in a large integrated health system in the USA: a retrospective cohort study,” Lancet, vol.398, pp.14071416, 2021.
Model of the infectionprevention effect of vaccination per capita
Scenario
１．For cases where the third vaccination is assumed to be conducted
1.six months later
2.seven months later
3.eight months later
4.and nine months later
Assumed the timing at which to start the third vaccination is December 1, and allocated the number of people who were vaccinated before that date, assuming such number will increase immediately as shown in the following table. (Second vaccination: Tokyo from 2021/3/10 and onward.)
2.Assume that the third vaccination is to be conducted eight months after the completion date of the second vaccination (in the case of 3 above).
1.100%
2.80%
3.70%
4.60%
Made trial calculations of the effective proportion of infection prevention per capita assuming that the said proportions of the applicable people seek vaccination:
Scenario 1: If the third vaccination is conducted six to nine months after the completion of the second vaccination
Assume the timing at which to start the third vaccination is December 1and assume the number of vaccinated people on the corresponding date before it will increase immediately after the start. (Start Date of the second vaccination: Tokyo from 2021/3/10 and onward.)
Scenario 2: If 60 to 100% of the applicable people receive the third vaccination (fixed to eight months)
Assume the timing at which to start the third vaccination is December 1and assume the number of vaccinated people on the corresponding date before it will increase immediately after the start. (Start Date of the second vaccination: Tokyo from 2021/3/10 and onward.)
Summary (update)
・Derived the effectiveness of the infectionprevention effect of vaccination per capita based on the temporal transition in the average infectionprevention effect on individual Japanese persons: High infectionprevention effect according to reports from overseas on the elderly
・The threshold in Japan is about 35% during the declaration of a state of emergency (August 2021). An increase in flows of people and behavior changes raise this threshold. Since behaviors also change, the threshold changes every day (Analysis and approximation based on scenario settings are possible).
・The effectiveness of vaccination on new variants is expected to be different, but if vaccination is started early, the effectiveness will rise to 5–10% up to around March. By multiplying it by the vaccination's effectiveness on new variants, the future number of positive cases, etc. can be approximated
Issue
・There is a possibility that the data of the prevention effect on Japanese people is still in the attenuation process and may change in the future
・Need to focus on the trend of foreign countries after the third booster shot (possible by analysis using AI for the decline rate of the prevention effect).
・As of the date of announcement, the nationwide number of new positive cases remained at around 100 per day, so it can easily be affected by clusters
Reference: Material provided by the COVID19 AI simulation office of the Cabinet Secretariat (12/7)
(Right figure)
https://www.jointkaigo.com/articles/202112012.html
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