Assessing inequality, irregularity, and severity regarding road traffic safety during COVID-19

Impact of COVID-19 pandemic on road traffic injuries in Iran: An interrupted time-series analysis

INTRODUCTION

Globally, the COVID-19 pandemic has affected the number of road accidents and deaths caused by them. The present study aimed to identify the effect of this epidemic on traffic accidents and their casualties in Iran.

METHODS

In this study, Interrupted Time Series Analysis (ITSA) was used in a semi-experimental design to measure the impact of the restrictive policies of COVID-19 on road accidents. Data were collected retrospectively from the Iran Red Crescent Society data set for 31 provinces from March 2017 to February 2022. The information related to the number of road accidents, injuries, deaths, and deaths in the hospital was collected. The Newey-West method is used for estimation. Statistical analyses were carried out using R software version 3.6.1.

RESULTS

Since February 2020 in Iran, the reduction in the number of road accidents and the number of injuries and deaths in these accidents was significant at 5% but the reduction of deaths in the scene and hospital was significant at 10%. In general, for all variables, the reduction trend was established only in the first months, and then it had an upward trend.

CONCLUSION

In the early months of the COVID-19 epidemic in Iran, the number of road accidents and their casualties decreased. Policies restricting traffic, quarantine, and fines for violators can be reasons for changing people's behavior and travel patterns and also lead to a reduction in traffic accidents and fatalities. Such studies can explain the importance of the policies in changing behavioural patterns and can be used as a guide in future policies.

What was the impact of COVID-19 restrictions on unintentional injuries, in Canada and globally? A scoping review investigating how lockdown measures impacted the global burden of unintentional injury

Background

Injuries are among the leading causes for hospitalizations and emergency department (ED) visits. COVID-19 restrictions ensured safety to Canadians, but also negatively impacted health outcomes, including increasing rates of certain injuries. These differences in trends have been reported internationally however the evidence is scattered and needs to be better understood to identify opportunities for public education and to prepare for future outbreaks.

Objective

A scoping review was conducted to synthesize evidence regarding the impact of COVID-19 restrictions on unintentional injuries in Canada, compared to other countries.

Methods

Studies investigating unintentional injuries among all ages during COVID-19 from any country, published in English between December 2019 and July 2021, were included. Intentional injuries and/or previous pandemics were excluded. Four databases were searched (MEDLINE, Embase, Web of Science, SPORTDiscus), and a gray literature search was also conducted.

Results

The search yielded 3,041 results, and 189 articles were selected for extraction. A total of 41 reports were included from the gray literature search. Final studies included research from: Europe (n = 85); North America (n = 44); Asia (n = 32); Oceania (n = 12); Africa (n = 8); South America (n = 4); and multi-country (n = 4). Most studies reported higher occurrence of injuries/trauma among males, and the average age across studies was 46 years. The following mechanisms of injury were reported on most frequently: motor vehicle collisions (MVCs; n = 134), falls (n = 104), sports/recreation (n = 65), non-motorized vehicle (n = 31), and occupational (n = 24). Injuries occurring at home (e.g., gardening, home improvement projects) increased, and injuries occurring at schools, workplaces, and public spaces decreased. Overall, decreases were observed in occupational injuries and those resulting from sport/recreation, pedestrian-related, and crush/trap incidents. Decreases were also seen in MVCs and burns, however the severity of injury from these causes increased during the pandemic period. Increases were observed in poisonings, non-motorized vehicle collisions, lacerations, drownings, trampoline injuries; and, foreign body ingestions.

Implications

Findings from this review can inform interventions and policies to identify gaps in public education, promote safety within the home, and decrease the negative impact of future stay-at-home measures on unintentional injury among Canadians and populations worldwide.

