Environmental factors affecting the frequency of road traffic accidents: a case study of sub-urban area of Pakistan

Factors associated with road traffic injury in a high-risk zone of Bangladesh: a mixed-method study

INTRODUCTION

Road traffic injuries are a significant public health issue in low-income and middle-income countries. This study was designed to explore the pattern and factors associated with road traffic injury in a high-risk zone of Bangladesh.

METHOD

This mixed-method study included a total of 363 road traffic injury victims for the quantitative component, and 10 traffic-related officials and 10 drivers for the qualitative element. Data were collected using a pretested questionnaire, key informant interviews and a focus group discussion using a focus group discussion guide. Quantitative and qualitative analyses were done using Stata V.17 and NVivo V.12, respectively.

RESULTS

Most participants were male, illiterate and young (<30 years) with age averaging 31.50±9.16 years. Of all road traffic injury victims, most had mild (45.18%) injuries, and the least had severe (5.79%) injuries, with head being the most common site (34.44%). The highest proportion of injuries were sustained by motor vehicle drivers (57.58%), followed by cyclists/rickshaw pullers (22.59%) and passengers (19.83%). Most vehicles were new (75.21%), and the rest were old (24.79%). Nearly one-third of the participants did not know about driving rules. The presence of knowledge was associated with less severe injury (p=0.031) compared with the absence of knowledge. The qualitative component of the study identified several factors related to road traffic injury, including driver factors (lack of sleep, bad driving habits and lack of helmets), driving activity factors (ignoring rules, overtaking, crossing speed limits and using bright headlights), road-related factors (broken roads, unplanned curves and angles, the need for spacious streets and the lack of appraisal of previous crash records) and traffic control factors (stringent traffic rules, effective implementation and training on using speed guns).

CONCLUSION

The factors related to road traffic injury identified in this study could be used to plan targeted interventions for road safety improvement.

Predicting the type of road accidents based on air temperature in Iran: A case study of roads in Qazvin province

This study investigates the relationship between ambient temperature, weather conditions, and types of road accidents in Qazvin province, Iran. The research addresses a significant societal challenge of road accidents, particularly in developing countries like Iran. The objectives are to analyze the correlation between temperature and accident types and to develop a predictive model using data mining techniques. The study employs a quantitative approach, analyzing over 15,000 accident records from 2010 to 2020. The findings reveal a connection between the temperature variable and the type of road accidents as well as weather conditions. Additionally, data mining analysis identifies a predictable pattern among temperature variables, types of road accidents, and weather conditions. Implications of the study underscore the importance of considering temperature and weather conditions as secondary factors influencing accidents. The predictive model can aid decision-makers in formulating effective strategies to reduce accidents. Understanding the relationship between temperature, weather, and accident types enables the design of targeted interventions to enhance road safety. This research contributes valuable insights to accident reduction efforts and emphasizes the significance of addressing environmental variables in road safety planning and policy-making. Moreover, the results of the data mining pattern analysis indicate that car overturning accidents in various weather conditions are the primary type of accidents, followed by chain accidents. However, the types of accidents vary based on different weather conditions and temperatures. The study highlights the intricate connection between weather conditions, temperature, and types of road accidents. By utilizing data mining techniques, the research provides a predictive model for accident patterns, offering valuable insights to enhance road safety strategies.

Spatiotemporal variation in the vegetation cover of Peshawar Basin in response to climate change

Climate factors like temperature, precipitation, humidity, and sunshine time exert a profound influence on vegetation. The intricate interplay between the two is crucial to understand in the face of changing climate to develop mitigation strategies. In the current exploration, we delve how climate variability (CV) has impacted the vegetation in the Peshawar Basin (PB) using remote sensing data tools. The trend of climatic variability was investigated using the modified Mann-Kendall test and Sen's slope statistics. The changing climatic parameters were regressed on the Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI). The NDVI was further analyzed for spatiotemporal variability under land surface temperature (LST) influence. Results revealed that among the climate factors, average annual temperature and solar radiation have a significant (p < 0.05) negative impact on vegetation while precipitation and relative humidity significantly (p < 0.05) influence NDVI positively. The overall positive trend shows that vegetation improved between 2001 and 2020 with time, however some years (2010, 2012, 2014, 2016, and 2017) with low NDVI. NDVI varied in space considerably due to climatic extremes brought on by CV and the urbanization of agricultural land. NDVI regressed on LST showed that there was no or very little vegetation in the grids with high LST. The study concluded that the region is significantly impacted by both CV-related extreme weather events and anthropogenic activities. The vegetation is improving, but it is in danger of being destroyed by deforestation due to CV and human activities that exacerbate the risk of future calamities. To protect vegetation and avoid disasters, there is an immense need for adaptation and mitigation measures to deal with the region's fast-changing environment. The study urges local authorities to create climate-resilient governmental policies and supports regional sustainable development and vegetation restoration.

