During the COVID-19 pandemic over the past one year or so, Japanese economists have announced the results of analyses regarding real-world policy responses to this crisis, with some of them conducting real-time policy analyses.
A group including Associate Professor Takayuki Mizuno of the National Institute of Informatics, in a paper published in May 2020, confirmed that there is not necessarily a correlation between a decline in the level of population flow (the number of persons per unit of area) and a decline in the frequency of contact (contact is defined as the situation of two people together occupying an area of four square meters for a given period of time). Their analysis examined changes in the level of human mobility and the frequency of contact on busy streets, such as the areas around the Shibuya and Shinjuku stations in Tokyo, under Japan's first declaration of a state of emergency, using location data obtained through NTT DoCoMo mobile phone terminals, among other datasets.
Their analysis showed that the rate of decline in the frequency of contact at a certain location tends to be 10 to 20 percentage points higher than the rate of decline in the level of population flow there. In other words, if population flow at a certain location fell 60%, for example, the frequency of contact there may be presumed to have fallen 80%. This finding shook the prevailing (and erroneous) assumption around the spring of 2020 that reducing population flow by 80% would lead to a fall of 80% in the frequency of contact.
In a paper published in August 2020, Professor Tsutomu Watanabe of the University of Tokyo and Professor Tomoyoshi Yabu of Keio University showed that the "information effect"—which refers in this case to the effect of information announcements from the central and local governments and news reports from media organizations leading to changes in people's perceptions of the situation of infection and encouraging them to voluntarily refrain from going out—is stronger than the "intervention effect"—which refers to the effect of direct policy interventions, such as declarations of a state of emergency by the central and local governments.
As a result of the analysis of factors affecting changes in population flow using location information obtained through mobile phone terminals, it was found that the information effect accounted for three quarters of the decline in population flow in Tokyo, while the direct intervention effect accounted for only one quarter. This finding affected the debate at the government's expert panel on the COVID-19 crisis in autumn of 2020 and later, and formed some of the basis of the central government's strategy of restricting population flow through more careful announcements of information, rather than relying on authoritative measures, such as declarations of states of emergency.
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Analyses that forecast policy effects through simulations also started to appear in the second half of 2020. Asako Chiba, a postdoctoral fellow at the Tokyo Foundation for Policy Research, developed a computer model of Japanese society through an agent-based modeling approach and conducted simulations analyzing the effects of actually implemented policy measures, such as calling for people to refrain from traveling long distances and for restaurants and stores to reduce opening hours, as well as other measures under consideration. The findings were reported back to the central government, and a further analysis has been conducted in response to the government's study on new policy options.
A research team led by Project Assistant Professor Daisuke Fujii and Associate Professor Taisuke Nakata, both from the University of Tokyo, conducted a simulation analysis using a macro-epidemiological model that combined a model for infection transmission (SIR model) from the field of theoretical epidemiology and an economic growth model (Solow model) from the field of macroeconomics. One characteristics of their research approach is that it is able to both forecast changes in the situation of infection and to calculate economic costs that may be caused by the situation of infection and policy responses.
Their research compared the scenario of "strong restrictions," under which the number of new infection cases is brought down to a sufficiently low level through measures that impose strong restrictions on people's behavior, such as a declaration of a state of emergency (it is assumed that the pandemic will be later contained due to the dissemination of vaccination), and the scenario of "weak restriction," under which the government removes the declaration of a state of emergency due to economic concerns before the number of new infection cases falls and is then forced to again declare a state of emergency. The comparison showed that both the number of deaths and the amount of economic losses due to COVID-19 are lower under the strong restriction scenario than the weak restriction scenario.
At the government's expert panel, it has been argued from a qualitative viewpoint that containing COVID-19 through strong policy measures reduces overall costs for society compared with hastily removing a declaration of a state of emergency out of consideration for the economy, and this study is very significant in that it supported the validity of this argument through quantitative model forecasting. The research team updates its simulation results weekly.
There are also various other studies conducted in Japan combining macroeconomic and epidemiological methodologies, including one being conducted by Associate Professor So Kubota of Waseda University and one being conducted jointly by Professor Mitsuhiro Fukao of Musashino University and Professor Etsuro Shoji of Hitotsubashi University.
In the field of microeconomics, a group of market design researchers raised concerns regarding the disorderly situation of the vaccine reservation systems. The group argues that in principle, an age-based priority system (under which vaccination is prioritized by age) or a government-designation system (under which the authorities designate vaccination dates for individuals) is better from the viewpoint of social welfare than offering vaccination on a first come, first served basis, and publicly presented a policy proposal along those lines. The group includes Professor Morimitsu Kurino of Keio University, Professor Fuhito Kojima of the University of Tokyo, Associate Professor Shunya Noda of the University of British Columbia, and Associate Professor Takeshi Murooka of Osaka University, as well as two members of the government's expert panel, namely Specially Appointed Professor Fumio Ohtake of Osaka University and the author of this article.
What is particularly noteworthy is that the market design centers of the University of Tokyo and Keio University have opened consulting windows for local governments in order to respond to inquiries about how to improve vaccine reservation systems. This is an example of efforts by economists to make proactive contributions to the real world by taking advantage of their professional knowledge.
Later, the above mentioned group was joined by Hiroaki Odahara, a project researcher at the University of Tokyo, and Professor Yasutora Watanabe of the University of Tokyo and it presented a policy proposal on how to stimulate demand for vaccination. Specifically, the group proposed that the government should encourage people to be vaccinated as early as possible by offering some kind of reward for vaccination, including for those who have already been vaccinated.
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In the field of healthcare economics as well, the COVID-19 crisis has led to new findings. According to the results of an analysis which were announced by Global Health Consulting Japan (based in Shinjuku Ward, Tokyo) in September 2020 and based on data from around 500 hospitals covered by the DPC (diagnosis procedure combination) system, both inpatient and outpatient revenues at healthcare institutions recorded year-on-year decreases of around 15% in the early phase of the crisis. It was also found that the rate of falling revenues at healthcare institutions that accepted COVID-19 patients was more than double the rate at institutions that did not.
At large hospitals with more than 500 beds, in the April-June quarter of 2020, inpatient revenue declined by as much as 370 million yen on a year-on-year average. Another finding was that the number of cases of hospitalizations due to ordinary pneumonia and viral enteritis in May 2020 fell as much as around 50-60% year-on-year. Those figures reflect the fact that many people suffering from diseases other than COVID-19 avoided receiving treatment due to fears of in-hospital infection, but they also suggest that some of the healthcare services taken for granted before the COVID-19 were superfluous.
It is also true that accepting COVID-19 patients has posed a great risk of financial loss for hospital. Likely as a result of such fears of financial losses, many hospital managers began to refuse to admit COVID-19 patients from the summer of 2020 through this year. Because of this fact, various additional subsidy programs have been created to encourage healthcare institutions to treat COVID-19 patients.
The above table is part of the reference materials submitted to the Fiscal System Council on May 21. It shows that at some public healthcare institutions, revenue in 2020, including subsidy revenue, was much larger than the revenue in 2019. This proves that the perception that receiving COVID-19 patients discouraged patient visits and caused financial losses to hospital management is already outdated.
Now that the vaccination of healthcare professionals has made significant progress, I hope that healthcare institutions that have so far refrained from admitting COVID-19 cases will overcome the fears of infection and financial losses and contribute to the fight against the pandemic by admitting COVID-19 patients and participating in vaccination programs.