Thailand, part of Southeast Asia, is an LMIC with over 70 million people spread unevenly across 77 provinces, with half of registered vehicles being motorcycles. RTIs are the second leading cause of death in Thailand16, with approximately 30 out of 100,000 people dying from these incidents every year, and children accounting for over 10% of these fatalities. Throughout the 11 years of this study, motorcycles were the main vehicles involved in RTMs, followed by cars, and a significant difference was seen between mortality rates before and during the COVID-19 pandemic. There were significant disparities between the distribution of hospital resources and rates of RTMs across Thailand.
In 2010, RTIs accounted for 334,815 deaths in South-East Asia. RTMs were higher in middle-income nations than in low-income countries17. Thailand had on average 30.34 deaths per 100,000 population from RTIs, and neighbouring LMIC Malaysia reported similar mortality rates of 34.5 RTMs per 100,000 population18. In contrast, mortality rates from RTIs in two other Southeast Asian countries, Laos and Vietnam, were 11.619 and 20.320 per 100,000 population respectively.
RTMs are a significant health concern in the paediatric population. Studies have analysed injury rates of children involved in road traffic accidents, and LMICs have been found to account for 95% of RTMs in children globally21. Our study showed that the mortality rate for children involved in RTIs was 19.08 per 100,000 and rose to as high as 26 per 100,000 children. Previous studies in Thailand have reported that 80% of the injured and dead from RTIs were motorcyclists22. Traffic accidents were the second most common paediatric injury in Thailand, with head injury being the most common cause of death23. For adolescents aged 14–19, road accidents were reported as the number one cause of death24. Malaysia reported that in 2013, the main cause of death for 10- to 24-year-old males was transport-related injury, with those sustained by people traveling by car and motorbike responsible for 20 and 5.5 per 100,000 deaths from all causes respectively25. In stark contrast, a study from Australia, a high-income country, showed RTI mortality rates at between 6.3 and 10.3 per 100,000 population26, and mortality rates for children < 15 years old in the United States ranged between 0.25 and 21.91 deaths per 100,000 children. Decreased mortality rates have been associated with the availability of trauma centers in the county27.
Premature childhood deaths result in societal as well as economic losses, with Thailand reporting that premature mortality contributed up to 88% of DALYs lost due to RTIs. This is high compared to other countries such as Australia (73%), Iran (62%), and Serbia (57%)11. Higher proportions of RTMs in LMICs result from the popularity of motorcycles, which are more affordable in these countries. Thailand was faced with a loss of about 100 million USD of quality-adjusted life years or approximately 300 million USD of value of statistical life years from traffic mortalities between 2010 and 201224.
Lockdown policies during the COVID-19 pandemic led to a sharp drop in traffic volume and a global decline in RTIs28,29. Travel restrictions imposed during COVID-19 significantly reduced vehicle mobility by more than 50% worldwide. Though relative increases in severity of injury and numbers of deaths were observed, the pandemic reduced the absolute number of RTIs. Like other countries, Thailand faced lockdown policies and decreased road usage together with alcohol restrictions. These road usage restrictions were implemented in April 2020, when people were not allowed to leave their homes between 10 PM and 4 AM, and traveling between cities was prohibited. The attendant decrease in the number of hours of road usage, along with the alcohol-free period, led to a significant decline in RTMs in Thailand during the COVID-19 pandemic. Interestingly, in 2021, around 21,000 people died from COVID-19 infection, while deaths form traffic accidents numbered approximately 12,000.
The average age of people dying as a result of RTIs was 40 years old, which is in the working age group. Productivity losses due to road traffic accidents are mainly concentrated in the 16- to 45-year-old groups. Road traffic injuries and fatalities in young adults significantly affect the nation’s GDP since younger people bear the largest share of the economic burden10,22.
Type of road accidents
Regions that were more populated did not necessarily have higher RTMs. Distribution of RTMs by road user groups has been shown to vary across countries. Motorcyclists account for most of the RTMs in Southeast Asian regions, while motorised four-wheelers constitute less than 20% of traffic-related mortalities6, and this in keeping with the findings of our study. Eighty-eight percent of motorized 2–3 wheelers are found in LMICs, with 75% in Southeast Asia30. Thailand was noted to have a high usage of 2-wheelers in addition to lax law enforcement, causing higher 2-wheeler deaths than in countries like Japan where law enforcement is more rigorous4. The second most common ICD-10 diagnosis from our study of persons injured in motor-vehicle accidents was specified as motorcycle injury. Similarly, Laos reported that 76% of RTIs involved motorcyclists19.
