Road traffic injuries disproportionately affect low- and middle-income countries (LMICs). Although traffic safety culture, social norms, and normalisation of deviance have received increasing attention, the processes through which cultural conditions may generate and reproduce road behaviour remain insufficiently integrated into dominant road safety frameworks. This paper proposes the Cultural Road Safety Model (CRSM), a preliminary conceptual framework for examining these processes. CRSM conceptualises the driver as a cultural agent and considers the cultural conditions underlying persistent unsafe practices. The framework draws on behavioural, criminological, organisational change, and relational perspectives, with ubuntu providing the philosophical foundation operationalised for this paper's Southern African context. It proposes a five-phase pathway comprising cultural diagnosis, policy alignment, community engagement, pilot implementation, and institutionalisation. Three propositions concerning diagnostic alignment, community anchoring, and cross-domain deviance are advanced for empirical testing. The proposed cultural dimensions offer further opportunities for empirical measurement. As a conceptual contribution, CRSM offers a theoretical foundation for future empirical validation and refinement.
This study examines the pattern in the establishment of road safety lead agencies (RSLAs) in 31 low- and middle-income countries (LMICs). It is based on a survey conducted with respondents in these countries. Two patterns emerge from the results. The first pattern is that RSLAs have continuously been established in LMICs over the years with the earliest RSLAs being established nearly four decades ago in a few of the LMICs surveyed. The second pattern is that most countries have established RSLAs through an act of parliament by adopting specific legislation. The study concludes that contrary to the concern raised in the World report on road traffic injury prevention (Peden et al., 2004) about a lack of an agency to coordinate road safety policy among state and nonstate agencies in some countries, the road safety organisational landscape in some of these 31 LMICs included a RSLA by 2000 that should have played this coordination role.
This study profiles suspected female homicide victims in Johannesburg, South Africa, during the COVID-19 period marked by socio-environmental changes from lockdown restrictions. Guided by the Socio-Ecological Model, a retrospective case series of 369 victims was reviewed using medico-legal mortuary records from Johannesburg and Diepkloof Forensic Pathology Service facilities. Descriptive analyses were conducted, supplemented by a chi-square test to assess whether distributions of causes of death among women differed between COVID-19 and non-COVID-19 periods. No statistically significant association was found, χ2 (6, N = 339) = 6.68, p = 0.35. Key findings highlight that Black, unemployed, unmarried women aged 21-40 were at greatest risk. Cause of death was established in 97.0% (358/369) of cases, with firearm injuries predominating (43.9%), followed by sharp‑force (24.5%) and blunt‑force trauma (13.1%). Approximately 90% of victims were suspected to have been killed by males, with half of deaths attributed to intimate partner violence. Homicide frequency decreased during strict lockdowns but rose as restrictions eased, suggesting that movement and alcohol controls may reduce risk. Despite temporary disturbance caused by COVID‑19 restrictions, the underlying risk profile of female homicide victims remained unchanged. These findings inform multi-level prevention and intervention strategies in South Africa.
This retrospective descriptive study examined firearm-related fatalities during (April-December 2020; n = 241) and after (April-December 2023; n = 299) COVID-19 lockdowns using 540 cases from the Diepkloof Forensic Pathology Service, Soweto, South Africa. Data was obtained from autopsy reports, forensic records, police statements, and death scene documentation. Firearm violence affected young adult Black males (22-43 years), with only minor demographic shifts post-pandemic. The overall burden and core patterns of violence remained stable, with criminal activity - primarily robbery and interpersonal violence - persisting as the leading contexts, and homicide the dominant manner of death. Post-COVID-19 findings demonstrated contextual shifts, including increased incidents in public and social environments, reflecting greater mobility and resumption of social activity. A significant rise in mean blood alcohol concentration (0.09 g/100 mL vs 0.14 g/100 mL; p < 0.0001) suggests increased alcohol involvement following easing of restrictions. Unfortunately, persistent information gaps, noted particularly in circumstantial history, incident location, firearm type, highlighting the need for improved data provision and capture systems. While the epidemiology of firearm-related fatalities remained unchanged, the post-COVID-19 period was characterised by increased alcohol involvement, shifts toward public-space violence, and fewer gunshot wounds per victim, suggesting changes in situational and behavioural dynamics rather than underlying drivers of violence.
