Increase in traffic injury crashes following the 2016 Kumamoto earthquake in Japan: A model comparison

Abstract

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
• traffic crashes with injury or death
• time-series count data model
• Poisson regression model
• negative binomial regression model
• SARIMAX model

Acknowledgments

We are grateful to the participants at the 63rd JSCE IP Conferences, 2021, for their helpful comments on a previous version of this paper.

Conflicts of interest/competing interests

No potential competing interest was reported by the authors.

Availability of data and material

The data that support the findings of this study are freely available on Kumamoto and Fukuoka city website.

Code availability

The codes that support the findings of this study are available from the corresponding author upon reasonable request.

Additional information

Funding

This work was supported by the research fund at Kumamoto University.