Abstract
Background
Road traffic accidents (RTAs) are a leading cause of mortality and disability in Nepal. Despite the scale of the problem, comprehensive province-level analyses covering recent years remain limited. This study describes the pattern of RTAs across all seven provinces of Nepal over four fiscal years.
Design and methods
A cross-sectional record review was conducted using RTA records obtained from Nepal Traffic Police departments across all provinces. Records spanning fiscal years 2020/21-2023/24 AD were analysed. Variables extracted included province and year of incident, urban/rural classification, driver age group, and vehicle type. Descriptive statistics were computed using SPSS version 20. Data for 2023/24 cover only the first five months of the fiscal year and should be interpreted with caution.
Results
A total of 74,929 RTAs were recorded over the study period. Annual totals increased from 20,640 in 2020/21 to a peak of 24,537 in 2021/22, before declining modestly to 23,597 in 2022/23. The Kathmandu Valley consistently recorded the highest accident burden (10,733 in 2021/22; 10,675 in 2022/23). Drivers aged 25–40 years accounted for the largest proportion of recorded driver involvements with known age (58,614; 50.2%), followed by those aged 16-25 years (34,886; 29.9%). Motorcycles and scooters were the most commonly involved vehicle type. Urban areas accounted for 30,401 accidents (59.0% of accidents with known location), though rural predominance was observed in Madhesh and Koshi provinces.
Conclusions
RTAs in Nepal are concentrated among young and middle-aged adult drivers, predominantly involve two-wheeled vehicles, and exhibit marked urban-rural variation across provinces. These findings support age-targeted safety interventions, strengthened motorcycle helmet enforcement, and geographically differentiated road safety strategies.
Keywords: Nepal, road traffic accident, road traffic injury, epidemiology, cross-sectional study, traffic police records
Significance for public health
Road traffic accidents are a major and growing cause of mortality, disability, and economic loss in Nepal. Between 2008 and 2018, government records reported more than 7,400 deaths from RTAs a toll exceeding that of many communicable diseases during the same period. This study provides the first comprehensive province-level analysis of RTA patterns across all seven provinces of Nepal using four years of national Traffic Police records. By identifying the concentration of accidents among young and middle-aged drivers, the predominance of motorcycle and scooter involvement, and stark urban-rural disparities across provinces, the findings provide an evidence base for targeted, context-specific road safety interventions. The results directly inform policy priorities including age-targeted licensing reform, helmet law enforcement, urban traffic management, and rural road safety investment each with measurable potential to reduce preventable deaths and injuries at population level.
Background
Road transport is the most widely used mode of travel in Nepal, serving as the primary artery for economic activity, social connectivity, and daily mobility. Despite this dependence, Nepal’s road infrastructure remains insufficient relative to demand. With approximately 26,900 miles of road network and nearly two million registered vehicles, the combination of rapid motorisation and underdeveloped infrastructure has produced a steadily rising burden of road traffic accidents (RTAs).1,2
RTAs claim hundreds of lives annually and impose substantial physical, financial, and psychological consequences on survivors, families, and caregivers. 1 The mortality burden is striking: RTA fatalities recorded in 2009/10 (n = 614) exceeded deaths attributable to natural disasters during the same period and surpassed malaria deaths during the 2006 epidemic.3,4 RTIs rank as the 11th leading cause of disability-adjusted life years (DALYs) and the 12th leading cause of premature death in Nepal. 5
Globally, the World Health Organization estimates that approximately 1.3 million people die from RTAs each year, with more than 91% of fatalities occurring in low- and middle-income countries (LMICs). 6 In the South-East Asia Region, an estimated 40 deaths from road accidents occur every hour. 7 A systems approach one that examines interactions among vehicles, road users, and infrastructure is essential for evidence-based prevention. 8
Understanding the geographic distribution, temporal trends, and demographic characteristics of RTAs is a necessary first step toward developing targeted interventions. However, comprehensive province-level analyses of RTA patterns in Nepal remain limited: existing studies have tended to focus on single regions or to rely on outdated data, hindering the development of context-specific policy responses.
This study therefore aims to describe the pattern of RTAs across all seven provinces of Nepal over four fiscal years 2020/21 to 2023/24 AD, examining temporal trends, driver age group distribution, vehicle types involved, and urban-rural disparities, with the aim of informing evidence-based road safety policy and practice.