Suicide is a growing public health concern in South Africa, with rural provinces such as Limpopo facing heightened vulnerability due to limited mental health services and socio-economic inequalities. Evidence on the impact of COVID-19 on suicide in rural contexts remains limited. This study examined suicide trends in Limpopo Province and changes associated with the COVID-19 period. A retrospective interrupted time series analysis was conducted using forensic mortality data from 1 January 2019 to 31 December 2021, allowing assessment of pre-existing trends and changes following COVID-19 lockdowns. Among 5770 unnatural deaths, 957 were suicides. The proportion of suicides increased from 29.5% in 2019 to 36.9% in 2021. Suicides predominantly occurred among males and young adults, with hanging accounting for over 90% of deaths throughout. Interrupted time series analysis revealed a significant downward trend in suicide cases during the strict national lockdown (Alert Level 5), with a 31% reduction in incidence (IRR = 0.69, 95% CI: 0.49-0.98). Less restrictive lockdown levels showed no significant effects. Suicide mortality increased prior to COVID-19, with a subsequent decline during the strictest lockdown period. Stable demographic patterns and methods highlight persistent vulnerabilities and the need for sustained suicide-prevention strategies beyond pandemic.
A small fraction of drivers accounts for a disproportionately large share of the world's most serious road crashes, yet remarkably little is known about how quickly these high-risk individuals progress from one crash to the next. This temporal blind spot limits the ability of policymakers and enforcement agencies to intervene at the moments when drivers are most vulnerable. To address this gap, this study investigates the determinants of the time interval between a prior non-fatal crash and a subsequent fatal crash among crash-prone drivers in the United States. Using 5 years of Fatality Analysis Reporting System (FARS) data (2015- 2019), a sample of 36,144 fatal crash-involved drivers with recorded prior non-fatal crashes was analysed through a random-parameter hazard-based duration model. The findings demonstrate that fatal crash recurrence is not random but reflects distinct behavioural and demographic risk signatures. Male drivers, young drivers (16-24 years), Hispanic drivers and individuals with extensive violation histories exhibited significantly shorter intervals between non-fatal and fatal incidents. Prior speeding violations, license suspensions, other non-driving under the influence (DUI) infractions and involvement in multiple previous crashes sharply accelerated the progression to a fatal crash. Characteristics of the fatal crash itself, including drug impairment, speeding, invalid licensing and single-vehicle involvement, were also associated with compressed temporal intervals. The incorporation of random parameters reveals further heterogeneity, particularly in the influence of prior speeding violations. By and large, the temporal structure of crash recurrence observed in the study aligns with the long-standing theory of crash proneness.
Homicide is a major form of violent injury in Latin America, yet post-pandemic increases may reflect not only changes in overall levels of lethal violence but also changes in how victimization is socially distributed. This repeated cross-sectional study examined homicide deaths in Peru from 2017 to 2025 across pre-pandemic, pandemic, and post-pandemic periods. Victims were characterized by sex, age, education, marital status, and ethnicity, and concentration was assessed within each dimension and across intersecting victim profiles. The post-pandemic period showed a measurable narrowing in the social composition of homicide victims. Deaths became increasingly concentrated among men, adults aged 30-59 years, and single individuals, with more modest concentration among those with secondary education and those classified as Mestizo. These findings suggest that post-pandemic homicide dynamics may involve changes in concentration as well as magnitude, with implications for surveillance, prevention targeting, and understanding violent injury in low- and middle-income settings.
Falls are a major global public health issue, but detailed evaluations of their burden in the Middle East and North Africa (MENA) region are limited. This study assesses the incidence, prevalence, mortality and disability-adjusted life years (DALYs) due to falls in MENA region from 1990 to 2021. We utilized data from the Global Burden of Disease (GBD) Study 2021, analyzing estimates for 21 MENA countries. We examined all-age and age-standardized rates per 100,000 population by sex, age group, country and year. In 2021, MENA reported 14.29 million (95% UI 12.71, 16.19) incident fall cases, with an age-standardized incidence rate of 2281.67 (2042.45, 2564.66) per 100,000. Prevalence was 30.32 million (25.69, 35.03) cases, at an age-standardized rate of 5234.03 (4476.03, 6011.50) per 100,000. Falls led to 23404 (20142, 27599) deaths, with an age-standardized mortality rate of 5.66 (4.85, 6.73) per 100,000, and 2.17 million (1.78, 2.69) DALYs. Burden was higher among males and adults over 80 years. Saudi Arabia had the highest incidence and prevalence, and Afghanistan had highest mortality. Falls represent a growing public health threat in MENA, intensified by ageing populations. Improved surveillance, targeted prevention for at-risk groups and embedding strategies in primary care and national health policies - are critical.