Evolution of work conditions for employees driving for work in France based on data from the 2003, 2010 and 2017 SUMER surveys (Surveillance Médicale des expositions aux risques Professionnels)

INTRODUCTION

The occupational road-accident risk on public roads and the work conditions for professional driving is still an important issue in occupational health despite lower road-accident rates. This study presents the evolution over time of the work-related constraints for these employees based on the Sumer surveys carried out in 2003, 2010 and 2017.

METHOD

Data from the 2010 and 2017 surveys were restricted to match the scope of the 2003 survey in order to enable prevalence data to be compared in equivalent populations. The main variable of interest was "driving (car, truck, bus, and other vehicles) on public thoroughfares" for work (during the last week of work: yes/no). Work time characteristics, work rhythm, autonomy and scope for initiative, collective work group, standards and evaluations variables were completed by the occupational health physicians. A self-administered questionnaire was also provided to employees and contained the Job Content Questionnaire, which assesses decision latitude, social support and psychological demands, the reward scale of Siegrist questionnaire, the hostile behaviour with inspired questions for Leymann, sick leave and work accidents during the past 12 months and job satisfaction. Finally, prevention in the workplace was also completed by the occupational health physicians.

RESULTS

About 25% of employees in France were exposed to work-related driving in 2017, which was stable in comparison with 2003 and 2010. However, the population was older and there were more females, more often from the clerical staff/middle manager category and working in companies with fewer than 10 employees. Employees exposed to work-related driving were also more frequently exposed to sustained work schedules and physical constraints, but less exposed to psychosocial risks.

CONCLUSIONS

The percentage of employees exposed to occupational road accident risk, i.e., exposure to work-related driving, remained stable at about 25% in 2017 compared with previous surveys. These employees were also more frequently exposed to sustained work schedules and physical constraints, but less exposed to psychosocial risks.

PRACTICAL APPLICATIONS

Prevention campaigns on work-related road accident risk should be provided to all employees in all companies since all jobs can be concerned.

Characteristics of injuries related to traffic crashes in Israel before and during the COVID-19 pandemic

OBJECTIVES

This study explored differences in patient characteristics, injury characteristics, treatment modalities, and treatment outcomes among patients who presented to the Emergency Department (ED) following traffic crashes during the COVID-19 period (from March 15, 2020 to March 15, 2022) in comparison to the previous corresponding period between 2017 and 2019.

METHODS

The study is a retrospective chart review study. The study included a random sample of 610 patients who presented to the ED of a major hospital located in northern-central Israel following traffic crashes: 305 patients who presented during the COVID-19 period (from March 15, 2020 to March 15, 2022) and 305 patients who presented during the previous corresponding period (from March 15, 2017 to March 15, 2019). Socio-demographic data, data regarding the traffic crashes, and medical data of the patients were collected from their medical records, and the data were compared.

RESULTS

In the context of the COVID-19 period, a notable surge in the percentage of cyclist victims was evident, marking an increase from 7.5% to 19% compared to the corresponding period. Conversely, the incidence of pedestrian victims during the COVID-19 period dropped to 19.7%, in contrast to 30.8% in the corresponding period. Notably, patients involved in pedestrian crashes amid the COVID-19 period exhibited a shorter hospital stay (M = 2.8 days, SD = 3.3) compared to the corresponding period (M = 4.3 days, SD = 7.1) [t = 1.8 (df = 141), p < 0.05]. However, a higher fatality rate was observed among these patients during the COVID-19 period compared to the corresponding period (6.7% vs. 0%) [χ2 = 6.4 (df = 1), p < 0.05].

CONCLUSIONS

The study reveals significant changes in traffic crashes characteristics during the pandemic period, including a notable increase in cyclist victims and a decrease in pedestrian incidents. These shifts may be attributed to factors such as changes in transportation patterns, increased use of bicycles for essential travel. Despite these changes, the proportion of severe crashes remained relatively consistent. These findings underscore the importance of understanding the underlying causes behind these shifts and highlight the ongoing need for public education and awareness initiatives to promote traffic safety, particularly for vulnerable road users, during pandemic periods.