Design and methods
Study design and setting
A cross-sectional record review was conducted using secondary data from the national RTA records maintained by the Nepal Traffic Police. The study was carried out in 2024. The study encompassed all seven provinces of Nepal: Koshi, Madhesh, Bagmati, Gandaki, Lumbini, Karnali, and Sudurpashchim. The Kathmandu Valley comprising Kathmandu, Lalitpur, and Bhaktapur districts was analysed as a distinct geographical unit owing to its high traffic density and urban concentration. To avoid double-counting, accidents occurring within the Kathmandu Valley were excluded from Bagmati Province totals; the geographic analysis therefore used eight mutually exclusive categories — Koshi, Madhesh, Bagmati (excluding the Kathmandu Valley), Gandaki, Lumbini, Karnali, Sudurpashchim, and the Kathmandu Valley — with each accident event counted once. The Kathmandu Valley was reported separately to highlight its distinct burden as the national capital and principal urban centre, not omitted from the study. The study period spanned four fiscal years: 2020/21 AD, 2021/22 AD, 2022/23 AD, and 2023/24 AD. Data for fiscal year 2023/24 were available only up to approximately mid-September 2023, representing approximately five months of the fiscal year; these data are partial and should be interpreted with caution in year-on-year comparisons.
Data source and collection
Permission to access RTA records was obtained from Nepal Traffic Police departments in all seven provinces. Records were extracted from the official Nepal Traffic Police database, which compiles incident reports filed by traffic police personnel at the time of accident response or investigation. Variables extracted from each record included: year and province of incident; urban or rural area classification (as defined by Nepal Traffic Police jurisdictional classification); age group of the driver involved (16-25 years, 25-40 years, or above 40 years); and type of vehicle involved. Driver age was available in the Traffic Police database only in three predefined categories: 16–25 years, 25–40 years, and above 40 years. These categories were established in the source records and were retained without modification for the present analysis. Individual-level exact ages were not available. Data extraction was carried out by trained research assistants using a standardised data abstraction form. Records with unavailable, incomplete, or illegible information for a particular variable were coded as missing. These records remained included in analyses of other variables for which complete information was available.
Units of analysis
Three analytical units were used in this study. For analyses of geographic distribution, fiscal-year trends, and urban–rural location, the unit of analysis was the distinct road traffic accident event. Each accident event was counted once, irrespective of the number of drivers or vehicles involved. For the driver-age analysis, the unit of analysis was the individual driver involvement. If an accident involved more than one driver, each driver was counted as a separate observation. Consequently, the total number of driver involvements could exceed the total number of accident events. For the vehicle-type analysis, the unit of analysis was the individual vehicle involvement. Each vehicle involved in an accident was counted separately; therefore, a multi-vehicle accident contributed more than one observation to the vehicle-type analysis. The available dataset was aggregated and did not retain crash-level identifiers linking accident events to individual drivers and vehicles. It was therefore not possible to determine the number or proportion of accidents involving one, two, three, or more drivers or vehicles.
Data analysis
Data were entered into Microsoft Excel (Microsoft Corp., Redmond, WA, USA) and exported to SPSS version 20 (IBM Corp., Armonk, NY, USA) for analysis. Descriptive statistics frequencies and percentages were used to summarise all categorical variables. Descriptive statistics, including frequencies and percentages, were calculated using the appropriate unit of analysis. Province, fiscal year, and urban–rural distributions were analysed at the accident-event level. Driver age was analysed at the driver-involvement level, and vehicle type was analysed at the vehicle-involvement level. Multiple drivers or vehicles involved in the same accident were counted separately in the respective involvement-based analyses. Missing data were handled using available-case analysis for each variable; records with missing information for a particular variable were excluded only from the analysis of that variable.
Ethical considerations
Ethical approval was obtained from the Ethical Review Board (ERB) of the Nepal Health Research Council (NHRC) (reference number: 2907). Written permission to access and review RTA records was obtained from the Nepal Traffic Police. As the study involved only anonymised secondary records with no direct contact with individuals, individual informed consent was not required. All data were anonymised prior to analysis, and confidentiality was maintained throughout the study. The study was conducted in accordance with the Declaration of Helsinki (2013 revision).
