  Aspirations to slow down the spread of Novel Coronavirus (SARS-CoV2) resulted
in unprecedented restrictions on personal and work-related travels in various
nations across the globe. As a consequence, economic activities within and
across the countries were almost halted. As restrictions loosen and cities
start to resume public and private transport to revamp the economy, it becomes
critical to assess the commuters' travel-related risk in light of the ongoing
pandemic. We develop a generalizable quantitative framework to evaluate the
commute-related risk arising from inter-district and intra-district travels by
combining Nonparametric Data Envelopment analysis for vulnerability assessment
with transportation network analysis. We demonstrate the application of the
proposed model for establishing travel corridors or travel bubbles within and
across Gujarat and Maharashtra, two Indian states that have reported many
SARS-CoV2 cases since early April 2020. Our findings suggest that establishing
the travel bubble between a pair of districts solely based on the health
vulnerability indices of origin-destination discards the en-route travel risks
due to prevalent pandemic, hence underestimating the threat. For example, while
the resultant of social and health vulnerabilities of Narmada and Vadodara's
districts is relatively moderate, the en-route travel risk exacerbates the
overall travel risk. Our study provides actionable insights to users into
choosing the alternate path with the least risk and can inform political
decisions to establish low-risk travel corridors within and across the states
while accounting for social and health vulnerabilities in addition to
transit-time related risks.