Changes in traffic crash patterns: Before and after the outbreak of COVID-19 in Florida

In the twentieth year of the twenty-first century, humanity is facing an unprecedented global crisis owing to the COVID-19 pandemic. It has brought about drastic changes in the way we live and work, as well as the way we move from one place to another, namely transportation. Previous studies have preliminarily found that mobility, travel behavior, and road traffic safety status experienced great changes after the outbreak of the COVID-19. The objective of this study is to explore how crash patterns have changed, as well as the contributing factors of such changes and the heterogeneity between counties in Florida. Thus, data of COVID-19 cases, crash, socioeconomic factors, and traffic volume of 2019 and 2020 are collected. Preliminary analyses show a considerable reduction from March to June. Substantial changes are shown in the proportions of crashes by time of occurrence and injury severity. Two types of statistical models are developed to identify factors of (1) changes in the percentages of crashes by type and (2) the numbers of crashes by type. The developed models reveal various demographic, socioeconomic, and travel factors. After controlling other factors, the total numbers of crashes are 14% lower after the outbreak. The most significant reductions are observed in peak-hour (22%), while no significant change is found in fatal crashes. The results show that the number of crashes has significantly decreased even after controlling the traffic volume, but some crash types (e.g., fatal) did not show a significant reduction. The findings are expected to provide some insights into better transportation planning and management to ensure traffic safety in a possible future epidemic.

Mortality by Education Before and During the COVID-19 Pandemic, U.S., 2017-2020

INTRODUCTION

Mortality disparities by SES, including education, have steadily increased in the U.S. over the past decades. This study examined whether these disparities overall and for 7 major causes of death were exacerbated in 2020, coincident with the emergence of the COVID-19 pandemic.

METHODS

Using data on 7,123,254 U.S. deaths from 2017 to 2020, age-standardized death rates and mortality rate differences per 100,000 population and rate ratios comparing least with most educated were calculated by sex and race/ethnicity.

RESULTS

All-cause death rates were approximately 2 times higher among adults with least than among those with most education. Disparities in all-cause mortality by educational attainment slightly increased from 2017 (rate ratio=1.97; 95% CI=1.95, 1.98; rate difference=739.9) to 2019 (rate ratio=2.04; 95% CI=2.03, 2.06; rate difference=761.3) and then greatly increased in 2020 overall (rate ratio=2.32; 95% CI=2.30, 2.33; rate difference=1,042.9) and when excluding COVID-19 deaths (rate ratio=2.27; 95% CI=2.25, 2.28; rate difference=912.3). Similar patterns occurred across race/ethnicity and sex, although Hispanic individuals had the greatest relative increase in disparities for all-cause mortality from 2019 (rate ratio=1.47; 95% CI=1.43, 1.51; rate difference=282.4) to 2020 overall (rate ratio=2.00; 95% CI=1.94, 2.06; rate difference=652.3) and when excluding COVID-19 deaths (rate ratio=1.84; 95% CI=1.79, 1.90; rate difference=458.7). Disparities in cause-specific mortality by education were generally stable from 2017 to 2019, followed by a considerable increase from 2019 to 2020 for heart disease, cancer, cerebrovascular disease, and unintentional injury. Among these causes of death, the relative increase in rate ratio from 2019 to 2020 was greatest for unintentional injury (24.8%; from 3.41 [95% CI=3.23, 3.60] to 4.26 [95% CI=3.99, 4.53]).

CONCLUSIONS

Mortality disparities by education widened in the U.S. in 2020, during the COVID-19 pandemic. Further research is warranted to understand the reasons for these widened disparities.