Causal analysis of coach and bus accidents in China based on road alignments

Given the complexity and the difficulty of controlling contributors effectively, road passenger transport often results in serious injuries and fatalities. The purpose of this study is to identify the main contributors to coach and bus accidents and to provide policy recommendations for making improvements in accident prevention. The Driving Reliability and Error Analysis Method 3.0 (DREAM 3.0) was modified and used to analyze the contributing factors (i.e. phenotypes and genotypes in DREAM) and their casual mechanisms. By having statistical analysis and social network analysis (SNA) adopted, the main genotypes and phenotypes of the DREAM charts were identified. The results of the study showed that A2.1 (too high speed) was the key phenotype and the main genotypic process chain leading to the phenotype was "inadequate safety management → inadequate training → inadequate skills/knowledge → misjudgment of the situation → too high speed" on all types of road. For A2.1 (too high speed), C2 (misjudgment of the situation) was the dominant genotype, while N5 (inadequate safety management) was the root cause of most genotypes. This suggests that road passenger transport companies, as the responsible parties, often fail to implement or violate safety prevention and control systems. Government regulators should promote the policy system and incentivize them to fulfil their safety management responsibilities. The government should also educate the public and improve the road environment to reduce passenger-related risks and the impact of environmental factors on drivers.

Traffic costs of air pollution: the effect of PM2.5 on traffic violation

Although emerging studies have investigated the effect of air pollution on traffic crashes, it is unclear to scholars whether air pollution affects another road safety problem-traffic violations. To address this gap, the current paper constructs a data set from 1,390,221 traffic violation records of 640,971 drivers from the Wuhan Traffic Management Bureau between January 2018 and December 2018. An ordered logistic regression was conducted to verify our hypotheses. The result shows that PM_2.5 has no overall impact on the severity of traffic violations, but each 1% increase in the daily concentration of PM_2.5 leads to a 1.02-fold increase in the odds of serious inexperience-related violations and a 0.99-fold decrease in the odds of serious overconfidence-related violations. This effect is the strongest in PM_2.5, followed by NO₂, and has not been observed in CO and O₃. In addition, robustness tests indicate that the relationship between air pollution and traffic violations is consistent among the different subsets (e.g., clear weather, no rain and snow, and good visibility). We also provide valuable practical advice for drivers and traffic authorities.

The relationship between ambient temperatures and road traffic injuries: a systematic review and meta-analysis

Traffic accidents cause considerable economic losses and injuries. Although the adverse effects of a change in ambient temperatures on human health have been widely documented, its effects on road traffic safety are still debated. This systematic review and meta-analysis was performed to synthesize available data on the association between ambient temperature and the risks of road traffic accidents (RTAs) and traffic accident injuries (TAIs). We searched 7 different databases to locate studies. The subgroup analyses were stratified by temperature type, temperature exposure, region, mean temperature, mortality, study period, statistical model, and source of injury data. This study was registered with PROSPERO under the number CRD42021264660. This is the first meta-analysis to investigate the association between ambient temperature and road traffic safety. A total of 34 high-temperature effect estimates were reported, and two additional studies reported the relationship between low temperatures and TAI risk. The meta-analysis results found a significant association between the high temperature and RTAs, and the pooled RR was 1.025 (95%CI 1.014, 1.035). The risk of TAI was also significantly associated with temperature increases. Subgroup analyses found that using daily mean temperatures, the RR value of road traffic accidents was 1.024 (95%CI 0.939, 1.116), and the RR value of road traffic injuries was 1.052 (95%CI 1.024, 1.080). Hourly temperatures significantly increased the risk of RTA, while the risk of TAI was not significantly increased by hourly temperature. The sensitivity analysis indicated that the results were stable, and no obvious publication bias was detected. The results of this systematic review and meta-analysis suggest that increases in ambient temperature are associated with an increased risk of RTAs and TAIs. These findings add to the evidence of the impact of ambient temperature on road traffic safety.

