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1.
Int J Inj Contr Saf Promot ; 29(2): 133-134, 2022 06.
Article in English | MEDLINE | ID: covidwho-1873797
2.
Accid Anal Prev ; 173: 106715, 2022 Aug.
Article in English | MEDLINE | ID: covidwho-1866757

ABSTRACT

With the advance of intelligent transportation system technologies, contributing factors to crashes can be obtained in real time. Analyzing these factors can be critical in improving traffic safety. Despite many crash models having been successfully developed for safety analytics, most models associate crash observations and contributing factors at the aggregate level, resulting in potential information loss. This study proposes an efficient Gaussian process modulated renewal process model for safety analytics that does not suffer from information loss due to data aggregations. The proposed model can infer crash intensities in the continuous-time dimension so that they can be better associated with contributing factors that change over time. Moreover, the model can infer non-homogeneous intensities by relaxing the independent and identically distributed (i.i.d.) exponential assumption of the crash intervals. To demonstrate the validity and advantages of this proposed model, an empirical study examining the impacts of the COVID-19 pandemic on traffic safety at six interstate highway sections is performed. The accuracy of our proposed renewal model is verified by comparing the areas under the curve (AUC) of the inferred crash intensity function with the actual crash counts. Residual box plot shows that our proposed models have lower biases and variances compared with Poisson and Negative binomial models. Counterfactual crash intensities are then predicted conditioned on exogenous variables at the crash time. Time-varying safety impacts such as bimodal, unimodal, and parabolic patterns are observed at the selected highways. The case study shows the proposed model enables safety analytics at a granular level and provides a more detailed insight into the time-varying safety risk in a changing environment.


Subject(s)
Automobile Driving , COVID-19 , Accidents, Traffic/prevention & control , Humans , Models, Statistical , Pandemics , Safety
3.
Inj Prev ; 28(3): 269-279, 2022 06.
Article in English | MEDLINE | ID: covidwho-1861642

ABSTRACT

BACKGROUND: Cohort studies play essential roles in assessing causality, appropriate interventions. The study, Post-crash Prospective Epidemiological Research Studies in IrAN Traffic Safety and Health Cohort, aims to investigate the common health consequences of road traffic injuries (RTIs) postcrash through multiple follow-ups. METHODS: This protocol study was designed to analyse human, vehicle and environmental factors as exposures relating to postcrash outcomes (injury, disability, death, property damage, quality of life, etc). Population sources include registered injured people and followed up healthy people in precrash cohort experienced RTIs. It includes four first-year follow-ups, 1 month (phone-based), 3 months (in-person, video/phone call), 6 and 12 months (phone-based) after crash. Then, 24-month and 36-month follow-ups will be conducted triennially. Various questionnaires such as Post-traumatic Stress Disorder Questionnaire, Patient Health Questionnaire, WHO Disability Assessment Schedules, Cost-related Information, etc are completed. Counselling with a psychiatrist and a medical visit by a practitioner are provided accompanied by extra tools (simulator-based driving assessment, and psychophysiological tests). Through preliminary recruitment plan, 5807, 2905, 2247 and 1051 subjects have been enrolled, respectively at the baseline, first, second and third follow-ups by now. At baseline, cars and motorcycles accounted for over 30% and 25% of RTIs. At first follow-up, 27% of participants were pedestrians engaged mostly in car crashes. Around a fourth of injuries were single injuries. Car occupants were injured in 40% of collisions. DISCUSSION: The study provides an opportunity to investigate physical-psychosocial outcomes of RTIs, predictors and patterns at follow-up phases postinjury through longitudinal assessments, to provide advocates for evidence-based safety national policy-making.


Subject(s)
Pedestrians , Wounds and Injuries , Accidents, Traffic , Humans , Motorcycles , Prospective Studies , Quality of Life , Wounds and Injuries/epidemiology
4.
PLoS One ; 17(5): e0268190, 2022.
Article in English | MEDLINE | ID: covidwho-1855025