Modeling the impact of the COVID-19 pandemic on speeding at rural roadway facilities in Maine using short-term speed and traffic count data

The COVID-19 pandemic caused a significant change in traffic operations and safety. For instance, various U.S. states reported an increase in the rate of fatal and severe injury crashes over this duration. In April and May of 2020, comprehensive stay-at-home orders were issued across the country, including in Maine. These orders resulted in drastic reductions in traffic volume. Additionally, there is anecdotal evidence that speed enforcement had been reduced during pandemic. Drivers responded to these changes by increasing their speed. More importantly, data show that speeding continues to occur, even one year after the onset of the pandemic. This study develops statistical models to quantify the impact of the pandemic on speeding in Maine. We developed models for three rural facility types (i.e., major collectors, minor arterials, and principal arterials) using a mixed effect Binomial regression model and short duration speed and traffic count data collected at continuous count stations in Maine. Our results show that the odds of speeding by more than 15 mph increased by 34% for rural major collectors, 32% for rural minor arterials, and 51% for rural principal arterials (non-Interstates) during the stay-at-home order in April and May of 2020 compared to the same months in 2019. In addition, the odds of speeding by more than 15 mph, in April and May of 2021, one year after the order, were still 27% higher on rural major collectors and 17% higher on rural principal arterials compared to the same months in 2019.

An overview of the impact of COVID-19 on road traffic safety and travel behavior

The COVID-19 epidemic caused global roads and highway networks to be disrupted to historic proportions. While the world is focused on combating COVID-19 pandemic, people are still dying and being injured as a result of traffic collisions on the highways owing to movement restrictions. Although the impact of shutdown mechanisms on traffic safety is still being studied, initial studies reveal a decrease in traffic flow and a rise in risky driving behaviors. On the other hand, it is important to investigate how the epidemic has influenced travel behavioral characteristics in order to design mobility regulations for the post-COVID-19 future. Considering numerous investigations, the present study attempts to provide an overview of the influence of the COVID-19 pandemic on road traffic crashes, deaths, and injuries, as well as road travel behavior. The magnitude of COVID-19 was found to result in fewer crashes and injuries, as well as a reduction in road safety performance, but substantially greater serious accidents. According to a study of many papers, Travel objective, method of transportation, mileage traveled, and numbers of trips for principal travel were considerably different before and during the epidemic. The result of this study have significant legislative ramifications and also can help to guide how further lockdowns are managed in terms of traffic safety and travel behavior.

ANN-Based traffic volume prediction models in response to COVID-19 imposed measures

Many countries around the globe have imposed several response measures to suppress the rapid spread of the COVID-19 pandemic since the beginning of 2020. These measures have impacted routine daily activities, along with their impact on economy, education, social and recreational activities, and domestic and international travels. Intuitively, the different imposed policies and measures have indirect impacts on urban traffic mobility. As a result of those imposed measures and policies, urban traffic flows have changed. However, those impacts are neither measured nor quantified. Therefore, estimating the impact of these combined yet different policies and measures on urban traffic flows is a challenging task. This paper demonstrates the development of an artificial neural networks (ANN) model which correlates the impact of the imposed response measure and other factors on urban traffic flows. The results show that the adopted ANN model is capable of mapping the complex relationship between traffic flows and the response measures with a high level of accuracy and good performance. The predicted values are closed to the observed ones. They are clustered around the regression line, with a coefficient of determination ( R 2 ) of 0.9761. Furthermore, the developed model can be generalized to determine the anticipated demand levels resulted from imposing any of the response measures in the post-pandemic era. This model can be used to manage traffic during mega-events. It can be also utilized for disaster or emergency situations, where traffic flow estimates are highly required for operational and planning purposes.

