Relaxing behavioral restrictions following the spread of vaccination

Date: 2021.08.24
Researcher: Asako Chiba
Organization: The Tokyo Foundation for Policy Research

Simulation of lifting of behavioral restrictions

・Whether or not to lift behavioral restrictions when the vaccination of applicants is completed
・Medical capacity needed when behavioral restrictions are lifted

・"An urgent proposal to more than double the size of the COVID-19 medical system: Other sacrifices will be made if social and economic activities are still suppressed" (Ohtake, Kobayashi, Takaku, Nakata, https://toyokeizai.net/articles/-/448544）

Model

・Recreating the daily contacts of Tokyo residents
・Situations in which people come into contact with other people
・Individual attributes (age, gender, industry, occupation, frequency of eating out)
・Infection rate and serious illness rate according to age

Chiba, Asako. 2021. "The effectiveness of mobility control, shortening of restaurants' opening hours, and working from home on control of COVID-19 spread in Japan" Health & Place 70: 102622.

Chiba, Asako. 2021. “Modeling the effects of contact-tracing apps on the spread of the coronavirus disease: mechanisms, conditions, and efficiency" PLOS ONE (forthcoming).

Reference: Kerr et al. (2020)

Population of Tokyo generated from national census

・Overview of hypothetical data of population of Tokyo
　・Regions: nationwide
　・Scale factor: 72,771 people
　・Attributes: age, gender, occupation, industry engaged in, size of workplace, frequency of eating out

・Randomly selecting 25,000 Tokyo residents from anonymous data (about 1.25 million people) from the national census, and generated a family for each person based on their answers about their household.
・Since the above processes increase the number of younger multi-person households, the number of single-person households aged 60 and over is doubled to bring the population ratio between ages closer to the original data.
・Each person is given an attribute other than age and gender, according to the actual distribution
From the above processes, the hypothetical population data that simulate the population of Tokyo is created.

Individual attributes and contacts

Daily contacts (home, school, workplace, facilities)

・The contacted persons do not change throughout the term

Contact in restaurants

・Frequency of eating out
・Those who eat out about three times a week　　25%
・Those who eat out about twice a week　　44%
・Those who do not eat out at all　　31%
(Impact of Covid-19 on Dining Out, Entertainment, and Travel-Related Consumption and Prospects for a Recovery in Demand, by Nomura Research Institute, Ltd.)

Spread of infection through contac/h2>

・Contagion occurs probabilistically when an uninfected person has contact with an infected person
・Determinants of the probability that infected person A transfers the virus to uninfected person B
　1.Probability of infection in a place where two persons have contact
　2.Infectivity of A (probability of infecting)
　3.Susceptibility of B (probability of being infected)
・Contact with many people in a place with a high probability of infection increases the risk of infection

Definition of medical conditions/h2>

Number of days required for state transition and transition probability

LN(a,b) is the lognormal distribution with expected value a and standard deviation b
Ministry of Health, Labour and Welfare (August 2021 edition),
Eleven things you need to know NOW about COVID-19
https://www.mhlw.go.jp/content/000788485.pdf

・Prevalent test rate 30% (test sensitivity 70%)
・δ variant (5-6 times increase in positive patients over 7 days)
・Vaccination: By getting two doses of vaccination, susceptibility would become 5%, and the serious illness rate would be 50% of non-vaccinated individuals

・Infection trends calculated for 3 months after vaccination coverage to applicants
・Vaccination coverage rate (2 ways) x Lifting of behavioral restrictions (4 ways)
　・Vaccination coverage rate:
　　1) Normal (80% of the elderly, 60% of the young),
　　2) Increased vaccination rate (90% of the elderly, 80% of the young)
　・Lifting of behavioral restrictions:
　Decreasing 70%, 50%, 30% in outings, or no restrictions

新Number of new positive patients

Number of patients with moderate or more serious illness

Cumulative deaths

Results summary

・If the human flow is restored at a normal vaccination coverage rate, there will be a significant increase in the number of patients and deaths (infection explosion)
・If vaccination coverage is increased, relaxing human flow suppression will not cause infection explosion
・The number of patients with moderate or more serious illness will stay below about 30,000, except for the pattern of "vaccination coverage rate is normal and human flow suppression is lifted", so in terms of the number of hospital beds, about three times the current 10,000 beds will be needed