Results
Overall pattern of RTAs by province and year
A total of 74,929 RTAs were recorded across Nepal over the four fiscal years included in this study (Table 1). The Kathmandu Valley consistently recorded the highest number of accidents in each fiscal year, with peak annual totals of 10,733 in 2021/22 and 10,675 in 2022/23. The national total increased from 20,640 in 2020/21 to a peak of 24,537 in 2021/22, then declined modestly to 23,597 in 2022/23. The 2023/24 total (6,155) represents only five months of data and is not directly comparable with full-year figures. Across all study years, Koshi, Madhesh, and Bagmati provinces reported the highest cumulative accident counts after the Kathmandu Valley, while Gandaki, Karnali, and Sudurpashchim consistently recorded the lowest (Figure 1). Bagmati Province figures reported here exclude the Kathmandu Valley, which is presented as a separate geographical category to avoid double-counting.
Table 1.
Total number of road traffic accidents (RTAs) by province and fiscal year.
| Province | 2023/24 AD | 2022/23 AD | 2021/22 AD | 2020/21 AD |
|---|---|---|---|---|
| Kathmandu Valley | 2,919 | 10,675 | 10,733 | 9,545 |
| Koshi Province | 747 | 3,510 | 3,820 | 3,131 |
| Madhesh Province | 1,560 | 5,988 | 5,711 | 3,983 |
| Bagmati Province | 303 | 1,361 | 1,798 | 1,512 |
| Gandaki Province | 91 | 374 | 408 | 405 |
| Lumbini Province | 228 | 892 | 1,164 | 1,211 |
| Karnali Province | 237 | 545 | 402 | 291 |
| Sudurpashchim Province | 70 | 252 | 501 | 562 |
| Total | 6,155 | 23,597 | 24,537 | 20,640 |
Data for 2023 cover only up to mid-September 2023 and are not directly comparable with full-year totals AD = Anno Domini.
Figure 1.
Total number of RTAs by province and fiscal year.
Age group of drivers involved in RTAs
Table 2 presents the distribution of driver age groups involved in accidents, aggregated across all study years. Across the 74,929 distinct accident events recorded during the study period, 116,702 driver involvements were included in the age-group analysis. The number of driver involvements exceeded the number of accident events because a single accident could involve more than one vehicle and driver. This represented an average of approximately 1.56 recorded driver involvements per accident event. Drivers aged 25–40 years accounted for the largest proportion of driver involvements in every province, representing 50.2% (58,614/116,702). Drivers aged 16–25 years represented 29.9% (34,886/116,702), while drivers aged above 40 years represented 19.9% (23,202/116,702).
Table 2.
Age distribution of driver involvements in road traffic accidents, by province, aggregated across all study years.
| Province | 16-25 Years n (%) | 25-40 Years n (%) | Above 40 Years n (%) | Total |
|---|---|---|---|---|
| Kathmandu Valley | 17,287 (28.3%) | 30,135 (49.3%) | 13,508 (22.1%) | 60,930 |
| Koshi Province | 3,988 (28.8%) | 6,647 (48.1%) | 3,358 (24.3%) | 13,993 |
| Madhesh Province | 8,298 (34.4%) | 12,294 (51.0%) | 3,384 (14.0%) | 24,106 |
| Bagmati Province | 1,842 (25.7%) | 4,344 (60.7%) | 1,029 (14.4%) | 7,163 |
| Gandaki Province | 510 (31.3%) | 824 (50.5%) | 311 (19.1%) | 1,630 |
| Lumbini Province | 1,544 (32.4%) | 2,383 (50.0%) | 889 (18.6%) | 4,764 |
| Karnali Province | 678 (34.8%) | 967 (49.6%) | 311 (15.9%) | 1,950 |
| Sudurpashchim Province | 739 (34.5%) | 1,020 (47.5%) | 412 (19.2%) | 2,147 |
| Total | 34,886 (29.9%) | 58,614 (50.2%) | 23,202 (19.9%) | 116,702 |
Row percentages indicate the proportion of drivers in each age group within each province. Percentages may not sum to 100% due to rounding. The unit of analysis is the individual driver involvement rather than the accident event. A single accident event may involve more than one vehicle and driver; therefore, the total number of driver involvements exceeds the total number of distinct accident events.