Pedestrians face disproportionate injury risk in traffic. Using nationwide SEWIK police records (2015-2024), I model five-level pedestrian injury severity with proportional-odds logistic regression, Random Forest and XGBoost under time-blocked, incident-aware cross-validation, and I interpret Random Forest predictions with SHAP while simulating repaired traffic signals. Random Forest attains the strongest ordinal agreement (quadratic weighted kappa 0.241 ± 0.042 across eight outer folds; bootstrap 95% CI 0.212-0.264), clearly outperforming naive baselines (majority-class and ordinal-median QWK ≈ 0), whereas XGBoost peaks on accuracy (0.556) and F1-weighted (0.496). SHAP highlights age, lighting, precise location in the road space and posted speed limit as dominant severity drivers; age ranked first and daylight second in seven of eight outer folds. Counterfactual signal restoration on n = 1,212 records with a non-functioning signal shifts predicted mass towards milder outcomes, most visibly 74 transitions from seriously to slightly injured (bootstrap 95% CI 59-92) and 31 from died within 30 days to seriously injured (CI 21-42). Predictive performance remains modest (macro ECE 0.115); estimates are prognostic and Poland-specific, and counterfactuals are associative rather than causal, but the workflow illustrates how registry analytics can inform maintenance prioritization for life-saving infrastructure.
This paper explores historical and contemporary intersections between mass-mortality epidemics and violent crime in South Africa, focusing on four major epidemics - Spanish Flu, tuberculosis, HIV, and Covid-19. The study integrates epidemiological data and contextual historical information such as crime statistics, archival records, and secondary scholarship to explore whether epidemic-driven mortality crises are associated with subsequent changes in violence and injury profiles. With the possible exception of gendered violence, the study finds little evidence that earlier epidemics directly contributed to rapid or sustained increases in violent crime, despite causing substantial adult mortality and long-term social and economic disruption. A comparison between epidemic and socio-economic profiles strongly suggests that the significant increases in violent crime recorded after the Covid-19 pandemic are highly localised, and may be more strongly related to lockdown responses, including alcohol restrictions, rather than the effects of disease itself.
Road traffic injuries (RTIs) are a significant cause of death in South Africa; however, the effects of the COVID-19 pandemic on provincial RTI patterns remain insufficiently explored. This systematic review compared RTI patterns in KwaZulu-Natal and the Western Cape across pre-COVID-19 (2019), during-COVID-19 (2020-2021), and post-COVID-19 (2022-2023) periods. A systematic search of five electronic databases and grey literature sources was conducted, with 90 sources included following an adapted PRISMA 2020 framework. Findings were analysed using a descriptive comparative approach and synthesised through narrative synthesis guided by the framework proposed by Popay et al. (2006). In KwaZulu-Natal, fatalities declined from 2,331 in 2019 to 2,031 in 2020 before returning to slightly below baseline levels (2,229) in 2023. In contrast, fatalities in the Western Cape increased from 1,013 in 2019 to 1,158 in 2020, declined slightly in 2021, and increased further to 1,371 in 2023. Males aged 25-39 years and pedestrians remained the most affected groups across all study periods. The findings suggest that both pandemic-related behavioural changes and persistent structural and system-level factors may have contributed to the observed provincial differences in RTI patterns.
Pedestrians usually sustain more severe injuries in traffic crashes due to the lack of protection. Although previous studies have analyzed crash-influencing factors, the causal relationships between injury severity and factors remain limited. Thus, the study aims to investigate the causal effects of factors, particularly the hazardous driving behaviors, on pedestrian injury severity. It employs causal machine learning and the Shapley Additive exPlanations to analyze the marginal contribution of the feature variables on crash injury severity. Furthermore, the causal tree model is used to reveal the heterogeneous causal effects. The results indicate that 1) the pedestrian injury severity is influenced by various factors, such as pedestrian age, speed limit, and vehicle type, 2) hazardous driving behaviors can deteriorate pedestrian injury severity, with 'failing to yield right of way' showing the highest mean conditional average treatment effect (CATE) (0.768), followed by 'careless driving' (0.626) and 'violating traffic signs or signals' (0.590), and 3) hazardous driving behaviors, road speed limits, and pedestrian age jointly contribute to the pedestrian injury severity. The study reveals heterogeneity in the causal relationship between hazardous driving behaviors and the injury severity of pedestrian-vehicle crashes, which serves to develop differential intervention strategies to mitigate pedestrian injury.