Risk-Compensation Trends in Road Safety during COVID-19

The COVID-19 pandemic has had a global impact, disrupting the normal trends of our everyday life. More specifically, the effects of COVID-19 on road safety are still largely unexplored. Hence, this study aims to investigate the change in road safety trends due to COVID-19 using real-time traffic parameters. Results from the extensive analyses of the 2017 to 2020 data of Interstate-4 show that traffic volume decreased by 13.6% in 2020 compared to the average of 2017–2019’s volume, whereas there is a decreasing number of crashes at the higher volume. Average speed increased by 11.3% during the COVID-19 period; however, the increase in average speed during the COVID-19 period has an insignificant relationship with crash severities. Fatal crashes increased, while total crashes decreased, during the COVID-19 period; severe crashes decreased with the total crashes. Alcohol-related crashes decreased by 22% from 2019 to 2020. Thus, the road-safety trend due to the impact of COVID-19 has evidently changed and presents a unique trend. The findings of the study suggest a larger need for a more in-depth study to analyze the impact of COVID-19 on road safety, to minimize fatalities on roads through appropriate policy measures.

Road traffic accidents in Italy during COVID-19

OBJECTIVE

To assess changes in the number and severity of road traffic accidents in Italy in 2020, in particular after the beginning of COVID-19 and during the lockdown, as compared with 2019, with monthly details and geographical variations within the country.

METHODS

Official monthly data on road traffic accidents recorded by the Police in Italy in 2020 were compared with those in 2019. The comparison regarded number of accidents, percent change, non-fatal injuries, deaths, injury index (injuries/accidents ×100) and fatality index (deaths/accidents ×100). Monthly data were graphically presented separately for each of the 21 Italian Regions and autonomous Provinces.

RESULTS

A steep generalized decrease in the number of road traffic accidents was observed in March and April 2020 (Italian lockdown) as compared with the corresponding months of 2019 (more than 70% change), with a smaller change in the number of deaths, more variable among Regions. Smaller decreases were observed in the following part of 2020.

CONCLUSIONS

In Italy, lockdown and limitation of mobility due to COVID-19 determined a strong decrease in the number of road traffic accidents and their health consequences. Inter-regional variability in the decrease of deaths might be associated with the severity of the SARS-CoV-2 local outbreak, although specific causes need to be investigated. These data are useful to inform traffic and public health policy makers.

Impact of COVID-19 travel-restriction policies on road traffic accident patterns with emphasis on cyclists: A case study of New York City

Since the COVID-19 outbreak, travel-restriction policies widely adopted by cities across the world played a profound role in reshaping urban travel patterns. At the same time, there has been an increase in both cycling trips and traffic accidents involving cyclists. This paper aims to provide new insights and policy guidance regarding the effect of COVID-19 related travel-restriction policies on the road traffic accident patterns, with an emphasis on cyclists' safety. Specifically, by analysing the accidents data in the New York City and estimating three fixed effects logit models on the occurrence of different types of accidents in a given zip code area and time interval, we derived the following findings. First, while the overall number of road traffic accidents plummeted in the NYC after the stay-at-home policy was implemented, the average severity increased. The average number of cyclists killed or injured per accidents more than tripled relative to levels in similar times in previous years. Second, the declaration of the New York State stay-at-home order was significantly associated with a higher risk of accidents resulting in casualties. The number of Citi Bike trips in the area at the time overwhelmingly predicted severe risk for cyclists. Last, we applied the models to detect hot zones for cyclists' severe accidents. We found that these hot zones tend to be spatially and temporally concentrated, making it possible to devise targeted safety measures. This paper contributes to the understanding of the impact of COVID-19 travel-restriction policies on accidents involving cyclists, reveals higher risks for cyclists as an unintended consequence of travel-restriction policies, and provides an analytical tool for road safety impact evaluation should future travel restrictions be considered.

Impact of night travel ban on road traffic crashes and fatalities in Zambia: an interrupted time series analysis

Background

The burden of road traffic crashes (RTCs) and road traffic fatalities (RTFs) has been increasing in low-income and middle-income countries (LMICs). Most RTCs and RTFs happen at night. Although few countries, including Zambia, have implemented night travel bans, there is no evidence on the extent to which such policies may reduce crashes and fatalities.

