On-site Dining in Tokyo During the COVID-19 Pandemic: Time Series Analysis Using Mobile Phone Location Data

• DOI: 10.2196/27342
• Publication Date: 2021-04-22T19:02:17Z
• Authors: Miharu Nakanishi; Ryosuke Shibasaki; Syudo Yamasaki; Satoshi Miyazawa; Satoshi Usami; Hiroshi Nishiura; Atsushi Nishida
• Keywords: Pandemic

Background During the second wave of COVID-19 in August 2020, Tokyo Metropolitan Government implemented public health and social measures to reduce on-site dining. Assessing associations between human behavior, infection, is essential understand achievable reductions cases identify factors driving changes dynamics. Objective The aim this study was investigate association nighttime population volumes, epidemic, implementation Tokyo. Methods We used mobile phone location data estimate populations 10 PM midnight seven metropolitan areas. Mobile trajectories were distinguish extract dining from stay-at-work stay-at-home behaviors. Numbers new symptom onsets obtained. Weekly mobility infection March 1 November 14, analyzed using a vector autoregression model. Results An increase number observed week after volume increased (coefficient=0.60, 95% CI 0.28 0.92). effective reproduction significantly 3 weeks (coefficient=1.30, 0.72 1.89). following reports decreasing numbers confirmed (coefficient=–0.44, –0.73 –0.15). Implementation restaurants bars not associated with (coefficient=0.004, –0.07 0.08). Conclusions started incidence announced. Considering time lags behavior changes, should be planned advance surge an sufficiently informed by data.