Epidemiological Characteristics and Temporal Patterns of E-Scooter Crashes in Hungary: A National One-Year Assessment

Micromobility has increasingly gained popularity in the sustainable urban transport mix but poses safety challenges as well. Safety evidence on micromobility in Central and Eastern Europe is still scarce at the national level. This paper presents a national epidemiological description of 836 e-scooter crashes reported in Hungary in 2024 based on national crash statistics of the Hungarian Central Statistical Office (KSH/HCSO). Descriptive statistics are used to describe the characteristics of crash severity, hour of occurrence, weather condition, nature of accident, and road shape. Chi-square tests were applied to examine whether crash severity was associated with these temporal, environmental, and crash-context characteristics. For inferential analysis, crash severity was dichotomized as slight versus serious/fatal. Monte Carlo permutation procedures were used to estimate p-values, and Cramér’s V was calculated to quantify the strength of association. Slight-injury crashes accounted for 63.4% of recorded cases, serious-injury crashes for 35.8%, and fatal crashes for 0.8%. Crash occurrence was concentrated in the afternoon, with 192 crashes (23.0%) recorded between 15:00 and 17:00 and the highest hourly frequency occurring at 16:00 (n = 79). The nature of the accident was significantly associated with crash severity (χ2(11) = 26.36, Monte Carlo p = 0.0037, Cramér’s V = 0.178), whereas weather condition, road shape, and hour of day were not. These findings establish a national descriptive baseline for recorded e-scooter crashes in Hungary and identify crash mechanism as an important dimension for further safety research on the integration of micromobility into the transportation system.