ABSTRACT

This study investigates the important role of attendant factors, such as road traffic victims' access to trauma centres, the robustness of health infrastructure, and the responsiveness of police and emergency services in the incidence of Road Traffic Injuries (RTI) during the pandemic-induced COVID-19 lockdowns. The differential effects of the first and second waves of the pandemic concerning perceived health risk and legal restrictions provide us with a natural experiment that helps us differentiate between the impact of attendant factors and the standard relationship between mobility and Road Traffic Injuries. The authors use the auto-regressive recurrent neural network method on two population levels-Tamil Nadu (TN), a predominantly rural state, and Chennai, the most significant metropolitan city of the state, to draw causal inference through counterfactual predictions on daily counts of road traffic deaths and Road Traffic Injuries. During the first wave of the pandemic, which was less severe than the second wave, the traffic flow was correlated to Road Traffic Death/Road Traffic Injury. In the second wave's partial and post lockdown phases, an unprecedented fall of over 70% in Road Traffic Injury-Grievous as against Road Traffic Injury-Minor was recorded. Attendant factors, such as the ability of the victim to approach relief centres, the capability of health and other allied infrastructures, transportation and medical treatment of road traffic crash victims, and minimal access to other emergency services, including police, assumed greater significance than overall traffic flow in the incidence of Road Traffic Injury in the more severe second wave. These findings highlight the significant role these attendant factors play in producing the discrepancy between the actual road traffic incident rate and the officially registered rate. Thus, our study enables practitioners to observe the mobility-adjusted actual incidence rate devoid of factors related to reporting and registration of accidents.


Subject(s)
COVID-19 , Wounds and Injuries , Accidents, Traffic , COVID-19/epidemiology , Communicable Disease Control , Humans , India , Pandemics , Wounds and Injuries/epidemiology
5.
Accid Anal Prev ; 172: 106687, 2022 Jul.
Article in English | MEDLINE | ID: covidwho-1803319

ABSTRACT

Risky driving behaviors such as speeding and failing to signal have been witnessed more frequently during the COVID-19 pandemic, resulting in higher rates of severe crashes. This study aims to investigate how the COVID-19 pandemic impacts the likelihood of severe crashes via changing driving behaviors. Multigroup structural equation modeling (SEM) is used to capture the complex interrelationships between crash injury severity, the context of COVID-19, driving behaviors, and other risk factors for two different groups, i.e., highways and non-highways. The SEM constructs two latent variables, namely aggressiveness and inattentiveness, which are indicated by risk driving behaviors such as speeding, drunk driving, and distraction. One great advantage of SEM is that the measurement of latent variables and interrelationship modeling can be achieved simultaneously in one statistical estimation procedure. Group differences between highways and non-highways are tested using different equality constraints and multigroup SEM with equal regressions can deliver the augmented performance. The smaller severity threshold for the highway group indicates that it is more likely that a crash could involve severe injuries on highways as compared to those on non-highways. Results suggest that aggressiveness and inattentiveness of drivers increased significantly after the outbreak of COVID-19, leading to a higher likelihood of severe crashes. Failing to account for the indirect effect of COVID-19 via changing driving behaviors, the conventional probit model suggests an insignificant impact of COVID-19 on crash severity. Findings of this study provide insights into the effect of changing driving behaviors on safety during disruptive events like COVID-19.


Subject(s)
Automobile Driving , COVID-19 , Accidents, Traffic , Humans , Latent Class Analysis , Pandemics , Risk Factors
6.
Transl Vis Sci Technol ; 11(3): 22, 2022 03 02.
Article in English | MEDLINE | ID: covidwho-1799157

ABSTRACT

Purpose: Advanced driver assistance systems (ADAS) have been reported to improve the safety of elderly and normally sighted drivers. The purpose of this study was to assess exposure to, perceived safety of, comfort level with, and interest in using ADAS among drivers with age-related macular degeneration (AMD). Methods: Current drivers aged 60+ years were recruited at four US sites to complete a survey about ADAS and driving habits. Frequency of use and/or perceptions of eight ADAS were investigated. An avoidance score was generated using questions about difficult driving situations. Results: The survey was completed by 166 participants (80 with AMD vs. 86 without). Participants with AMD had worse self-rated vision than those without (34% vs. 2% poor or fair rating), and drove fewer weekly miles (median [interquartile range [IQR] 30 [15 to 75] vs. 60 [30 to 121] miles, P = 0.002). Participants with AMD reported more avoidance of difficult driving situations (P < 0.001). There was no difference in the number of ADAS used by AMD status (median [IQR for AMD = 2.5 [1 to 5] vs. 3 [2 to 4] without, P = 0.87). Greater reported number of ADAS used was associated with less avoidance of difficult situations (P = 0.02). The majority perceived improved safety with most ADAS. Conclusions: Many drivers with AMD utilize common ADAS, which subjectively improve their road safety and may help to reduce self-imposed restrictions for difficult situations and mileage. Translational Relevance: Drivers with AMD are adopting readily available ADAS, for which they reported potential benefits, such as safety and less restrictive driving.


