Epidemiology
RTIs are a large and growing public health burden and account for nearly 1.36 million deaths worldwide in 2015.
RTI was ranked as the eighth leading cause of years of life lost (YLLs) (Wang et al., 2016).
The burden of road traffic injuries, are projected to be the fourth leading cause of disease burden by 2030 (Kassebaum et al., 2016; Mathers and Loncar, 2006).
Rapid urbanization and motorization associated with rapid economic growth are some of the
reasons for the rising RTI related burden in South Asia (Lozano et al., 2013).
India has one of the highest reported mortality rates from RTI in the world (WHO-world
status report, 2015).
Number of people injured in road traffic crashes in the year 2006 was estimated to exceed
450,000(Gururaj 2008).
Road traffic crashes lead to more than 200,000 deaths and are associated with 15 million
disability-adjusted life years (Murray and Lopez 1996).
Previous studies have found traffic crashes to be under-reported in India by 5% for deaths and more than 50% for serious injuries (Gururaj 2006).
Every year nearly 85,000 persons are reported to be killed and 300,000 are injured due to
accidents on road.
An accident takes place every 3 minutes and a person killed every 10 minutes on Indian
roads and this number is continuously increasing.
According to the MoRTH 61% of the RTI fatalities occur in rural areas and it is possible that a larger number of cases go unreported on rural roads.
Risk factors
Rather than mechanical, its human factor that contribute significantly to increasing number of road accidents in India.
Alcohol’s involvement in various types of injuries, including road traffic injuries (RTIs) is well-established among emergency department (ED) patients, and has also been documented in India (Benegal, 2005). The risk of being involved in a crash increases significantly above a blood alcohol concentration (BAC) of 0.04 g/dl (WHO, Global status report 2014).
Over speeding, refusal to follow traffic rules, and reckless driving are main reasons for road accidents.
Reckless driving like use of mobile phones during driving, non-use of helmets, non-use of
seat-belts are significant contributing factors for road traffic accidents.
Driver fatigue and sleepiness also contribute to crashes.
Improper designing of roads and lack of pedestrian pavement are other contributing factors.
Only 28 countries have comprehensive road safety laws on major key risk factors like
drunken driving, speeding, and failing to use helmets, seat-belts, and child restraints.
Economic impact
High out of pocket (OOP) expenditures pose major economic burden for the affected families with one of the prior studies showing average household OOP expenses ranging from US$380 to US$780 in Bangalore (Thomas et al., 2004).
A study of 95 traffic accident cases in Chandigarh (India) showed that OOP medical
expenses averaged US$100 (Reddy et al.,2009).
A review of four studies in India estimated the cost of traffic crashes in the country to be between 0.29% and 0.69% of the gross domestic product (GDP) (Mohan 2004).
Prevention and Management
Effective road safety interventions should address the traffic system as a whole and look into interactions between vehicle, road users, and road infrastructure to identify solution.
‘Golden Hour’ – the first hour after trauma, is vital from heath system research perspective,as proper care is given during this period, the victims have a greater chance of survival and a reduction in the severity of their injury.
Injuries occur due to a combination of agent, host, vector and environment factors
Understanding injuries using this model will help in identifying factors involved in an injury.
Existing challenges
Limited data exists addressing the problem of road traffic injuries.
Existing data is of poor quality, non-representative and difficult to access, and includes a limited number of relevant variables.
The incidence and burden of RTI remains poorly measured in India
There is no national digital road traffic injury surveillance system that combines both self-report and secondary data sources to optimally predict etiological variables of RTI and predictors of poor outcomes resulting due to RTI across diverse settings.
There is clearly a need for data on RTI and it is essential for implementing preventing
strategies.