This study examined the relationship between the lockdown during the COVID-19 pandemic and the severity of injuries sustained by drivers involved in run-off-road (ROR) crashes. A random parameter ordered logit (RPOL) modeling framework was utilized to account for the ordinal nature of severity outcome and capture the potential unobserved heterogeneity. The data used in this study contained ROR crashes that occurred in the state of Florida from April to September for 2019 and 2020 representing non-pandemic and pandemic time periods, respectively. Separate driver injury severity models were developed across the two time periods, and the overall stability of the model estimates was examined through likelihood ratio tests. The impacts of various potential contributing factors, including crash-, driver-, and vehicle-related variables, roadway geometric characteristics, environmental conditions, and traffic-specific factors, were assessed. Although the developed models share some common features, the analysis results showed that the model specifications indicated a strong temporal instability among the estimated parameters. Compared to the non-pandemic period, the following variables resulted in increased driver injury severity in ROR crashes during the pandemic: drivers 65 years or older, careless driving, and absence of traffic control devices