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How Change of Public Transportation Usage Reveals Fear of the SARS Virus in a City

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  • Kuo-Ying Wang

Abstract

The outbreaks of the severe acute respiratory syndrome (SARS) epidemic in 2003 resulted in unprecedented impacts on people's daily life. One of the most significant impacts to people is the fear of contacting the SARS virus while engaging daily routine activity. Here we use data from daily underground ridership in Taipei City and daily reported new SARS cases in Taiwan to model the dynamics of the public fear of the SARS virus during the wax and wane of the SARS period. We found that for each reported new SARS case there is an immediate loss of about 1200 underground ridership (the fresh fear). These daily loss rates dissipate to the following days with an e-folding time of about 28 days, reflecting the public perception on the risk of contacting SARS virus when traveling with the underground system (the residual fear). About 50% of daily ridership was lost during the peak of the 2003 SARS period, compared with the loss of 80% daily ridership during the closure of the underground system after Typhoon Nari, the loss of 50–70% ridership due to the closure of the governmental offices and schools during typhoon periods, and the loss of 60% daily ridership during Chinese New Year holidays.

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  • Kuo-Ying Wang, 2014. "How Change of Public Transportation Usage Reveals Fear of the SARS Virus in a City," PLOS ONE, Public Library of Science, vol. 9(3), pages 1-10, March.
  • Handle: RePEc:plo:pone00:0089405
    DOI: 10.1371/journal.pone.0089405
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    1. Stephen Eubank & Hasan Guclu & V. S. Anil Kumar & Madhav V. Marathe & Aravind Srinivasan & Zoltán Toroczkai & Nan Wang, 2004. "Modelling disease outbreaks in realistic urban social networks," Nature, Nature, vol. 429(6988), pages 180-184, May.
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