Animal-vehicle collisions in Victoria, Australia: An under-recognised cause of road traffic crashes

Going, Going, Gone The Diminishing Capacity of Museum Specimen Collections to Address Global Change Research: A Case Study on Urban Reptiles

It has been increasingly popular to use natural history specimens to examine environmental changes. As the current functionality of museum specimens has extended beyond their traditional taxonomic role, there has been a renewed focus on the completeness of biological collections to provide data for current and future research. We used the collections of the Western Australian Museum to answer questions about the change in occurrence of five common reptile species due to the rapid urbanization of Perth. We recorded a significant decline in collection effort from the year 2000 onwards (F = 7.65, p < 0.01) compared to the period 1990–1999. Spatial analysis revealed that only 0.5% of our study region was well sampled, 8.5% were moderately sampled and the majority of the regions (91%) were poorly sampled. By analysing the trend of specimen acquisition from 1950 to 2010, we discovered a significant inconsistency in specimen sampling effort for 13 common reptile species across time and space. A large proportion of past specimens lacked information including the place and time of collection. An increase in investment to museums and an increase in geographically and temporally systematic collecting is advocated to ensure that collections can answer questions about environmental change.

Characteristics of kangaroo-related motor vehicle crashes

BACKGROUND

Kangaroo-related motor vehicle collisions are common but there is limited literature on this topic. Drivers confronted by kangaroos may choose to swerve or to directly collide with the kangaroo. The effect of these differing crash mechanisms, along with the effect of vehicle type or time of day, has not yet been reported.

METHODS

A retrospective cohort study was performed, examining patients admitted to our tertiary trauma centre for kangaroo-related motor vehicle collisions between 2000 and 2020. Data on patient demographics, crash characteristics, and hospital stay were collected and analysed.

RESULTS

A total of 366 patients were included and were predominantly male (76%) with an median age of 40. Swerve crashes were more common (59%) than direct impact and swerving was a statistically significant predictor of reduced injury severity score on multivariable analysis (other significant factors were female sex and no rollover). Motor vehicle crashes and motorbike crashes had differing crash characteristics. Motor vehicle crashes were more likely the result of swerving, and swerving was less likely to cause ejection or require extrication but more likely to cause rollover. Motorbike crashes however, were more likely the result of head on collision and riders were more likely to be ejected from the vehicle, require extrication, or be involved in a rollover. In terms of time of day, there were more crashes at dawn and there was a trend towards higher injury severity score and length of stay for night-time crashes.

CONCLUSION

For kangaroo-related motor vehicle crashes, predictors of increased injury severity score on multivariable analysis were male sex, direct impact, and rollover. Motorbikes and motor vehicles had differing crash mechanisms and characteristics, as did night-time crashes when compared to daytime or twilight crashes.

LEVEL OF EVIDENCE

IV, prognostic.

Involvement of Road Users from the Productive Age Group in Traffic Crashes in Saudi Arabia: An Investigative Study Using Statistical and Machine Learning Techniques

Road traffic crashes (RTCs) are a major problem for authorities and governments worldwide. They incur losses of property, human lives, and productivity. The involvement of teenage drivers and road users is alarmingly prevalent in RTCs since traffic injuries unduly impact the working-age group (15–44 years). Therefore, research on young people’s engagement in RTCs is vital due to its relevance and widespread frequency. Thus, this study focused on evaluating the factors that influence the frequency and severity of RTCs involving adolescent road users aged 15 to 44 in fatal and significant injury RTCs in Al-Ahsa, Saudi Arabia. In this study, firstly, descriptive analyses were performed to justify the target age group analysis. Then, prediction models employing logistic regression and CART were created to study the RTC characteristics impacting the target age group participation in RTCs. The most commonly observed types of crashes are vehicle collisions, followed by multiple-vehicle and pedestrian crashes. Despite its low frequency, the study area has a high severity index for RTCs, where 73% of severe RTCs include individuals aged 15 to 44. Crash events with a large number of injured victims and fatalities are more likely to involve people in the target age range, according to logistic regression and CART models. The CART model also suggests that vehicle overturn RTCs involving victims in the target age range are more likely to occur as a result of driver distraction, speeding, not giving way, or rapid turning. As compared with the logistic regression model, the CART model was more convenient and accurate for understanding the trends and predicting the involvement probability of the target age group in RTCs; however, this model requires a higher processing time for its development.

The Perils of Being Populous: Control and Conservation of Abundant Kangaroo Species

Australia's first people managed landscapes for kangaroo species as important elements of their diet, accoutrements and ceremony. This developed and persisted for about 65,000 years. The second wave of colonists from the United Kingdom, Ireland and many subsequent countries introduced familiar domesticated livestock and they have imposed their agricultural practices on the same landscapes since 1788. This heralded an ongoing era of management of kangaroos that are perceived as competitors to livestock and unwanted consumers of crops. Even so, a kangaroo image remains the iconic identifier of Australia. Kangaroo management is shrouded in dogma and propaganda and creates a tension along a loose rural-city divide. This divide is further dissected by the promotion of the consumption of kangaroo products as an ecological good marred by valid concerns about hygiene and animal welfare. In the last decade, the fervour to suppress and micro-manage populations of some kangaroo species has mounted. This includes suppression within protected areas that have generally been considered as safe havens. This review explores these tensions between the conservation of iconic and yet abundant wildlife, and conflict with people and the various interfaces at which they meet kangaroos.

