ABSTRACT
Aspirations to slow down the spread of novel Coronavirus (COVID-19) resulted in unprecedented restrictions on personal and work-related travels in various nations across the globe in 2020. 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. The paper develops a generalizable quantitative framework to evaluate the commute-related risk arising from inter-district and intra-district travel by combining nonparametric data envelopment analysis for vulnerability assessment with transportation network analysis. It demonstrates the application of the proposed model for establishing travel corridors within and across Gujarat and Maharashtra, two Indian states that have reported many COVID-19 cases since early April 2020. The findings suggest that establishing travel corridors between a pair of districts solely based on the health vulnerability indices of the origin and destination discards the en-route travel risks from the prevalent pandemic, underestimating the threat. For example, while the resultant of social and health vulnerabilities of Narmada and Vadodara districts is relatively moderate, the en-route travel risk exacerbates the overall travel risk of travel between them. The study provides a quantitative framework to identify the alternate path with the least risk and hence establish low-risk travel corridors within and across states while accounting for social and health vulnerabilities in addition to transit-time related risks.
ABSTRACT
Aspirations to slow down the spread of novel Coronavirus (COVID-19) resulted in unprecedented restrictions on personal and work-related travels in various nations across the globe in 2020. 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. The paper develops a generalizable quantitative framework to evaluate the commute-related risk arising from inter-district and intra-district travel by combining nonparametric data envelopment analysis for vulnerability assessment with transportation network analysis. It demonstrates the application of the proposed model for establishing travel corridors within and across Gujarat and Maharashtra, two Indian states that have reported many COVID-19 cases since early April 2020. The findings suggest that establishing travel corridors between a pair of districts solely based on the health vulnerability indices of the origin and destination discards the en-route travel risks from the prevalent pandemic, underestimating the threat. For example, while the resultant of social and health vulnerabilities of Narmada and Vadodara districts is relatively moderate, the en-route travel risk exacerbates the overall travel risk of travel between them. The study provides a quantitative framework to identify the alternate path with the least risk and hence establish low-risk travel corridors within and across states while accounting for social and health vulnerabilities in addition to transit-time related risks.
ABSTRACT
Nationwide lockdown for COVID-19 created an urgent demand for public transportation among migrant workers stranded at different parts of India to return to their native places. Arranging transportation could spike the number of COVID-19 infected cases. Hence, this paper investigates the potential surge in confirmed and active cases of COVID-19 infection and assesses the train and bus fleet size required for the repatriating migrant workers. The expected to repatriate migrant worker population was obtained by forecasting the 2011 census data and comparing it with the information reported in the news media. A modified susceptible-exposed-infected-removed (SEIR) model was proposed to estimate the surge in confirmed and active cases of COVID-19 patients in India's selected states with high outflux of migrants. The developed model considered combinations of different levels of the daily arrival rate of migrant workers, total migrant workers in need of transportation, and the origin of the trip dependent symptomatic cases on arrival. Reducing the daily arrival rate of migrant workers for states with very high outflux of migrants (i.e., Uttar Pradesh and Bihar) can help to lower the surge in confirmed and active cases. Nevertheless, it could create a disparity in the number of days needed to transport all repatriating migrant workers to the home states. Hence, travel arrangements for about 100,000 migrant workers per day to Uttar Pradesh and Bihar, about 50,000 per day to Rajasthan and Madhya Pradesh, 20,000 per day to Maharashtra and less than 20,000 per day to other states of India was recommended.