Urban versus rural distribution of RTAs
Table 3 and Figure 2 present the urban-rural distribution of accidents, aggregated across all study years. Urban–rural classification was available for 51,558 of the 74,929 accident events included in the study, representing 68.8% of all recorded accidents. Location information was unavailable or incomplete for 23,371 accidents (31.2%), which were excluded only from the urban–rural analysis. Among accidents with documented location, 30,401 (59.0%) occurred in urban areas and 21,157 (41.0%) occurred in rural areas. The Kathmandu Valley exhibited the most pronounced urban concentration, with 26,517 urban and 623 rural accidents. By contrast, Madhesh and Koshi provinces recorded more accidents in rural than in urban areas.
Table 3.
Urban–rural distribution of road traffic accidents with documented location, by province, aggregated across all study years.
| Province | Urban n (%) | Rural n (%) | Total |
|---|---|---|---|
| Kathmandu Valley | 26,517 (97.7%) | 623 (2.3%) | 27,140 |
| Koshi Province | 735 (13.2%) | 4,847 (86.8%) | 5,582 |
| Madhesh Province | 1,274 (10.1%) | 11,395 (89.9%) | 12,669 |
| Bagmati Province | 246 (14.0%) | 1,515 (86.0%) | 1,761 |
| Gandaki Province | 391 (52.1%) | 360 (47.9%) | 751 |
| Lumbini Province | 669 (33.4%) | 1,335 (66.6%) | 2,004 |
| Karnali Province | 338 (36.9%) | 578 (63.1%) | 916 |
| Sudurpashchim Province | 231 (31.4%) | 504 (68.6%) | 735 |
| Total | 30,401 (59.0%) | 21,157 (41.0%) | 51,558 |
Row percentages indicate the proportion of accidents in urban or rural areas within each province. Urban–rural classification was available for 51,558 of 74,929 accident events (68.8%). Location information was missing or incomplete for 23,371 accidents (31.2%); these records were excluded only from the urban–rural analysis. Geographic categories are mutually exclusive. The Bagmati Province category excludes accidents occurring in Kathmandu, Lalitpur, and Bhaktapur districts, which are presented separately as Kathmandu Valley.
Figure 2.
Distribution of RTAs by urban/rural area and province (aggregated across all study years).
Vehicle types involved in RTAs
Figure 3 presents the frequency of accidents by vehicle type, aggregated across all study years. Motorcycles and scooters were the vehicle category most frequently involved in RTAs across all provinces and years. Jeeps and cars constituted the second most commonly involved category. Together, these two vehicle types accounted for the majority of reported RTAs. Buses, trucks, tractors, bicycles, and other vehicle types were involved less frequently.
Figure 3.
Frequency of road traffic accidents by vehicle type (aggregated across all study years).
Discussion
This study provides a comprehensive province-level analysis of RTA patterns across all seven provinces of Nepal over four consecutive fiscal years. The findings reveal four consistent and interrelated patterns: concentration of accidents in the Kathmandu Valley; predominant involvement of drivers aged 25-40 years; high frequency of motorcycle and scooter involvement; and marked urban-rural variation across provinces. Each carries specific implications for road safety policy.
Geographic concentration in the Kathmandu Valley
The Kathmandu Valley consistently recorded the highest accident counts across all study years, reflecting the combination of high vehicle density, complex traffic infrastructure, inadequate pedestrian facilities, and insufficient enforcement of traffic regulations that characterise Nepal’s primary urban centre.9,10 Similar patterns of urban epicentres for road traffic injuries have been documented across rapidly urbanising LMICs, where population and vehicle growth routinely outpaces investment in safe road infrastructure. 6 The modest year-on-year fluctuations in Kathmandu Valley totals peaking at 10,733 in 2021/22 before declining slightly to 10,675 in 2022/23 likely reflect changes in reporting practices or short-term enforcement campaigns rather than sustained structural improvements. Long-term urban transport planning that prioritises safety, consistent with ‘safe systems’ principles embedded in Vision Zero frameworks, 11 is required to achieve durable reductions.
