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Interactive COVID-19 Mobility Impact and Social Distancing Analysis Platform.
Zhang, Lei; Darzi, Aref; Ghader, Sepehr; Pack, Michael L; Xiong, Chenfeng; Yang, Mofeng; Sun, Qianqian; Kabiri, Aliakbar; Hu, Songhua.
  • Zhang L; Maryland Transportation Institute, Department of Civil and Environmental Engineering, University of Maryland, College Park, MD.
  • Darzi A; Maryland Transportation Institute, Department of Civil and Environmental Engineering, University of Maryland, College Park, MD.
  • Ghader S; Maryland Transportation Institute, Department of Civil and Environmental Engineering, University of Maryland, College Park, MD.
  • Pack ML; Center for Advanced Transportation Technology Laboratory, University of Maryland, College Park, MD.
  • Xiong C; Maryland Transportation Institute, Department of Civil and Environmental Engineering, University of Maryland, College Park, MD.
  • Yang M; Maryland Transportation Institute, Department of Civil and Environmental Engineering, University of Maryland, College Park, MD.
  • Sun Q; Maryland Transportation Institute, Department of Civil and Environmental Engineering, University of Maryland, College Park, MD.
  • Kabiri A; Maryland Transportation Institute, Department of Civil and Environmental Engineering, University of Maryland, College Park, MD.
  • Hu S; Maryland Transportation Institute, Department of Civil and Environmental Engineering, University of Maryland, College Park, MD.
Transp Res Rec ; 2677(4): 168-180, 2023 Apr.
Article in English | MEDLINE | ID: covidwho-2320840
ABSTRACT
The research team has utilized privacy-protected mobile device location data, integrated with COVID-19 case data and census population data, to produce a COVID-19 impact analysis platform that can inform users about the effects of COVID-19 spread and government orders on mobility and social distancing. The platform is being updated daily, to continuously inform decision-makers about the impacts of COVID-19 on their communities, using an interactive analytical tool. The research team has processed anonymized mobile device location data to identify trips and produced a set of variables, including social distancing index, percentage of people staying at home, visits to work and non-work locations, out-of-town trips, and trip distance. The results are aggregated to county and state levels to protect privacy, and scaled to the entire population of each county and state. The research team is making their data and findings, which are updated daily and go back to January 1, 2020, for benchmarking, available to the public to help public officials make informed decisions. This paper presents a summary of the platform and describes the methodology used to process data and produce the platform metrics.

Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies Language: English Journal: Transp Res Rec Year: 2023 Document Type: Article Affiliation country: 03611981211043813

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies Language: English Journal: Transp Res Rec Year: 2023 Document Type: Article Affiliation country: 03611981211043813