RTMs across each province
Rayong and Chonburi were the two provinces with the highest RTMs at 62 and 49 per 100,000 population, possibly because they had the highest proportion of motorcycles per population; in fact, the number of registered motorcycles exceeded the population of the provinces. Bangkok has about a tenth of the country’s population with RTMs at only about a fourth of these top two provinces. This highlights the fact that higher numbers of people does not necessarily mean more road accidents. Studies have found that less-urbanised districts were associated with higher mortality than large metropolitan areas27. Other risk factors involved in RTMs in Southeast Asia were type of roads, number of male motorcycle drivers, driving without a driver’s license, and non-use of helmets31.
Distribution of hospital resources
Both in-hospital and pre-hospital care have been identified as factors affecting RTMs32,33,34,35,36,37. A paper from Iran showed that pre-hospital trauma care was dispensed unequally across the nation and should be adjusted to reduce the number of RTMs32. The estimated number of lives that could potentially be saved globally if a complete trauma system with 100% coverage was available in LMICs was estimated at 200,000 per year. Having trauma centres and efficient trauma teams has also been shown to reduce deaths from RTIs38. Mortality rates from motorcycle injuries in the United Arab Emirates dropped significantly due to improved pre-hospital and in-hospital trauma care39.
Our study looked further into the distribution of available hospital resources and found that they were not balanced in accordance with mortality rates from RTIs in each province. A paper from Poland reported that poor HCRs were responsible for anomalies in mortality rates due to traffic accidents in each region9 and that ORs were found to be the least equally distributed out of all the hospital resources. This is due to the extensive process required to provide appropriate venues, as well as surgical teams and equipment, making it harder to open ORs. In contrast, physicians in Thailand were more equally distributed than other resources, and this could be because Thailand has been trying to allocate enough doctors to each province according to its population. HCRs were previously allocated according to the number of people in each province, which was why Bangkok, which had the highest population, had the most HCRs per 100,000 population. Physicians and nurses could be reallocated appropriately, and provision of other facilities, such as ORs and ICUs, could be integrated into healthcare policies, while taking into account the rates of RTMs in each province and focusing attention on trauma teams and facilities.
Gross national income (GNI), urban speed limits, road quality, and regular road infrastructure inspections have all been shown to be influential factors in the rate of RTMs40,41,42,43,44. Countries with high GNI per capita have fewer deaths per 100,000 population even though they have higher numbers of vehicles while nations with low GNI per capita have higher rates of deaths per 100,000 population despite having fewer vehicles4.
Traffic injuries have repeatedly been shown to follow the trends of economic growth. Globally, a drastic increase in the number of vehicles led to RTMs reaching 135 cases per 100 vehicles in the year 2000, but this fell to 64 cases per 100 vehicles in 201631. Other factors that were found from this study to correlate with RTMs were, income, number of registered vehicles, and amount of precipitation. RTIs in Thailand have been shown to go in the same direction as the nation’s economy45.
Amounts of precipitation did not correlate with RTMs in our study, in contrast to another study previously conducted in Thailand which found a significant increase in road accidents resulting from high rainfall. These contradictory results were probably due to differences in data collection and analysis: our study calculated the amount of rain throughout the year and found no correlation with RTMs while the previous study grouped different rain intensities measured by daily rates of precipitation46.
Strengths and weaknesses
One of the main strengths of this study was that it provided the largest data available in all 77 provinces in Thailand from various reliable governmental resources and collected them over a period of 11 years. We also divided the population into adults and children so that Thailand could have data on different age groups, which will be helpful when allocating medical personnel, since children and adults require different types of medical attention.
Another strength of this study is that we showed which hospital resources were the most unequally distributed in order to help prioritise which resources needed to be adjusted first.
The limitations of this paper were that although we had the number of RTMs of each province, we did not know the exact location where the accidents occurred; therefore, we could not assess factors such as road types which have shown to be associated with RTMs. We also did not have details on levels of alcohol consumption or helmet usage in the reported RTMs, both of which affect mortality. We reported RTM rates for children but did not sub-group physicians into paediatricians and emergency department physicians, so that we could not establish how effectively trauma cases are handled in each province. The times at which the accidents occurred were not available, and we did not divide the period into weekdays, weekends, and long holidays, so we were not able to analyse these risk factors of RTMs, as this was not within the scope of the study.