The Impact of Bike Share Services in Disease Transmission: Numerical Exploration of the COVID 19 Spread in Washington DC Through Modeling and Sensitivity Analysis

Covid-19 is a respiratory disease cause by the virus SARS-CoV-2. This corovirus first emerged in the city of Wuhan, China, in December of 2019. Due to its ability to stay alive/active in air and on different surfaces for a given period of time, this virus was widely spread with a high contagion rate impacting considerable portions of different populations with different socio-economic characteristics. The World Health Organization declared Covid-19 as a pandemic in March of 2020. Because of the nature of the Covid-19 transmission, public transport is considered as a driver for human to human transmission. In this study, the authors focus mainly on cyclist’s behavior as a function of the Covid-19 transmission evolution in an urban environment; the impact of the Covid-19 on Washington DC’s Capital Bikeshare system is analyzed. Moreover, the possible relationship between the bikeshare usage and the Covid-19 transmission is explored. In order to investigate the transmission via the use of bikeshare system, a probabilistic contagion model is adopted. From the prediction outcome of the contagion model it, is found that 1 infected people can infect a maximum of 5 people and 3 infected people can infect a maximum of 27 people during a 3-day interval. The peak value of the 7-day moving average of infected people is 181: the maximum impact of Covid-19 transmission due to the usage of bikeshare services remain significant. However, if compared to other modes of public transport such as light rails and buses, bike sharing is safer for its direct users.

Language

  • English

Media Info

  • Media Type: Digital/other
  • Features: Figures; References; Tables;
  • Pagination: 17p

Subject/Index Terms

Filing Info

  • Accession Number: 01764281
  • Record Type: Publication
  • Report/Paper Numbers: TRBAM-21-04050
  • Files: TRIS, TRB, ATRI
  • Created Date: Feb 4 2021 11:00AM