Pattern of road traffic fatalities in India: a case study of Chhattisgarh State

India does not have a national crash-level surveillance system. Instead, police stations report crashes in standardized tables that are summarized at the state level. Since tabulations provide limited insights into crash patterns, we developed a crash database from police First Information Reports (FIRs) on all (<i>n</i> = 11,175) fatalities in Chhattisgarh during 2017–2019. The data show that not only were motorcycle riders the most common victims (59% of fatalities), but they also posed a substantial threat to other road users. Motorcycle impacts caused 16% of all fatalities (37% of pedestrians). Although truck occupants comprised only 5% of fatalities, trucks were the most common striking vehicle. Remarkably, 94% of tractor occupants were killed in single-vehicle crashes, and more than were rollovers. The FIR database provides a richer description of crashes than tabulations and an important information source for safety management. India and other LMICs will benefit substantially by investing in crash surveillance systems.

Publication Details

Journal
Figshare
Published
2025-01-01
DOI
https://doi.org/10.6084/m9.figshare.28716318.v1
Primary Topic
Genetic diversity and population structure
Type
article
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article

Pattern of road traffic fatalities in India: a case study of Chhattisgarh State

Figshare
Genetic diversity and population structure
article

Pattern of road traffic fatalities in India: a case study of Chhattisgarh State

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Abstract

India does not have a national crash-level surveillance system. Instead, police stations report crashes in standardized tables that are summarized at the state level. Since tabulations provide limited insights into crash patterns, we developed a crash database from police First Information Reports (FIRs) on all (<i>n</i> = 11,175) fatalities in Chhattisgarh during 2017–2019. The data show that not only were motorcycle riders the most common victims (59% of fatalities), but they also posed a substantial threat to other road users. Motorcycle impacts caused 16% of all fatalities (37% of pedestrians). Although truck occupants comprised only 5% of fatalities, trucks were the most common striking vehicle. Remarkably, 94% of tractor occupants were killed in single-vehicle crashes, and more than were rollovers. The FIR database provides a richer description of crashes than tabulations and an important information source for safety management. India and other LMICs will benefit substantially by investing in crash surveillance systems.

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Genetic diversity and population structure
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