Methods

We exploit the quasi-experimental set up afforded by the banning of night travel of public service vehicles in Zambia in 2016 and interrupted time series analysis to assess whether the ban had an impact on both levels and trends in RTCs and RTFs. We use annual administrative data for the period 2006—2020, with 10 pre-intervention and 4 post-intervention data points. In an alternative specification, we restrict the analysis to the period 2012—2020 so that the number of data points are the same pre-interventions and post-interventions. We also carry out robustness checks to rule out other possible explanation of the results including COVID-19.

Results

The night travel ban was associated with a reduction in the level of RTCs by 4131.3 (annual average RTCs before the policy=17 668) and a reduction in the annual trend in RTCs by 2485.5. These effects were significant at below 1%, and they amount to an overall reduction in RTCs by 24%. The policy was also associated with a 57.5% reduction in RTFs. In absolute terms, the trend in RTFs reduced by 477.5 (Annual average RTFs before the policy=1124.7), which is significant at below 1% level. Our results were broadly unchanged in alternative specifications.

Conclusion

We conclude that a night travel ban may be an effective way of reducing the burden of RTCs and RTFs in Zambia and other LMICs. However, complementary policies are needed to achieve more gains.

Impact of COVID-19 pandemic on road safety in Tamil Nadu, India

This study uses structured literature mapping to review worldwide trends in traffic safety following the phenomenon of the COVID-19 pandemic. Motivated by dissimilar findings globally and a lack of evidence from emerging nations which have been significantly more affected by road traffic crashes, the study examines the impact of the pandemic-induced lockdown on road traffic deaths and injuries in Tamil Nadu, India. Using a holistic approach, methods such as ARIMA, Holt-Winters, Bayesian Structural Time Series, and Generalized Additive Model are employed for counterfactual prediction, to draw a causal inference of lockdown on traffic safety. In line with global studies, a substantial reduction in traffic crashes, injuries, and fatalities during lockdowns has been found. However, the comparison of relative differences shows that the number of grievous injuries reduced more than minor injuries, crashes, or fatalities. Furthermore, these relative differences were sustained even when metrics returned to normalcy in the post-lockdown phases. Further spatial stratification at two levels (cities and districts) shows that the macroscopic state-level trends are also broadly seen in the sub-units. This validates the consistency of trends across rural-urban differences and shows that, despite variations in the degree of enforcement of the lockdown within Chennai city, contrary to expectation, increased police presence did not have a differential impact on road crashes.

A Descriptive Analysis on the Impact of COVID-19 Lockdowns on Road Traffic Incidents in Sydney, Australia

COVID-19 has had tremendous effects worldwide, resulting in large-scale death and upheaval. An abundance of studies have shown that traffic patterns have changed worldwide as working from home has become dominant, with many facilities, restaurants and retail services being closed due to the lockdown orders. With regards to road safety, there have been several studies on the reduction in fatalities and crash frequencies and increase in crash severity during the lockdown period. However, no scientific evidence has been reported on the impact of COVID-19 lockdowns on traffic incident duration, a key metric for crash management. It is also unclear from the existing literature whether the impacts on traffic incidents are consistent across multiple lockdowns. This paper analyses the impact of two different COVID-19 lockdowns in Sydney, Australia, on traffic incident duration and frequency. During the first (31 March-28 April 2020) and second (26 June-31 August 2021) lockdowns, the number of incidents fell by 50% and 60%, respectively, in comparison to the same periods in 2018 and 2019. The proportion of incidents involving towing increased significantly during both lockdowns. The mean duration of crashes increased by 16% during the first lockdown, but the change was less significant during the subsequent lockdown. Crashes involving diversions, emergency services and towing saw an increase in the mean duration by 67%, 16%, and 47%, respectively, during the first lockdown. However, this was not reflected in the 2021 data, with only major crashes seeing a significant increase, i.e., by 58%. There was also a noticeable shift in the location of incidents, with more incidents recorded in suburban areas, away from the central business area. Our findings suggest drastic changes in incident characteristics, and these changes should be considered by policymakers in promoting a safer and more sustainable transportation network in the future.