Unwillingness to cooperate with COVID-19 contact tracing in Japan.

OBJECTIVES: Contact tracing for COVID-19 relies heavily on the cooperation of individuals with authorities to provide information of contact persons. However, few studies have clarified willingness to cooperate and motivation to provide information for contact tracing. This study sought to describe willingness to cooperate and motivation to report contact persons for COVID-19 contact tracing among citizens in Japan, and to assess any associated sociodemographic factors. STUDY DESIGN: Cross-sectional study. METHODS: This was an online-based survey using quota sampling. Participants were asked about their willingness to cooperate in reporting contacts for COVID-19 contact tracing if they tested positive. Participants also responded to questions regarding their reasons for cooperating or not cooperating and provided sociodemographic data. Multiple logistic regression analysis was performed to clarify associations between sociodemographic factors and willingness to cooperate. RESULTS: This study included 2844 participants. The proportion of participants who were not willing to cooperate in reporting contacts was 27.6%, with their main reasons being concerns about causing trouble for the other person and being criticised for revealing their names. Willingness to cooperate was lower among men, young adults and those with an educational level less than a university degree. CONCLUSIONS: To improve the effectiveness of contact tracing, educational campaigns, such as reducing the fear and stigma associated with COVID-19, may be important. Furthermore, it is essential to understand that individuals may have contacts whom they do not wish to disclose to others and to be considerate when handling such situations.

EVEA: A System of Activating Multi-group Online Communication

Online communication is rapidly replacing face-to-face group communication in real space due to COVID-19 pandemic. However, in online group communication, when the number of participants increases and the entire members are arbitrarily divided into groups, some participants find it difficult to decide which group to join;it becomes difficult to see the topics discussed in other groups. To overcome the problem, we are developing a system called EVEA to assist the online group communication for text chatting. In EVEA, the discussed topics and the activeness of discussions based on our metrics in other groups are provided to participants as a hint for deciding which group to join. In this paper, we describe an overview of EVEA and explain how the system is designed.

Preventing infectious diseases outbreaks at exercise facilities. (Special Issue: Managing sport and leisure in the era of Covid-19.)

Exercise facilities play an important role in enhancing physical fitness and in supporting an active lifestyle among users. During the global coronavirus disease 2019 (COVID-19) pandemic, exercise facilities have been shut as part of the "physical distancing" policies in many countries. Exercise facilities have been considered "high-risk" places for transmission because of their enclosed environment, shared equipment and the close contact between users and staff. In Japan, in response to the COVID-19 clusters developed from the exercise facilities in the early phase of pandemic, the Fitness Industry Association of Japan released guidelines for gym managers, workers, and users in March. This commentary aims to introduce exercise facilities guidelines in Japan. This article provides reference for the rest of the world to reopen exercise facilities safely in the post pandemic period or to prevent future outbreaks of infectious disease.

Adoption of personal protective measures by ordinary citizens during the COVID-19 outbreak in Japan. (Coronavirus (COVID-19) collection.)

Objectives: To clarify the implementation status of personal protective measures by ordinary citizens in Japan during the coronavirus disease 2019 (COVID-19) outbreak.

Itocon - A system for visualizing the congestion of bus stops around Ito campus in real-time: Poster abstract

Due to the spread of COVID-19, we are desired to avoid crowded places including public transportation. Kyushu University has the largest campus in Japan, called "Ito campus", and the population there is about 20,000 in which 23% of students and 46% of staff use a bus for reaching the campus. The lectures in the first half of 2020 have been conducted online, but we plan to resume face-to-face lectures gradually. At that time, we expect the bus stops and buses to be crowded, especially during rush hour. In this paper, we introduce a system, called Itocon, to visualize the human congestion of bus stops around the campus. Itocon aggregates the sensing data from various sensors deployed around the target bus stops, and calculate and visualize the congestion degrees in real-time. Itocon is developed as a web application to avoid requesting the application install. We hope all the people who use a bus change their moving time based on the congestion information for avoiding human crowds. We explain the details and the future prospects of Itocon. © 2020 ACM.