A Study of the Pattern of Injuries Sustained from Road Traffic Accidents Caused by Impact with Stray Animals

Background

The incidence of road traffic accidents (RTA) is increasing every day, especially in developing nations. Amongst various attributable factors, the menace of the stray animals remains one of the most underrecognized factors leading to animal-vehicle collision (AVC). Objectives: Our prospective cross-sectional study aims to survey the incidence of RTA attributable to stray animals and record the pattern of injuries along with other epidemiological parameters.

Methods

The present study was conducted at a tertiary care trauma centre located in a major city of eastern India, between June 2019 and March 2020. Variables like demographic details, type of vehicle and injury with severity score, use of safety gear including types of stray animals were collected and analysed.

Results

A total of 185 patients had suffered RTA due to AVC during the study period. The median age of occurrence was 29.0 years. The evening was the most frequent time of accidents (4 PM to 8 PM) with two-wheelers affected in 92% of cases. Stray dogs account for 69% of cases followed by cattle 21% cases. 41% of all RTA victims had polytrauma. Patients with RTA due to impact with ox were found to have higher injury severity score (ISS). The ISS comparison between two-wheeler drivers with and without helmet and influence of alcohol were statistically significant (P<0.01).

Conclusion

The study highlights an alarming incidence of RTA due to stray animals roaming freely on roads, thus adding significant morbidity and costs to the society. There is a need of the hour for imposing stringent measures from the appropriate authority, including public awareness to make sustainable action plans to prevent animal homelessness and wander freely on streets and major roads.

Spatio-Temporal Patterns and Consequences of Road Kills: A Review

Simple Summary

Road kill continues to be a challenge in the 21st century. Numerous studies have sought to explain the causes and risks of animal-vehicle collisions that result in road kills, and how best to mitigate these events. This review evaluates the relevant literature on road kills, in order to determine how to effectively address them. Identifying methodologies and sources used in previous studies, how mortalities are normally recorded and reported was determined. Previous literature has suggested that spatial proximity, road infrastructure, traffic volume and velocity, driver awareness, landscape, climate and weather conditions, and animal behavior are the primary factors contributing to the spatio-temporal patterns of road kills. Important socioeconomic and environmental impacts of animal-vehicle collisions that result in road kills were also identified. Current mitigation measures for addressing road kills were examined from previous studies; including road management and wildlife crossing structures. Shortcomings to strategies and methodologies for addressing animal-vehicle collisions were subsequently assessed. Thereafter, the paper analysed geospatial technologies that have been utilised inroad kill studies. This review recommends focusing an all road kills in an area, using larger study locations, taking timelier observations, the increased use of citizen science, more research on nighttime driving speeds, and popularising effective road kill apps.

Abstract

The development and expansion of road networks have profoundly impacted the natural landscape and various life forms. Animals are affected by these roads in a myriad of ways, none as devastating as road mortalities. This article reviews the literature on the magnitude, spatiotemporal patterns, factors, and consequences of Animal-Vehicle Collisions (AVCs) and the subsequent road kills. Furthermore, the review paper briefly outlines the relationship between roads and animals in the surrounding landscape and later examines the nature and impacts of AVCs. This article evaluates the statistics on the number of road kills and a critical analysis of the spatiotemporal patterns of these mortalities is also evaluated. Subsequently, the review paper examines current mitigation measures and the challenges impeding their success. The paper then concludes with an evaluation of geospatial tools (GIS) and other technologies used in road kill studies. The relevant findings of this paper are that, (1) factors influencing road kill patterns interact with one another; (2) AVCs have serious environmental, economic and social consequences; (3) road kill mitigation strategies suffer several challenges hindering their success; and (4) specific geospatial tools and other technologies have been utilised in assessing AVC road kill patterns. The review, therefore, recommends including overall road kill clusters of all animals in mortality surveys, increasing the spatial coverage of road kill observations, consistent surveying, sufficient research on nighttime driving distances and speed, utilising citizen science in all road mortality studies and incorporating GIS into all apps used for recording road kills. An increased sufficiency in road kill data coupled with improved technologies can enable more effective mitigation strategies to prevent AVCs.