Predominant involvement of young and middle-aged drivers
Drivers aged 25-40 years accounted for 50.2% and those aged 16-25 years for 29.9% of accidents with documented driver age a combined 80.1% among working-age adults. This pattern is consistent with studies from China, 12 India, 13 and Vietnam, 14 where young and middle-aged adults are disproportionately represented in RTA statistics. In Nepal, this group comprises commercial drivers, daily commuters, and migrant workers whose livelihoods depend on road transport. The elevated risk among younger drivers likely reflects inexperience, risk-taking behaviours, and inconsistent licensing enforcement. 13 The lower involvement of drivers aged above 40 years (19.9%) should not divert attention from this group, as older road users may be more vulnerable to severe injury when accidents do occur. 15
Motorcycles and scooters as the most frequently involved vehicle type
Motorcycles and scooters were the most commonly involved vehicle type across all provinces and years, consistent with their dominance within Nepal’s vehicle fleet, where they account for approximately 80% of registered vehicles. 16 Their limited occupant protection makes riders disproportionately vulnerable to serious injury. 10 Comparable patterns have been documented in Vietnam, where motorcycles account for over 70% of RTAs, 8 and in India, where two-wheelers are implicated in a substantial proportion of fatal road traffic injuries. 3 The growing involvement of jeeps and cars in the Kathmandu Valley reflects increasing urban vehicle ownership and the resulting risk of mixed traffic collisions involving motorcyclists. 17
Beyond conventional two-wheelers, the rapid international growth of e-scooters and shared micromobility introduces new road-safety challenges. Police-reported data from Türkiye have characterised the accident patterns of e-scooter crashes 18 and situated e-scooters within broader urban micromobility systems. 19 A recent systematic review and meta-analysis reported that head, facial, and upper-extremity injuries predominate among e-scooter casualties, with fewer than three percent classified as severely injured. 20 Reviews of e-scooter crashes have similarly noted low rates of helmet use and frequent collisions with pedestrians and other vehicles. 21 Although electric micromobility devices are not yet separately recorded in Nepal’s Traffic Police database, their anticipated growth in dense urban areas such as the Kathmandu Valley warrants their inclusion in future RTA surveillance.
Urban-rural disparities requiring differentiated strategies
Urban areas accounted for 59.0% of RTAs nationally, but this aggregate conceals marked provincial heterogeneity. The Kathmandu Valley’s extreme urban concentration (97.7%) reflects its high vehicle and population density. By contrast, Madhesh and Koshi provinces recorded substantially more accidents in rural than in urban settings, likely owing to poor road quality, inadequate lighting, limited traffic enforcement, and reduced access to emergency medical services. 10 A predominance of rural and non-urban traffic fatalities has likewise been reported elsewhere; an autopsy-based study of road-traffic-accident deaths in Türkiye found that most fatal crashes occurred outside urban areas. 22 These findings underscore that a uniform national road safety strategy will be insufficient; geographically differentiated approaches addressing the distinct challenges of urban and rural settings are needed.
Temporal trends and surveillance gaps
Annual totals increased from 20,640 in 2020/21 to a peak of 24,537 in 2021/22, before declining modestly to 23,597 in 2022/23. The absence of a consistent downward trend, despite ongoing government and civil society efforts, reflects the need for sustained, systematic, multisectoral interventions. Countries achieving substantial reductions in road fatalities including Sweden through Vision Zero 11 and Australia through comprehensive helmet and seatbelt legislation 23 have done so through long-term political commitment to evidence-based strategies.
These findings broadly corroborate earlier analyses by Karkee and Lee (2016) 17 and Mishra et al. (2010), 8 which reported similar patterns of motorcycle predominance and young adult driver involvement. However, the present study extends existing evidence by providing province-level disaggregation across all seven provinces for four recent fiscal years a scope not previously reported for Nepal.
Implications for policy and practice
Several actionable recommendations follow from these findings. First, the concentration of accidents among drivers aged 16-40 years supports targeted road safety education in schools, licensing processes, and workplaces, alongside stricter enforcement of existing age and licensing requirements. Second, the predominance of motorcycle involvement calls for strengthened helmet law enforcement, public awareness campaigns, and graduated licensing for new riders. Third, urban-rural disparities require differentiated strategies: urban areas need traffic management and speed enforcement; rural areas need road maintenance, improved vehicle safety standards, and strengthened emergency medical services. Fourth, linking police records with hospital data in a standardised national surveillance system would enable more rigorous risk factor analysis and monitoring of intervention effectiveness.
