Objective: Following natural disasters, the number of motor vehicle crashes may increase as drivers are often forced to drive under stressful conditions. This study aims to analyze the changes in motor vehicle crashes that resulted in injury or death (injury crash) following the 2016 Kumamoto earthquake in Japan. An existing study reported that the increased crashes resulted in property damage following the earthquake; however, the effects on injury crashes remain unreported.
Methods: Interrupted time series analysis is employed to investigate the changes in injury crashes following the earthquake. The results are compared based on several time series models, including negative binomial and autoregressive integrated moving average models. Monthly injury-crash data from 2011 to 2020 in Kumamoto and Fukuoka city is used.
Results: The results reveal a 1,642-count or 20% increase (1.20-times increase, 95% confidence interval: 1.12, 1.27) in injury crashes due to the earthquake in Kumamoto city, where the earthquake damage was heavy. In contrast, statistically significant change is not detected in Fukuoka city, where the earthquake damage is negligible.
Conclusion: The results indicate that the earthquake has increased the motor-vehicle-crash risk and that traffic crash alerts are important following disasters.
Keywords: Earthquake disaster; Poisson regression model; SARIMAX model; negative binomial regression model; time-series count data model; traffic crashes with injury or death.