Subject(s)
Automobile Driving , Macular Degeneration , Accidents, Traffic , Aged , Humans , Macular Degeneration/therapy , Surveys and Questionnaires
7.
BMJ Open ; 12(4): e059312, 2022 04 13.
Article in English | MEDLINE | ID: covidwho-1788967

ABSTRACT

OBJECTIVE: To identify and prioritise the research needed to help Nepali agencies develop an improved road safety system. DESIGN: Delphi study. SETTING: Nepal. PARTICIPANTS: Stakeholders from government institutions, academia, engineering, healthcare and civil society were interviewed to identify knowledge gaps and research questions. Participants then completed two rounds of ranking and a workshop. RESULTS: A total of 93 participants took part in interviews and two rounds of ranking. Participants were grouped with others sharing expertise relating to each of the five WHO 'pillars' of road safety: (1) road safety management; (2) safer roads; (3) safer vehicles; (4) safer road users and (5) effective postcrash response. Interviews yielded 1019 research suggestions across the five pillars. Two rounds of ranking within expert groups yielded consensus on the important questions for each pillar. A workshop involving all participants then led to the selection of 6 questions considered the most urgent: (1) How can implementing agencies be made more accountable? (2) How should different types of roads, and roads in different geographical locations, be designed to make them safer for all road users? (3) What vehicle fitness factors lead to road traffic crashes? (4) How can the driver licensing system be improved to ensure safer drivers? (5) What factors lead to public vehicle crashes and how can they be addressed? and (6) What factors affect emergency response services getting to the patient and then getting them to the right hospital in the best possible time? CONCLUSIONS: The application of the Delphi approach is useful to enable participants representing a range of institutions and expertise to contribute to the identification of road safety research priorities. Outcomes from this study provide Nepali researchers with a greater understanding of the necessary focus for future road safety research.


Subject(s)
Automobile Driving , Accidents, Traffic/prevention & control , Delphi Technique , Humans , Licensure , Nepal , Research , Safety
8.
PLoS One ; 17(4): e0266097, 2022.
Article in English | MEDLINE | ID: covidwho-1779760

ABSTRACT

BACKGROUND: Shareable e-scooters have become popular, but injuries to riders and bystanders have not been well characterized. The goal of this study was to describe e-scooter injuries and estimate the rate of injury per e-scooter trip. METHODS AND FINDINGS: Retrospective review of patients presenting to 180 clinics and 2 hospitals in greater Los Angeles between January 1, 2014 and May 14, 2020. Injuries were identified using a natural language processing (NLP) algorithm not previously used to identify injuries, tallied, and described along with required healthcare resources. We combine these tallies with municipal data on scooter use to report a monthly utilization-corrected rate of e-scooter injuries. We searched 36 million clinical notes. Our NLP algorithm correctly classified 92% of notes in the testing set compared with the gold standard of investigator review. In total, we identified 1,354 people injured by e-scooters; 30% were seen in more than one clinical setting (e.g., emergency department and a follow-up outpatient visit), 29% required advanced imaging, 6% required inpatient admission, and 2 died. We estimate 115 injuries per million e-scooter trips were treated in our health system. CONCLUSIONS: Our observed e-scooter injury rate is likely an underestimate, but is similar to that previously reported for motorcycles. However, the comparative severity of injuries is unknown. Our methodology may prove useful to study other clinical conditions not identifiable by existing diagnostic systems.


Subject(s)
Accidents, Traffic , Natural Language Processing , Emergency Service, Hospital , Humans , Motorcycles , Retrospective Studies
9.
Front Public Health ; 10: 849547, 2022.
Article in English | MEDLINE | ID: covidwho-1776064

