Your browser doesn't support javascript.
Correlation between the Level of Social Distancing and Activity of Influenza Epidemic or COVID-19 Pandemic: A Subway Use-Based Assessment.
Seong, Hye; Hong, Jin-Wook; Hyun, Hak-Jun; Yoon, Jin-Gu; Noh, Ji-Yun; Cheong, Hee-Jin; Kim, Woo-Joo; Jung, Jae-Hun; Song, Joon-Young.
  • Seong H; Department of Internal Medicine, Korea University College of Medicine, Guro Hospital, Seoul 08308, Korea.
  • Hong JW; Artificial Intelligence and Big-Data Convergence Center, Gachon University College of Medicine and Science, Incheon 21565, Korea.
  • Hyun HJ; Department of Preventive Medicine, Gachon University College of Medicine, Incheon 21565, Korea.
  • Yoon JG; Department of Internal Medicine, Korea University College of Medicine, Guro Hospital, Seoul 08308, Korea.
  • Noh JY; Department of Internal Medicine, Korea University College of Medicine, Guro Hospital, Seoul 08308, Korea.
  • Cheong HJ; Department of Internal Medicine, Korea University College of Medicine, Guro Hospital, Seoul 08308, Korea.
  • Kim WJ; Asian Pacific Influenza Institute, Seoul 08308, Korea.
  • Jung JH; Department of Internal Medicine, Korea University College of Medicine, Guro Hospital, Seoul 08308, Korea.
  • Song JY; Asian Pacific Influenza Institute, Seoul 08308, Korea.
J Clin Med ; 10(15)2021 Jul 29.
Article in English | MEDLINE | ID: covidwho-1335126
ABSTRACT
Social distancing is an effective measure to mitigate the spread of novel viral infections in the absence of antiviral agents and insufficient vaccine supplies. Subway utilization density may reflect social activity and the degree of social distancing in the general population.; This study aimed to evaluate the correlations between subway use density and the activity of the influenza epidemic or coronavirus disease 2019 (COVID-19) pandemic using a time-series regression method. The subway use-based social distancing score (S-SDS) was calculated using the weekly ridership of 11 major subway stations. The temporal association of S-SDS with influenza-like illness (ILI) rates or the COVID-19 pandemic activity was analyzed using structural vector autoregressive modeling and the Granger causality (GC) test. During three influenza seasons (2017-2020), the time-series regression presented a significant causality from S-SDS to ILI (p = 0.0484). During the COVID-19 pandemic in January 2020, S-SDS had been suppressed at a level similar to or below the average of the previous four years. In contrast to the ILI rate, there was a negative correlation between COVID-19 activity and S-SDS. GC analysis revealed a negative causal relationship between COVID-19 and S-SDS (p = 0.0098).; S-SDS showed a significant time-series association with the ILI rate but not with COVID-19 activity. When public transportation use is sufficiently suppressed, additional social mobility restrictions are unlikely to significantly affect COVID-19 pandemic activity. It would be more important to strengthen universal mask-wearing and detailed public health measures focused on risk activities, particularly in enclosed spaces.
Keywords

Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies / Prognostic study Topics: Vaccines Language: English Year: 2021 Document Type: Article

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies / Prognostic study Topics: Vaccines Language: English Year: 2021 Document Type: Article