{"id":3453,"date":"2025-06-03T10:33:37","date_gmt":"2025-06-03T07:33:37","guid":{"rendered":"https:\/\/fti.dp.ua\/conf\/?p=3453"},"modified":"2025-09-23T10:37:07","modified_gmt":"2025-09-23T07:37:07","slug":"cims-311","status":"publish","type":"post","link":"https:\/\/fti.dp.ua\/conf\/2025\/cims-311\/","title":{"rendered":"Statistical Analysis and Forecasting of Injury-Related Road Accidents in Dnipropetrovsk Region"},"content":{"rendered":"\n

Statistical Analysis and Forecasting of Injury-Related Road Accidents in Dnipropetrovsk Region<\/h1>\n\n\n\n
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Tetiana Rusakova<\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/h5>\n\n\n\n

ORCID: https:\/\/orcid.org\/0000-0001-5526-3578<\/a><\/em><\/p>\n\n\n\n

Oles Honchar Dnipro National University<\/em><\/p>\n<\/div><\/div>\n\n\n\n

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Purpose<\/strong>. The study aims to identify seasonal and weather-related factors influencing the number of road traffic accidents (RTAs) with casualties in Dnipropetrovsk Oblast, in order to provide a basis for short-term accident forecasting and improve the effectiveness of traffic safety prevention measures.\u00a0Design \/ Method \/ Approach<\/strong>. The study is based on monthly statistical data from 2020 to 2025, sourced from the Patrol Police of Ukraine and the Main Department of Statistics in Dnipropetrovsk Oblast. The analysis integrates boxplot visualization, one- and two-way ANOVA, correlation analysis, and multiple regression analysis, accounting for temperature, precipitation, humidity, wind speed, and calendar month.\u00a0Findings.\u00a0<\/strong>A statistically significant impact of the calendar month was confirmed as the main seasonal factor. The regression model showed a clear link between RTAs and combined weather and calendar variables. Accident rates peaked in summer\u2013autumn and dropped in winter\u2013spring, with February showing the least variation. Monthly factors proved useful for short-term forecasting. Time series analysis enabled tracking trends (2020\u20132024) and projecting them through 2026.\u00a0Theoretical Implications<\/strong>. The results enhance the understanding of the interplay between seasonal, calendar, and weather-related factors and accident rates within a regional context.\u00a0Practical Implications<\/strong>. The findings can be used by local authorities, police, and road safety services to plan preventive measures during periods of increased accident risk.\u00a0Originality \/ Value<\/strong>. A comprehensive approach is proposed for analyzing RTAs at the regional level, involving various types of statistical analysis and seasonal forecasting. The methodology can be adapted for other regions of Ukraine.\u00a0Research Limitations \/ Future Research<\/strong>. The study is limited to the 2020\u20132025 period and does not account for social, behavioral, or infrastructure-related factors. Future research should incorporate additional explanatory variables and apply multifactor forecasting methods.\u00a0Article Type<\/strong>. Applied Research.<\/p>\n\n\n\n

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ACCESS ARTICLE<\/a><\/div>\n<\/div>\n\n\n\n
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CIMS 2025 The Awakening of Nature<\/a><\/div>\n\n
Ecology, industrial and environmental safety<\/a><\/div><\/div>\n\n\n\n
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Statistical Analysis and Forecasting of Injury-Related Road Accidents in Dnipropetrovsk Region Tetiana Rusakova ORCID: https:\/\/orcid.org\/0000-0001-5526-3578 Oles Honchar Dnipro National University Purpose. The study aims to identify seasonal and weather-related factors influencing the number of road traffic accidents (RTAs) with casualties in Dnipropetrovsk Oblast, in order to provide a basis for short-term accident forecasting and improve the effectiveness of traffic safety prevention measures.\u00a0Design \/ Method \/ Approach. The study is based on monthly statistical data from 2020 to 2025, sourced from … <\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[22],"tags":[39],"class_list":["post-3453","post","type-post","status-publish","format-standard","hentry","category-ecosafe","tag-cims-2025-the-awakening-of-nature"],"_links":{"self":[{"href":"https:\/\/fti.dp.ua\/conf\/wp-json\/wp\/v2\/posts\/3453","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/fti.dp.ua\/conf\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/fti.dp.ua\/conf\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/fti.dp.ua\/conf\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/fti.dp.ua\/conf\/wp-json\/wp\/v2\/comments?post=3453"}],"version-history":[{"count":1,"href":"https:\/\/fti.dp.ua\/conf\/wp-json\/wp\/v2\/posts\/3453\/revisions"}],"predecessor-version":[{"id":3454,"href":"https:\/\/fti.dp.ua\/conf\/wp-json\/wp\/v2\/posts\/3453\/revisions\/3454"}],"wp:attachment":[{"href":"https:\/\/fti.dp.ua\/conf\/wp-json\/wp\/v2\/media?parent=3453"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/fti.dp.ua\/conf\/wp-json\/wp\/v2\/categories?post=3453"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/fti.dp.ua\/conf\/wp-json\/wp\/v2\/tags?post=3453"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}