Rural road safety remains a critical yet underexplored challenge in India's transportation system, where connectivity improvements under the Pradhan Mantri Gram Sadak Yojana (PMGSY) have been accompanied by increasing accident risks. Despite large-scale infrastructure development, the absence of structured, data-driven safety evaluation frameworks limits effective prioritization of high-risk segments. This study integrates regression analysis with a Relative Importance Index (RII) based multi-criteria framework to assess and prioritize safety risks on PMGSY rural roads in Sinnar Taluka, Nashik District. Accident data from 110 reported cases, field surveys and Indian Roads Congress (IRC) standards were used to evaluate critical parameters including sight distance, shoulder width, sharp curves, roadside environment, pavement condition and residential access. Regression analysis identified sight distance, blind turns and residential access density as the most influential predictors of accidents, while RII-based ranking reflected expert perceptions of safety severity. To address recent methodological advancements, a baseline artificial neural network (ANN) model was additionally employed as a comparative benchmark to examine consistency in segment prioritization. The integrated regression-RII approach enables a comprehensive, data and perception-driven assessment of rural road safety. Findings support targeted interventions, such as geometric realignment, roadside protection and access control, providing a replicable framework for policymakers and planners to enhance safety performance and promote sustainable rural mobility.
The COVID-19 lockdown restrictions, while necessary to curb the spread of the virus, also led to the increase in gender-based violence (GBV) in many countries, including South Africa. Despite numerous studies on GBV, the voices of local community members, as key informants with situated knowledge, have largely been excluded. This study therefore explored community members' accounts of GBV during the COVID-19 lockdowns. Participants included men and women from an informal settlement in Johannesburg South. Three focus group discussions, each consisting of 12-13 participants, were undertaken to collect the data. The study used structural violence theory as well as Ubuntu feminism as a framing tool. Data were analysed using thematic analysis. The findings point to increased intra-familial violence, a deepening culture of silence around violence, escalating neglect within health and protection services, and the stifling of community activism. Participants also recounted feelings of helplessness in their efforts to mitigate GBV, alongside expressions of solidarity with survivors. Overall, the findings suggest that the COVID-19 lockdown restrictions unintentionally magnified existing drivers of GBV. We argue that future crisis responses -whether public health, social, or economic - must integrate violence prevention and protection mechanisms, ensuring that measures intended to safeguard populations do not simultaneously intensify gendered harm.
Driver behaviors and psychological traits are important and modifiable risk factors for traffic accidents. Previous studies have reported inconsistent results, often with small sample sizes. We conducted a systematic review and meta-analysis to quantitatively synthesize evidence on the association between driver behaviors, psychological traits, and traffic accident risk. PubMed and CNKI databases were searched. Eligible cross-sectional and case-control studies reporting odds ratios (ORs) or sufficient data to calculate them were included. Study quality was assessed using the 11-item Agency for Healthcare Research and Quality checklist. Pooled ORs were calculated using a random-effects model. I2 and τ2 statistics assessed heterogeneity, and leave-one-out sensitivity analyses were performed. Eighteen studies were included, covering nine behavioral factors (alcohol drinking, fatigue, lack of speed limit awareness, running a red light, sleep disorder, sleep duration less than 8 h, unawareness of entering the non-motorized lane, phone use, and not wearing a seatbelt/helmet) and five psychological traits (anger, anxiety, and three Eysenck personality dimensions). Pooled ORs ranged from 1.16 to 3.65. Study quality was generally moderate to high (scores 5-10), with no studies rated as high risk of bias. Heterogeneity was moderate to high for most factors but decreased after excluding certain studies, and effect directions remained consistent. Multiple driver behaviors and psychological traits significantly increase traffic accident risk, highlighting the importance of incorporating behavioral and psychological risk factor assessment into traffic safety policies and designing targeted prevention strategies.