Limitations
Several limitations should be acknowledged. First, the study relies on official Nepal Traffic Police records, which may underestimate actual accident counts owing to unreported incidents or cases resolved without police involvement. Second, data quality issues including inaccuracies or inconsistencies in recorded information may affect reliability. Third, important contextual variables such as weather conditions, road surface type, driver alcohol status, and helmet or seatbelt use were not available in the records, precluding causal inference. Fourth, the 2023/24 data are partial, covering only five months, and cannot be directly compared with full-year totals. Lastly, the dataset used for this study was available in an aggregated form and did not retain the crash-level linkage required to classify individual accident events according to the number of drivers or vehicles involved. Consequently, the proportions of accidents involving one, two, three, or more drivers or vehicles could not be determined. These limitations highlight the need for a standardised, prospective national RTA surveillance system in Nepal.
Conclusions
This study provides a detailed epidemiological profile of RTAs across all seven provinces of Nepal and the Kathmandu Valley over four fiscal years. The Kathmandu Valley bears the greatest accident burden; young and middle-aged adults predominantly motorcycle and scooter users account for the large majority of involved drivers; and marked urban-rural disparities indicate that road safety strategies must be geographically differentiated to be effective. Strengthening Nepal’s RTA surveillance system and investing in evidence-based, context-specific interventions are essential steps toward reducing the burden of road traffic injuries in the country.
Acknowledgements
The authors are grateful to the Nepal Traffic Police for granting access to the accident records that formed the basis of this study and DySP Dr. Bibek Rajbhandari for his continuous help, unwavering support and guidance.
Appendix.
List of abbreviations
- AD
Anno Domini
- BS
Bikram Sambat
- CBS
Central Bureau of Statistics
- DALY
Disability-Adjusted Life Year
- ERB
Ethical Review Board
- LMIC
Low- and Middle-Income Country
- NHRC
Nepal Health Research Council
- RTA
Road Traffic Accident
- RTI
Road Traffic Injury
- SPSS
Statistical Package for the Social Sciences
- WHO
World Health Organization
Footnotes
Author contributions: MG: Conceptualisation, Methodology, Investigation, Data curation, Supervision, Writing original draft, Writing review and editing. OS: Software, Data curation, Formal analysis, Writing original draft, Writing review and editing. LP: Data curation, Investigation, Formal analysis, Writing original draft, Writing review and editing. BS: Data curation, Investigation, Formal analysis, Writing original draft. AP: Data curation, Investigation, Writing original draft, Writing review and editing. TAL: Investigation, Writing original draft, Writing review and editing. NP: Investigation, Writing original draft, Writing review and editing. BG: Methodology, Investigation, Project administration, Visualisation, Writing original draft, Writing review and editing. All authors have read and approved the final manuscript.
Funding: The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was funded by the Nepal Health Research Council (NHRC), Government of Nepal, Ramshah Path, Kathmandu, Nepal. The funders had no role in study design, data collection, analysis, interpretation, or the decision to submit for publication.
The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
ORCID iD
Minani Gurung https://orcid.org/0000-0002-0330-0848
Ethical considerations
Ethical approval was obtained from the Ethical Review Board (ERB) of the Nepal Health Research Council (NHRC) (reference number: 2907) in accordance with the Declaration of Helsinki (2013 revision). Written permission to access RTA records was obtained from the Nepal Traffic Police. As the study involved only anonymised secondary records with no direct contact with individuals, individual informed consent was not required. Confidentiality was maintained throughout the study.
Data Availability Statement
The data underlying this study consist of official road traffic accident records held by the Nepal Traffic Police, provided under a restricted access agreement for this study only. Raw data cannot be made publicly available. Aggregated data as presented in the tables and figures are available from the corresponding author upon reasonable request.*
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data underlying this study consist of official road traffic accident records held by the Nepal Traffic Police, provided under a restricted access agreement for this study only. Raw data cannot be made publicly available. Aggregated data as presented in the tables and figures are available from the corresponding author upon reasonable request.*