ABSTRACT

Fatal vehicle crashes (FVCs) are among the leading causes of death worldwide. Professional drivers often drive under dangerous conditions; however, knowledge of the risk factors for FVCs among professional drivers remain scant. We investigated whether professional drivers have a higher risk of FVCs than non-professional drivers and sought to clarify potential risk factors for FVCs among professional drivers. We analyzed nationwide incidence rates of FVCs as preliminary data. Furthermore, by using these data, we created a 1:4 professionals/non-professionals preliminary study to compare with the risk factors between professional and non-professional drivers. In Taiwan, the average crude incidence rate of FVCs for 2003-2016 among professional drivers was 1.09 per 1,000 person-years; professional drivers had a higher percentage of FVCs than non-professional drivers among all motor vehicle crashes. In the 14-year preliminary study with frequency-matched non-professional drivers, the risk of FVCs among professional drivers was significantly associated with a previous history of involvement in motor vehicle crashes (adjustment odds ratio [OR] = 2.157; 95% confidence interval [CI], 1.896-2.453), previous history of benzodiazepine use (adjustment OR = 1.385; 95% CI, 1.215-1.579), and speeding (adjustment OR = 1.009; 95% CI, 1.006-1.013). The findings have value to policymakers seeking to curtail FVCs.


Subject(s)
Accidents, Traffic , Automobile Driving , Accidents, Traffic/mortality , Humans , Incidence , Occupations , Taiwan/epidemiology
10.
Traffic Inj Prev ; 23(4): 193-197, 2022.
Article in English | MEDLINE | ID: covidwho-1752012

ABSTRACT

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.


Subject(s)
Accidents, Traffic , COVID-19 , COVID-19/epidemiology , Communicable Disease Control , Humans , Italy/epidemiology , SARS-CoV-2
11.
PLoS One ; 17(3): e0264484, 2022.
Article in English | MEDLINE | ID: covidwho-1736510

ABSTRACT

Companies developing automated driving system (ADS) technologies have spent heavily in recent years to conduct live testing of autonomous vehicles operating in real world environments to ensure their reliable and safe operations. However, the unexpected onset and ongoing resurgent effects of the Covid-19 pandemic starting in March 2020 has serve to halt, change, or delay the achievement of these new product development test objectives. This study draws on data obtained from the California automated vehicle test program to determine the extent that testing trends, test resumptions, and test environments have been affected by the pandemic. The importance of government policies to support and enable autonomous vehicles development during pandemic conditions is highlighted.


Subject(s)
Automation/methods , Mechanical Tests/methods , Accidents, Traffic/prevention & control , Accidents, Traffic/trends , Automation/economics , Automobile Driving/statistics & numerical data , COVID-19/economics , California , Humans , Mechanical Tests/economics , User-Centered Design
12.
Med Health Care Philos ; 25(2): 219-224, 2022 Jun.
Article in English | MEDLINE | ID: covidwho-1669909

ABSTRACT

The seat belt analogy argument is aimed at furthering the success of coercive vaccination efforts on the basis that the latter is similar to compulsory use of seat belts. However, this article demonstrated that this argument does not work so well in practice due to several reasons. The possibility of saving resources in health care does not usually apply in our societies, and the paternalist mentality that contributed to the implementation of seat belt-wearing obligation was predominant 30 years ago, but it does not apply at this moment. Furthermore, the risk/benefit analysis is totally different in both scenarios. In the case of seat belts, there is no way to discriminate between the users. In the case of vaccines, individuals present with unique circumstances that may differ substantially from those of another and might be foreseen a priori. This means that an analysis must be performed individually before vaccination is imposed. Finally, one must keep in mind that seat belts are often the only way in which we can protect third parties against a tragic hit by the occupant of another vehicle and are very efficient tools for this purpose. Vaccines, in contrast, do not always create sterilising immunity and are definitely not the only way by which we can avoid spreading a virus; immunity certificates, isolation, or even confinement may also serve as viable methods to achieve this purpose.


Subject(s)
COVID-19 , Seat Belts , Accidents, Traffic , COVID-19/epidemiology , COVID-19/prevention & control , Humans , Pandemics/prevention & control , Vaccination
14.
Accid Anal Prev ; 167: 106586, 2022 Mar.
Article in English | MEDLINE | ID: covidwho-1664570

ABSTRACT

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.


Subject(s)
Accidents, Traffic , COVID-19 , Bicycling , Humans , New York City , Policy , SARS-CoV-2
15.
Sensors (Basel) ; 22(2)2022 Jan 08.
Article in English | MEDLINE | ID: covidwho-1630027

ABSTRACT

This paper aims to provide a review of the electrically assisted bicycles (also known as e-bikes) used for recovery of the rider's physical and physiological information, monitoring of their health state, and adjusting the "medical" assistance accordingly. E-bikes have proven to be an excellent way to do physical activity while commuting, thus improving the user's health and reducing air pollutant emissions. Such devices can also be seen as the first step to help unhealthy sedentary people to start exercising with reduced strain. Based on this analysis, the need to have e-bikes with artificial intelligence (AI) systems that recover and processe a large amount of data is discussed in depth. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were used to complete the relevant papers' search and selection in this systematic review.


