Prediction model
１．Predict the number of new positive cases from the Japanese situation considering the impact of the variant (no definition of the vaccination rate)
２．Learned and corrected the data of other countries to consider the impact of vaccination in more detail
Model (1)：The impact of vaccination is not defined explicitly
・The input values include the weather information (minimum/maximum and average temperature), data on flows of people, weekdays or holidays, presence or non-presence of declaration of a state of emergency, and number of new positive cases to date as well as the newly added variation label (0: standard, 1: alpha, 2: delta)
・The future values of weather data and the data of flows of people are assumed to be similar to those of last year
・The applicable city of learning data is Tokyo
Model (2)
・Separated the prediction model to make it possible to consider only the impact of vaccination
・The input values of the network are the number of new positive cases and the effectiveness of vaccination
・The applicable city of learning data is Tokyo
Transition in the vaccination rate in Tel Aviv
Definition of the vaccination's effectiveness: Vaccination rate of the total population multiplied by the infection-prevention effect (considering temporal attenuation)
Model of the infection-prevention effect of vaccination
Attenuation rate of the vaccination effect (assumed to linearly decrease) and effect of the third vaccination (assumed to be conducted 14 days later) based on the medium model (infection-prevention effects of the first and second ones are 65% and 75%, respectively)
The vaccination effect is assumed to keep its peak for 14 days after vaccination and then attenuate.The reference is (https://doi.org/10.1038/d41586-021-02261-8). In the case of model 1, the prevention effect of 75% of 14 days after the second vaccination is assumed to drop to 45% (-30 points) half a year later.
Summary
・Machine-learned the relationship between the number of new positive cases and the vaccination rate in Tokyo and applied it to the estimate of the number of new positive cases in Israel (Tokyo -> Israel)
・Estimated the infection-prevention effect of vaccination and its attenuation
・Approximated the attenuation rate of the effect of the second vaccination and the effect of the third one based on the medium model (first: 65%, second: 75%)
・ Since the reproducibility of model 9 is high, the effect of the second vaccination (75%) is estimated to become 45% (-40 points) and the infection-prevention effect of the third vaccination is estimated to be 95%
Issues
1.Consideration of the effect of the third vaccination in Tokyo based on the data of Israel (including the estimates of the number of seriously ill patients, etc.)
2.If any new variant appears: Application of learning of overseas data to prediction of Japan
