Treffer: Road traffic accidents & climatic factors in an urban area in Kerala, India: A time series approach.

Background & objectives Road traffic accidents (RTAs) are increasing globally and its relationship with climatic factors are less studied. This study aimed to determine the trends and patterns of RTAs and its relationship with climate factors in Urban Ernakulam district, Kerala. Methods This retrospective analysis used 47,582 RTA records from the Crime Records Bureau, Ernakulam City Police, Kerala, India and daily meteorological data of 2,149 days (2018-2023) from the department of Atmospheric Science, Cochin University for Science and Technology, Kerala. The combined dataset was analysed using Python, with descriptive statistics, time series analysis, autocorrelation function (ACF) analysis, and the seasonal autoregressive integrated moving average (SARIMA) model conducted. Results Of the total RTAs, one-fifth (n=9817, 20.6%) occurred in 2023. Two wheelers (motorcycles) were the most common (n=27515, 57.8%) vehicle type, minor roads were the most frequent sites (n=29801, 62.6%), and over-speeding contributed to over one third (n=17489, 36%) of the RTAs. RTAs were most common (n=15829, 33.3%) in the afternoon 12.00-18.00 PM and the majority (n=33799 ,71%) of RTA victims suffered grievous injuries. Minimum temperature (<21.71°C) and rainfall (<2.15 mm) were significantly associated with RTAs. Lower minimum temperatures had a negative correlation with RTAs during winter (-0.21 to -0.28) in 2022-23, and the monsoon season (-0.20 to -0.26) in 2020-21. Higher rainfall was negatively correlated (-0.2 to - 0.22) with RTAs during the monsoon in 2018-19. Grievous injury patterns were influenced by past three-month trends and recurring cycles every three yr, reflecting a mix of short-term seasonal, medium-term biennial, and long-term triennial factors. Interpretation & conclusions Adverse weather conditions such as lower temperatures and less rainfall increased the risk of RTAs. Long term studies, free from external interruptions, are needed to get deeper insights into these relations. Targeted interventions and advisories to reduce RTAs, especially before monsoon season are essential.