Public transport disruptions caused by the COVID-19 pandemic had wide-ranging impacts on the ability of individuals to access health care. Individuals with opioid use disorder represent an especially vulnerable population due to the necessity of frequent, supervised doses of opioid agonists. Focused on Toronto, a major Canadian city suffering from the opioid epidemic, this analysis uses novel realistic routing methodologies to quantify how travel times to individuals' nearest clinics changed due to public transport disruptions from 2019 to 2020. This analysis uses entirely open-source data sources to estimate the vulnerable populations that were impacted by the largest transport disruptions in the city's history. Individuals seeking opioid agonist treatment face very constrained windows of access due to the need to manage work and other essential activities. As even small changes to travel times can lead to missed appointments and heighten the chances of overdose and death, understanding the distribution of those most impacted can help inform future policy measures to ensure adequate access to care.