Association of Air Pollution and Weather Factors with Traffic Injury Severity: A Study in Taiwan

Exposure to air pollutants may elevate the injury severity scores (ISSs) for road traffic injuries (RTIs). This multicenter cross-sectional study aimed to investigate the associations between air pollution, weather conditions, and RTI severity. This retrospective study was performed in Taiwan in 2018. The location of each road traffic accident (RTA) was used to determine the nearest air quality monitoring and weather station, and the time of each RTA was matched to the corresponding hourly air pollutant concentration and weather factors. Five multiple logistic regression models were used to compute the risk of sustaining severe injury (ISS ≥ 9). Of the 14,973 patients with RTIs, 2853 sustained severe injury. Moderate or unhealthy air quality index, higher exposure to particulate matter ≤2.5 μm in diameter, bicyclists or pedestrians, greater road width, nighttime, and higher temperature and relative humidity were significant risk factors for severe injury. Exposure to nitrogen oxide and ozone did not increase the risk. Auto occupants and scene-to-hospital time were the protective factors. Sensitivity analyses showed consistent results between air pollutants and the risk of severe injury. Poor air quality and hot and humid weather conditions were associated with severe RTIs. Active commuters were at higher risk of sustaining severe RTI.

What Factors Would Make Single-Vehicle Motorcycle Crashes Fatal? Empirical Evidence from Pakistan

The existing research on motorcycle safety has shown that single-vehicle motorcycle crashes (SVMC) account for a higher fatality rate than other types of crashes. Also, motorcycle safety has become one of the critical traffic safety issues in many developing countries, such as Pakistan, due to the growing number of motorcycles and lack of sufficient relevant infrastructure. However, the available literature on SVMC and motorcycle safety in developing countries is limited. Therefore, the present study attempted to investigate the factors that contribute to the injury severity of SVMC in a developing country, Pakistan. For this purpose, a random parameter logit model with heterogeneity in means and variances is developed using two years of data extracted from the road traffic injury research project in Karachi city, Pakistan. The study's findings show that the presence of pillion passengers and young motorcyclists indicators result in random parameters with heterogeneity in their means and variances. The study's results also reveal that the summer, morning time, weekends, older motorcyclists, collisions with fixed objects, speeding, and overtaking are positively, while younger motorcyclists and the presence of pillion passengers are negatively associated with fatal crashes. More importantly, in the particular Pakistan's context, female pillion passenger clothes trapped in the wheel, riding under the influence, intersections, U-turns, and collisions due to loss of control are also found to significantly influence the injury severity of SVMC. Based on these research findings, multiple appropriate countermeasures are recommended to enhance motorcycle safety in Pakistan and other developing countries with similar problems.

Pavement maintenance management framework for flexible roads: a case study of Pakistan

Roads play a pivotal role in the overall economic growth of any country. Developed countries allocated sufficient budget to make new roads and to maintain the existing roads. They also have a proper pavement management system (PMS) in practice to manage roads, whereas developing countries suffer from budgetary issues to make new roads and maintain the existing road network. Therefore, this paper explores the awareness of PMS via direct and indirect methods in Pakistan with a proposed framework of the low-cost model and pavement maintenance indicators for developing countries. This paper also performs a scientometric assessment of PMS. A detailed literature review has been carried out for this study, followed by a quantitative study from experienced professionals. The scientometric data is collected from the Scopus database from 1975 to 2020, whereas the data for PMS awareness assessment has been collected using questionnaires from different experts working directly and indirectly in the road management sector. The data has been analyzed using the arithmetic mean because of the nature of the questions and scope of the study. The direct method results show that experts are aware of PMS for a new road, but they have no PMS to rehabilitate roads. The indirect method results show that the authorities are applying various components of PMS, but there is no proper PMS in practice. This paper helps decision-makers to make better decisions and policies for improved road maintenance and rehabilitation. The proposed framework in the study can significantly assist the UN-SDG 9 (Facilitate Sustainable Infrastructure in Developing Countries) and 11 (Affordable and Sustainable Transport System).

