Analysis
■Update of the scenarios on January 10 regarding the rates of serious illness and mortality
■Analysis of the impact on the calculation of serious illness rate where the number of PCR test is constrained
Important Points
■Serious illness rate predictions on the sixth wave (Optimistic, Basic, Pessimistic) are currently 0.03%, 0.11%, and 0.25%
■Mortality rate predictions on the sixth wave (Optimistic, Basic, and Pessimistic) are currently 0.02%, 0.07%, and 0.2%
■If constraints on the number of PCR tests becomes apparent, the rate of serious illness (mortality) may increase significantly if it is calculated by dividing the cumulative number of cases of serious illness (mortality) by the cumulative number of PCR positive patients
■Above serious illness rates may increase by 2 to 5 times
■Above serious illness rates may increase by 2 to 10 times
■However, the impact of constraints on the number of PCR tests is on the "apparent rates of serious illness and mortality" and not on the "actual rates of serious illness and mortality," which is important for policy making
Results (serious illness rate)
■Contribution (Tokyo, basic scenario)
■Fifth wave: 0.66%
■+ Percentage of people who received 2 vaccinations: 0.41% (-38%)
■+ Percentage of elderly people: 0.48% (+17%)
■+ Intrinsic rate of serious illness of Omicron variant: 0.097% (-80%)
■+ 2 vaccinations to prevent serious illness (= sixth wave): 0.11% (+11%)
Results (mortality rate)
■Contribution (Tokyo, basic scenario)
■Fifth wave: 0.31%
■+ Percentage of people who received 2 vaccinations: 0.22% (-29%)
■+ Percentage of elderly people: 0.31% (+41%)
■+ Intrinsic mortality rate of Omicron variant: 0.062% (-80%)
■+ 2 vaccinations to prevent mortality (= sixth wave): 0.070% (+13%)
Percentage of positive cases who received 2 vaccinations
Percentage of elderly among those who are tested positive
Current rates of serious illness and mortality Serious illness rate (national standard)
Background
■As of January 28, the positive rate exceeded 30%, continuing to put a strain on the testing systems
■(Reference) 24% at the peak of the fifth wave
■As the positive rate increases, the (apparent) rate of serious illness also increases
■If the testing systems are further under the strain in the future, elderly people who are at higher risk of serious illness may be given priority for testing
■“If there is a further surge in the number of infected people, experts suggest that ‘young people should be diagnosed without being tested’”
■https://www.asahi.com/articles/ASQ1N6TSDQ1NULBJ01L.html
■Limit testing of young people => Increase in proportion of new positive cases among the elderly => Increase in overall rate of serious illness
■Here, we estimate how much the serious illness rate could increase based on 4 scenarios
4 Scenarios (Serious illness rate: Relative to the Basic Scenario)
(Scenario Details)
■Scenario A: In Tokyo, the number of new positive cases during the peak period (7-day moving average) is approximately 20,000
■Scenario B: As an even more pessimistic scenario than A, the number of positive cases is twice that of Scenario A: approximately 40.000
■In the case of "with" priority given to the elderly, it is assumed that even if the positive rate increases in the future, there will be no elderly people who cannot be tested (additionally)
4 Scenarios (Mortality rate: Relative to the Basic Scenario)
(Scenario Details)
■Scenario A: In Tokyo, the number of new positive cases during the peak period (7-day moving average) is approximately 20,000
■Scenario B: As an even more pessimistic scenario than A, the number of positive cases is twice that of Scenario A: approximately 40.000
■In the case of "with" priority given to the elderly, it is assumed that even if the positive rate increases in the future, there will be no elderly people who cannot be tested (additionally)
Interpretation of positive rate
Relationship between the trend in positive rate and the number of new positive cases
Assumption 1: Positive rate increases to the power of the number of new positive cases
■Assuming this relationship is strong...
■Number of new infections (7-day moving average): 20,000 => positive rate: 49.1%
■Number of new infections (7-day moving average): 40,000 => positive rate: 79.2%
Relationship between positive rate and serious illness rate
Assumption 2: Those who are not prioritized for testing are treated equally, regardless of their symptoms
Relationship between positive rate and serious illness rate
Assumption 3: 30% of all infected people will be subject to priority testing in the future
Scenario on priority for elderly (young people restricted)
Assumption 4: Positive rate is the same for the elderly and non-elderly
