2020/09/09 by Jungwoo Cho, Cho, Jungwoo, Yu Yol Shin +13
Computer Science · Economics, Econometrics and Finance · Mathematics · Psychology · #COVID-19 Pandemic Impacts #COVID-19 and Mental Health #COVID-19 epidemiological studies #Computers and Society (cs.CY) #FOS: Computer and information sciences #cs.CY
paper · pdf · doi:10.48550/arxiv.2009.09073
22 pages of manuscript, 19 pages of supplementary information
arxiv created 2020/09/09 · openalex publication_date 2020/09/09 · arxiv updated 2020/09/22 · openalex created_date 2020/09/25 · openalex updated_date 2026/07/28
Battle with COVID-19 turned out to be a marathon, not a sprint, and behavioral adjustments have been unavoidable to stay viable. In this paper, we employ a data-centric approach to investigate individual mobility adaptations and mask-wearing in Seoul, South Korea. We first identify six epidemic phases and two waves based on COVID-19 case count and its geospatial dispersion. The phase-specific linear models reveal the strong, self-driven mobility reductions in the first escalation and peak with a common focus on public transit use and less-essential weekend/afternoon trips. However, comparable reduction was not present in the second wave, as the shifted focus from mobility to mask-wearing was evident. Although no lockdowns and gentle nudge to wear mask seemed counter-intuitive, simple and persistent communication on personal safety has been effective and sustainable to induce cooperative behavioral adaptations. Our phase-specific analyses and interpretation highlight the importance of targeted response consistent with the fluctuating epidemic risk.