GLM-Based Flexible Monitoring Methods: An Application to Real-Time Highway Safety Surveillance

Statistical modeling of historical crash data can provide essential insights to safety managers for proactive highway safety management. While numerous studies have contributed to the advancement from the statistical methodological front, minimal research efforts have been dedicated to real-time monitoring of highway safety situations. This study advocates the use of statistical monitoring methods for real-time highway safety surveillance using three years of crash data for rural highways in Saudi Arabia. First, three well-known count data models (Poisson, negative binomial, and Conway–Maxwell–Poisson) are applied to identify the best fit model for the number of crashes. Conway–Maxwell–Poisson was identified as the best fit model, which was used to find the significant explanatory variables for the number of crashes. The results revealed that the road type and road surface conditions significantly contribute to the number of crashes. From the perspective of real-time highway safety monitoring, generalized linear model (GLM)-based exponentially weighted moving average (EWMA) and cumulative sum (CUSUM) control charts are proposed using the randomized quantile residuals and deviance residuals of Conway–Maxwell (COM)–Poisson regression. A detailed simulation-based study is designed for predictive performance evaluation of the proposed control charts with existing counterparts (i.e., Shewhart charts) in terms of the run-length properties. The study results showed that the EWMA type control charts have better detection ability compared with the CUSUM type and Shewhart control charts under small and/or moderate shift sizes. Finally, the proposed monitoring methods are successfully implemented on actual traffic crash data to highlight the efficacy of the proposed methods. The outcome of this study could provide the analysts with insights to plan sound policy recommendations for achieving desired safety goals.

Using GIS tools to detect the land use/land cover changes during forty years in Lodhran District of Pakistan

Land use/land cover (LULC) change has serious implications for environment as LULC is directly related to land degradation over a period of time and results in many changes in the environment. Monitoring the locations and distributions of LULC changes is important for establishing links between regulatory actions, policy decisions, and subsequent LULC activities. The normalized difference vegetation index (NDVI) has the potential ability to identify the vegetation features of various eco-regions and provides valuable information as a remote sensing tool in studying vegetation phenology cycles. Similarly, the normalized difference built-up index (NDBI) may be used for quoting built-up land. This study aims to detect the pattern of LULC, NDBI, and NDVI change in Lodhran district, Pakistan, from the Landsat images taken over 40 years, considering four major LULC types as follows: water bodies, built-up area, bare soil, and vegetation. Supervised classification was applied to detect LULC changes observed over Lodhran district as it explains the maximum likelihood algorithm in software ERDAS imagine 15. Most farmers (46.6%) perceived that there have been extreme changes of onset of temperature, planting season, and less precipitation amount in Lodhran district in the last few years. In 2017, building areas increased (4.3%) as compared to 1977. NDVI values for Lodhran district were highest in 1977 (up to + 0.86) and lowest in 1997 (up to - 0.33). Overall accuracy for classification was 86% for 1977, 85% for 1987, 86% for 1997, 88% for 2007, and 95% for 2017. LULC change with soil types, temperature, and NDVI, NDBI, and slope classes was common in the study area, and the conversions of bare soil into vegetation area and built-up area were major changes in the past 40 years in Lodhran district. Lodhran district faces rising temperatures, less irrigation water, and low rainfall. Farmers are aware of these climatic changes and are adapting strategies to cope with the effects but require support from government.

Developing the first halophytic turfgrasses for the urban landscape from native Arabian desert grass

Climate change is occurring and is influencing biological systems through augmented temperatures, more inconstant precipitation, and rising CO₂ in the atmosphere. For sustainable landscaping, it was essential to assess the diversity of native/wild grasses and their suitability for turf and to combat the salinity problem in the region. For this purpose, a native halophytic grass, Aeluropus lagopoides, was investigated by conducting mowing tests on its ecotypes during the year 2014-2016 under desert climatic conditions. The research was carried out in two phases, i.e. Phase-I was for collection and establishment of ecotypes from various parts of UAE, while in Phase-II, mowing tests were conducted. During mowing tests, 50 ecotypes of A. lagopoides were given various mowing treatments (i.e. they were cut back at 1-, 2-, 3-, 4- and 5-cm heights) in field conditions. Significant differences were found among various ecotypes for different agronomic parameters such as ground cover, canopy stiffness, leaf number, clippings fresh and dry weights and internode length. Overall, the grass exhibited better performance at mowing heights of 3 and 4 cm, which are the standard mowing heights for turfgrasses. Ecotypes FA5, RA3, RUDA2, RUDA7 and RUADA1 of A. lagopoides showed the best performance against mowing shock and became the candidates for the turfgrass varieties from the native Arabian flora.