Classification of road traffic injury collision characteristics using text mining analysis: Implications for road injury prevention

Road traffic injuries are a leading cause of morbidity and mortality globally. Understanding circumstances leading to road traffic injury is crucial to improve road safety, and implement countermeasures to reduce the incidence and severity of road trauma. We aimed to characterise crash characteristics of road traffic collisions in Victoria, Australia, and to examine the relationship between crash characteristics and fault attribution. Data were extracted from the Victorian State Trauma Registry for motor vehicle drivers, motorcyclists, pedal cyclists and pedestrians with a no-fault compensation claim, aged > = 16 years and injured 2010-2016. People with intentional injury, serious head injury, no compensation claim/missing injury event description or who died < = 12-months post-injury were excluded, resulting in a sample of 2,486. Text mining of the injury event using QDA Miner and Wordstat was used to classify crash circumstances for each road user group. Crashes in which no other was at fault included circumstances involving lost control or avoiding a hazard, mechanical failure or medical conditions. Collisions in which another was predominantly at fault occurred at intersections with another vehicle entering from an adjacent direction, and head-on collisions. Crashes with higher prevalence of unknown fault included multi-vehicle collisions, pedal cyclists injured in rear-end collisions, and pedestrians hit while crossing the road or navigating slow traffic areas. We discuss several methods to promote road safety and to reduce the incidence and severity of road traffic injuries. Our recommendations take into consideration the incidence and impact of road trauma for different types of road users, and include engineering and infrastructure controls through to interventions targeting or accommodating human behaviour.

Vehicle fatalities involving collisions with kangaroos

A search was undertaken of the Forensic Science South Australia (FSSA), Australia, autopsy database over a 20-year period from 2000 to 2019 for all cases where vehicle crashes had involved kangaroos. There were six cases with an age range of 18-62 years (M=42 years) and a male-to-female ratio of 5:1. There were three crashes involving motor vehicles and three involving motorcycles. The three motor-vehicle crashes were initiated by impact with a kangaroo followed by a head-on crash with a truck (n=1) and a tree (n=2). In two of the motorcycle crashes, the cycle hit a kangaroo, resulting in the rider being unseated. In the third case, following impact with the animal, the cyclist hit a tree. In one of the latter cases, the only evidence of impact with a kangaroo was fur found by investigating officers adherent to the front-right indicator. Lethal injuries were located in the chest in six cases, the cranio-cervical region in five cases and the abdomen in three cases. Thus, in the majority of cases (n=5), death was due to multiple injuries. In the remaining case, death was caused by blunt chest trauma. This study shows that kangaroo-vehicle impacts may result in very significant blunt-force trauma. Motorcycle riders are particularly vulnerable. It may be only by careful examination of the vehicle/motorcycle for animal residues that the nature of the incident will be clarified.

Developing a correction factor to apply to animal–vehicle collision data for improved road mitigation measures

Abstract ContextRoad mitigation to reduce animal–vehicle collisions (AVCs) is usually based on analysis of road survey animal carcass data. This is used to identify road sections with high AVC clusters. Large mammals that are struck and die away from a road are not recorded nor considered in these analyses, reducing our understanding of the number of AVCs and the cost–benefit of road mitigation measures. AimsOur aim was to develop a method to calculate a correction factor for large mammal carcass data reported through road survey. This will improve our understanding of the magnitude and cost of AVCs. MethodCitizen scientists reported animal carcasses on walking surveys along transects parallel to the highway and reported observations using a smartphone application at three sites over a 5-year period. These data were compared with traditional road survey data. Key resultWe found that many large mammals involved in AVCs die away from the road and are, therefore, not reported in traditional road surveys. A correction factor of 2.8 for our region can be applied to road survey data to account for injury bias error in road survey carcass data. ConclusionsFor large mammals, AVCs based on road survey carcass data are underestimates. To improve information about AVCs where little is known, we recommend conducting similar research to identify a correction factor to conventionally collected road survey carcass data. ImplicationsIdentifying road mitigation sites by transportation agencies tends to focus on road sections with above-threshold AVC numbers and where cost–benefit analyses deem mitigation necessary. A correction factor improves AVC estimate accuracy, improving the identification of sites appropriate for mitigation, and, ultimately, benefitting people and wildlife by reducing risks of AVCs.

Predicting deer–vehicle collision risk across Victoria, Australia

The risk of deer–vehicle collisions (DVCs) is increasing in south-east Australia as populations of introduced deer expand rapidly. There are no investigations of the spatial and temporal patterns of DVC or predictions of where such collisions are most likely to occur. Here, we use an analytical framework to model deer distribution and vehicle movements in order to predict DVC risk across the State of Victoria. We modelled the occurrence of deer using existing occurrence records and geographic climatic variables. We estimated patterns of vehicular movements from records of average annual daily traffic and speeds. Given the low number of DVCs reported in Victoria, we used a generalised linear regression model fitted to DVCs in California, USA. The fitted model coefficients suggested high collision risk on road segments with high predicted deer occurrence, moderate traffic volume and high traffic speed. We used the California deer model to predict collision risk on Victorian roads and validated the predictions with two independent datasets of DVC records from Victoria. The California deer model performed well when comparing predictions of collision risk to the independent DVC datasets and generated plausible DVC risk predictions across the State of Victoria.