Subject(s)
Artificial Intelligence , Bicycling , Accidents, Traffic , Electricity , Humans , Transportation
16.
Emerg Med Australas ; 34(2): 150-156, 2022 Apr.
Article in English | MEDLINE | ID: covidwho-1626693

ABSTRACT

This scoping review describes the current state of research about two-wheeled delivery riders who have been injured while performing commercial food delivery. The key areas of interest are the patterns of injury, associated risk factors and current gaps in knowledge. Five databases were searched to identify key papers that describe injuries to two-wheeled food delivery riders. Papers were assessed for quality and eligibility and key information was extracted relating to patterns of injury and risk factors. From an initial 264 records from PubMed, Embase, CINAHL, Scopus and SafetyLit, studies were screened by title, abstract and full text to yield 12 key papers for analysis. No papers reporting on Australian data were identified. Men comprise over 85% of workers in the food delivery industry. The average age of injured riders varies by country, but is commonly under 30 years old. Most injuries are lower limb musculoskeletal injuries, although there are no consistent data about frequency, severity or cost to the healthcare system. Twenty-three key risk factors were categorised according to rider characteristics, working conditions and environmental factors. The most common risk factors were younger age, lack of driving experience, time-pressured work and inadequate protective gear. There are very few publications describing food delivery rider injuries and risk factors. This is an emerging industry in which the worker population may be younger and more vulnerable. Given the different legal and cultural contexts across different countries, Australian-specific research is needed.


Subject(s)
Motorcycles , Wounds and Injuries , Accidents, Traffic , Adult , Australia/epidemiology , Emergency Service, Hospital , Humans , Male , Risk Factors
17.
N Engl J Med ; 386(2): 148-156, 2022 Jan 13.
Article in English | MEDLINE | ID: covidwho-1621318

ABSTRACT

BACKGROUND: The effect of cannabis legalization in Canada (in October 2018) on the prevalence of injured drivers testing positive for tetrahydrocannabinol (THC) is unclear. METHODS: We studied drivers treated after a motor vehicle collision in four British Columbia trauma centers, with data from January 2013 through March 2020. We included moderately injured drivers (those whose condition warranted blood tests as part of clinical assessment) for whom excess blood remained after clinical testing was complete. Blood was analyzed at the provincial toxicology center. The primary outcomes were a THC level greater than 0, a THC level of at least 2 ng per milliliter (Canadian legal limit), and a THC level of at least 5 ng per milliliter. The secondary outcomes were a THC level of at least 2.5 ng per milliliter plus a blood alcohol level of at least 0.05%; a blood alcohol level greater than 0; and a blood alcohol level of at least 0.08%. We calculated the prevalence of all outcomes before and after legalization. We obtained adjusted prevalence ratios using log-binomial regression to model the association between substance prevalence and legalization after adjustment for relevant covariates. RESULTS: During the study period, 4339 drivers (3550 before legalization and 789 after legalization) met the inclusion criteria. Before legalization, a THC level greater than 0 was detected in 9.2% of drivers, a THC level of at least 2 ng per milliliter in 3.8%, and a THC level of at least 5 ng per milliliter in 1.1%. After legalization, the values were 17.9%, 8.6%, and 3.5%, respectively. After legalization, there was an increased prevalence of drivers with a THC level greater than 0 (adjusted prevalence ratio, 1.33; 95% confidence interval [CI], 1.05 to 1.68), a THC level of at least 2 ng per milliliter (adjusted prevalence ratio, 2.29; 95% CI, 1.52 to 3.45), and a THC level of at least 5 ng per milliliter (adjusted prevalence ratio, 2.05; 95% CI, 1.00 to 4.18). The largest increases in a THC level of at least 2 ng per milliliter were among drivers 50 years of age or older (adjusted prevalence ratio, 5.18; 95% CI, 2.49 to 10.78) and among male drivers (adjusted prevalence ratio, 2.44; 95% CI, 1.60 to 3.74). There were no significant changes in the prevalence of drivers testing positive for alcohol. CONCLUSIONS: After cannabis legalization, the prevalence of moderately injured drivers with a THC level of at least 2 ng per milliliter in participating British Columbia trauma centers more than doubled. The increase was largest among older drivers and male drivers. (Funded by the Canadian Institutes of Health Research.).