The impact of temperature, rainfall, and health worker density index on road traffic fatalities in Pakistan

A road traffic accident is a burning issue because the cost of road accidents is about 2% of gross domestic product in Pakistan. This paper explores the relationship between health force density index, temperature, rainfall, road lengths, and road traffic fatalities in Pakistan from 1985 to 2016. The stationarity was determined with the help of four-unit root tests. The existence of long-run cointegration was determined by using the autoregressive distributing lag bound test. The vector error correction model showed the long-run causality of road traffic fatalities, which implies that road traffic fatalities were affected by selected variables in the long-run. The short-run unidirectional causality was running from road traffic fatalities to health force density index; temperature to health force density index; rainfall to health force density index; health force density index to rainfall; road traffic fatalities to high type road length; health force density index to high type road length; and temperature to high type roads. The reduction in road fatalities was 1.713% due to a 1% increase in health force density. But, road fatalities increase by 3.628% due to a 1% increase in temperature. The road fatalities increase by 0.255% and 0.485% due to a 1% increase in rainfall and high type road length, respectively. The governments should increase the number of doctors and nurses for the life-saving of an injured person. Due to the adverse impact of temperature on road safety, the government should formulate a comprehensive environmental policy in order to mitigate global warming. It is recommended to increase the forest area to reduce the level of emission. It is required to modify the system of transportation according to the guidelines of international transportation associations with respect to the quality and maintenance of vehicles, medical check-up of drivers, and construction of roads. Installation of speed cameras is also needed on high type roads to ensure road safety. It is also recommended to increase traffic law enforcement. It is difficult for the Pakistani government to effectively execute road safety plans due to the limitation of resources. However, the government should invest the revenue collected through tax violation fine for the improvement in road safety. It is also needed to invest in the health sector and up-gradation of the hospitals for the safety of human beings. The government should ensure the availability of the latest medical technology in the hospitals and the improvement of emergency services. It is required to develop coordination between various ministries such as transportation, planning, law, education, public health, and information. It is necessary to make the public aware of the social and economic cost of road accidents using electronic, print, and social media. Graphical abstract.

Effects of hourly precipitation and temperature on ambulance response time

BACKGROUND

Longer ambulance response time (ART) delaying treatment would worsen conditions of seriously ill or injured patients, but limited evidence is available on the effects of weather factors on ART. This study aims to assess precipitation- and temperature-ART associations and their potential lagged effects using a novel modeling strategy.

METHODS

Based on 779,156 emergency records during 2010-2016 from the whole population in Shenzhen, China, we creatively combined quantile regression with distributed-lag nonlinear models to examine the non-linear and lagged effects of hourly precipitation and temperature on ART at the 50th and 90th percentiles.

RESULTS

A linear precipitation-ART association with a delay of 9.01 (95%CI, 7.82-10.20) seconds at median ART for a 1 mm increase in hourly precipitation, and the effects lasted for 5 h with the greatest effect at the current hour. A two linear thresholds temperature-ART association revealed 1 °C decrease below 19 °C caused 1.68 (95%CI, 0.92-2.44) seconds delay in total ART over lag 0-7 h, and 1 °C increase above 24 °C caused 2.44 (95%CI, 1.55-3.33) seconds delay. The hourly call volumes exceeding 54 calls caused 8.79 (95%CI, 8.71-8.86) seconds delay in total ART for 1 more call, but not affected the effects of weather factors. The internal ART suffered more from the hourly call volumes, while the external ART suffered more from precipitation and temperature. The effects were apparently greater on ART at the 90th percentile than median.

CONCLUSIONS

Precipitation and temperature are independent risk factors for ambulance services performance, and their lagged effects are notable. The external ART and patients with long ART are vulnerable. More attention should be paid to weather and ART, and these findings may have implications for effective policies to reduce ART to protect public health.