Crash type is an important factor in understanding crash severity, as certain types lead to higher mortality rates. Predicting crash type for specific road sections can therefore support road safety assessments. This study examines the relationships between geometric road elements at crash sites and identifies key features in crash type classification. Crash data from a 10-year period in 10 central districts of İzmir, Türkiye, were analysed. Among these districts, the three with the highest number of crashes, namely Bornova, Karşıyaka and Konak, were used as geographically distinct test districts, while model training was performed using data from the remaining central districts within each temporal group. Feature importance ranking was conducted using the Extreme Gradient Boosting (XGBoost) method. As the main contribution, we propose Embedding-XGBoost (E-XGB), a novel two-stage dimensionality reduction approach that integrates entity embeddings with XGBoost to improve classification performance. E-XGB enables modelling crash data in a lower-dimensional feature space, allowing predictions with reduced computational effort and robustness against missing data. The superiority of E-XGB was demonstrated by comparing its performance with four machine learning algorithms: XGBoost, support vector machine, K-nearest neighbours and multilayer perceptron. Results show that E-XGB achieves classification performance values, in terms of accuracy, F1-score and precision up to 85.42%, 85.09% and 86.03%, respectively, when 10 features are used.
Purpose: Drowning ranks as the third leading cause of injury-related death in children globally. This systematic review and meta-analysis aims to provide a comprehensive assessment of mortality rates, and resuscitation success rates in pediatric populations. Methods: A comprehensive literature search was conducted across four databases PubMed, Cochrane, Web of Science and Scopus for all original studies published till November 2024 with reported outcomes of drowning in the pediatric population. Outcomes evaluated include mortality, rate of discharge, neurological outcomes at discharge, and success rate of resuscitation. Results: Twenty-four studies encompassing 2,436 pediatric drowning cases were analyzed. The pooled mortality rate was 24% (95% CI [0.17, 0.34]), underscoring the critical fatality risk. The pooled discharge rate was 63% (95% CI [0.47, 0.76]), indicating favorable recovery for most cases. However, one-third of patients exhibited significant neurological deficits. Resuscitation success was achieved in 39% (95% CI [0.32, 0.48]), with bystander resuscitation demonstrating nearly double the success rates compared to emergency medical personnel or lifeguards. Conclusion: Despite favorable discharge rates, pediatric drowning remains a major public health challenge with high mortality and neurological impairment rates. Urgent action is required to develop standardized management protocols and prevention strategies, particularly in resource-limited settings.
Drowning remains a major global public health challenge, yet how built environment characteristics shape population-level drowning risk remains poorly understood. This study linked satellite-derived built environment data to subnational drowning mortality estimates across 203 regions in 12 countries from 2006-2021. It found that built environment associations with drowning mortality are complex, non-linear, and shaped by development context. Urban extent was strongly protective, while built area near water showed protection overall but increased risk when combined with high population crowding. Almost all drowning mortality variance occurred between regions rather than within regions over time, indicating risk is predominantly determined by place-based characteristics. Income-stratified analyses revealed profound heterogeneity: crowding was protective in low- to middle-income settings, while near-water built area was protective mainly in middle-income settings. These findings highlight the importance of tailoring drowning prevention strategies to local built environment configurations and development contexts.
Road traffic significantly contributes to injury mortality in South Africa, with few descriptions of its impact on rural provinces like Limpopo. This study reports on the demographics and circumstances surrounding road traffic fatalities in Limpopo from 2019 to 2021, utilising mortuary-based data. A retrospective descriptive analysis was undertaken on data from five sentinel mortuaries in the five districts of Limpopo. Variables included age, sex, road user type, day and time of death, and incident location. Results were showcased through proportional analyses. Road traffic injuries accounted for 38.8% (n = 2,242) of non-natural mortality. Males constituted 77% (n = 1,733) of these fatalities, with the highest proportions among drivers (34.5%, n = 549) and individuals aged 15-39 years (60%, n = 1,034). A 19.7% decrease in mortality was observed in 2020, following the onset of the COVID-19 pandemic and subsequent restrictions, and a 24.9% increase in 2021 as restrictions lifted. Pedestrian mortality, however, increased with the onset of the pandemic. The trends of road traffic mortality in Limpopo highlight distinct patterns, underscoring the need for targeted, localised safety measures.