Subject(s)
Accidents, Traffic , Cannabis , Dronabinol/blood , Ethanol/blood , Adult , Age Distribution , Alcohol Drinking/adverse effects , Alcohol Drinking/epidemiology , British Columbia , Dronabinol/adverse effects , Female , Humans , Legislation, Drug , Male , Marijuana Use/epidemiology , Middle Aged
18.
Int J Environ Res Public Health ; 19(1)2022 01 04.
Article in English | MEDLINE | ID: covidwho-1613758

ABSTRACT

Young drivers are generally associated with risky driving behaviors that can lead to crash involvement. Many self-report measurement scales are used to assess such risky behaviors. This study is aimed to understand the risky driving behaviors of young adults in Qatar and how such behaviors are associated with crash involvement. This was achieved through the usage of validated self-report measurement scales adopted for the Arabic context. A nationwide cross-sectional and exploratory study was conducted in Qatar from January to April 2021. Due to the Covid-19 pandemic, the survey was conducted online. Therefore, respondents were selected conveniently. Hence, the study adopted a non-probability sampling method in which convenience and snowball sampling were used. A total of 253 completed questionnaires were received, of which 57.3% were female, and 42.7% were male. Approximately 55.8% of these young drivers were involved in traffic accidents after obtaining their driving license. On average, most young drivers do have some risky driving behavior accompanied by a low tendency to violate traffic laws, and their driving style is not significantly controlled by their personality on the road. The older young drivers are more involved in traffic accidents than the younger drivers, i.e., around 1.5 times more likely. Moreover, a young male driver is 3.2 times less likely to be involved in traffic accidents than a female driver. In addition, males are only 0.309 times as likely as females to be involved in an accident and have approximately a 70% lower likelihood of having an accident versus females. The analysis is complemented with the association between young drivers' demographic background and psychosocial-behavioral parameters (linking risky driving behavior, personality, and obligation effects on crash involvement). Some interventions are required to improve driving behavior, such as driving apps that are able to monitor and provide corrective feedback.


Subject(s)
Automobile Driving , COVID-19 , Accidents, Traffic , Cross-Sectional Studies , Female , Humans , Male , Pandemics , Qatar/epidemiology , Risk-Taking , SARS-CoV-2 , Surveys and Questionnaires , Young Adult
19.
PLoS One ; 16(3): e0243263, 2021.
Article in English | MEDLINE | ID: covidwho-1576004

ABSTRACT

As mobile device location data become increasingly available, new analyses are revealing the significant changes of mobility pattern when an unplanned event happened. With different control policies from local and state government, the COVID-19 outbreak has dramatically changed mobility behavior in affected cities. This study has been investigating the impact of COVID-19 on the number of people involved in crashes accounting for the intensity of different control measures using Negative Binomial (NB) method. Based on a comprehensive dataset of people involved in crashes aggregated in New York City during January 1, 2020 to May 24, 2020, people involved in crashes with respect to travel behavior, traffic characteristics and socio-demographic characteristics are found. The results show that the average person miles traveled on the main traffic mode per person per day, percentage of work trip have positive effect on person involved in crashes. On the contrary, unemployment rate and inflation rate have negative effects on person involved in crashes. Interestingly, different level of control policies during COVID-19 outbreak are closely associated with safety awareness, driving and travel behavior, and thus has an indirect influence on the frequency of crashes. Comparing to other three control policies including emergence declare, limits on mass gatherings, and ban on all nonessential gathering, the negative relationship between stay-at-home policy implemented in New York City from March 20, 2020 and the number of people involved crashes is found in our study.


Subject(s)
Accidents, Traffic/statistics & numerical data , Automobile Driving/statistics & numerical data , COVID-19 , Safety/statistics & numerical data , Travel/statistics & numerical data , Humans , New York City , Public Policy , Risk-Taking
20.
BMJ Glob Health ; 6(12)2021 12.
Article in English | MEDLINE | ID: covidwho-1571196

ABSTRACT

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.


Subject(s)
Accidents, Traffic , COVID-19 , Accidents, Traffic/prevention & control , Humans , Interrupted Time Series Analysis , SARS-CoV-2 , Zambia/epidemiology
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