HomeHealthHealth CareCharacteristics of road traffic mortality and distribution of healthcare resources in Thailand

Characteristics of road traffic mortality and distribution of healthcare resources in Thailand

Thailand, part of Southeast Asia, is an LMIC of over 70 million people, unevenly distributed across 77 provinces, with half of registered vehicles being motorcycles. RTIs are the second leading cause of death in Thailand16, with about 30 out of 100,000 people dying each year from these incidents, and more than 10% of these fatalities are children. Over the 11 years of this study, motorcycles were the main vehicles involved in RTMs, followed by cars, and a significant difference was seen between death rates before and during the COVID-19 pandemic. There were significant differences between the distribution of hospital resources and the rates of RTMs across Thailand.


In 2010, RTIs accounted for 334,815 deaths in Southeast Asia. RTMs were higher in middle-income countries than in low-income countries17. Thailand averaged 30.34 deaths per 100,000 population from RTIs, and neighboring LMIC Malaysia reported similar death rates of 34.5 RTMs per 100,000 population18. In contrast, death rates from RTIs in two other Southeast Asian countries, Laos and Vietnam, were 11.619 and 20.320 respectively per 100,000 inhabitants.

RTMs are a major health concern in the pediatric population. Studies have analyzed the injury rates of children involved in traffic accidents, and LMICs have been found to account for 95% of RTMs in children worldwide21. Our study showed that the mortality rate for children involved in RTIs was 19.08 per 100,000 and as high as 26 per 100,000 children. Previous studies in Thailand have reported that 80% of RTIs injured and killed were motorcyclists22. Traffic accidents were the second most common childhood injury in Thailand, with head injuries being the most common cause of death23. For adolescents aged 14–19, traffic accidents were cited as the leading cause of death24. Malaysia reported that in 2013 the leading cause of death for 10- to 24-year-old males was transport-related injuries, with injuries sustained by people traveling by car and motorcycle 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 between 6.3 and 10.3 per 100,000 inhabitants26and death rates for children < 15 years old in the United States ranged between 0.25 and 21.91 deaths per 100,000 children. Lower death rates have been associated with the availability of trauma centers in the province27.

Premature infant mortality leads to societal and economic losses, with Thailand reporting that premature mortality contributed up to 88% of lost DALYs due to RTIs. This is high compared to other countries such as Australia (73%), Iran (62%) and Serbia (57%)11. A higher share of RTMs in LMICs is due to the popularity of motorcycles, which are cheaper in these countries. Thailand experienced a loss of about USD 100 million in quality-adjusted life years or about USD 300 million worth of statistical life years from road fatalities between 2010 and 201224.

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Closure policies during the COVID-19 pandemic led to a sharp drop in traffic volume and a worldwide decline in RTIs28.29. Travel restrictions imposed during COVID-19 have significantly reduced vehicle mobility globally by more than 50%. While a relative increase in injury severity and deaths was observed, the pandemic reduced the absolute number of RTIs. Like other countries, Thailand faced lockdown policies and reduced road use along with alcohol restrictions. These road use restrictions were introduced in April 2020, when people were not allowed to leave their homes between 10 p.m. and 4 a.m. and travel between cities was banned. The associated reduction in hours of road use, along with the alcohol-free period, led to a significant drop in RTMs in Thailand during the COVID-19 pandemic. Interestingly, in 2021, about 21,000 people died from COVID-19 infection, while the number of road fatalities was about 12,000.

The average age of people who died due to RTIs was 40 years old, which falls into the working age group. Productivity losses as a result of traffic accidents are mainly concentrated in the groups aged 16 to 45 years. Road injuries and fatalities among young adults have a significant impact on the country’s GDP, as young people bear the bulk of the economic burden10.22.

Type of traffic accidents

Regions with more population did not necessarily have higher RTMs. It has been shown that the distribution of RTMs among road user groups differs from country to country. Motorcyclists account for most RTMs in Southeast Asian regions, while motorized four-wheelers account for less than 20% of traffic-related deaths6, and this is consistent 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 use a lot of two-wheelers in addition to lax law enforcement, resulting in more deaths from two-wheelers than in countries like Japan, where law enforcement is stricter4. The second most common ICD-10 diagnosis from our study of individuals injured in motor vehicle accidents was motor injury. Similarly, Laos reported that 76% of RTIs involved motorcyclists19.

RTMs in every 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 capita; in fact, the number of registered motorcycles exceeded the provinces’ population. Bangkok has about one-tenth of the country’s population with RTMs in only about one-fourth of these top two provinces. This highlights the fact that a higher number of people does not necessarily mean more road accidents. Studies have shown that less urbanized districts were associated with higher mortality than major metropolitan areas27. Other risk factors for RTMs in Southeast Asia included the type of roads, the number of male motorcyclists, driving without a license and not wearing a helmet.31.

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Distribution of hospital resources

Both hospital care and pre-hospital care have been identified as factors influencing RTMs32,33,34,35,36.37. A paper from Iran showed that pre-hospital trauma care was unevenly distributed across the country and should be adjusted to reduce the number of RTMs32. The estimated number of lives that could potentially be saved worldwide if a complete trauma system with 100% coverage were available in LMICs was estimated at 200,000 per year. Having trauma centers and efficient trauma teams has also been shown to reduce deaths from RTIs38. Death rates from motorcycle accidents in the United Arab Emirates have fallen significantly due to improved pre- and in-hospital trauma care39.

Our study further looked at the distribution of available hospital resources and found that they were unbalanced in line with RTI death rates in each province. An article from Poland reported that poor HCRs were responsible for anomalies in death rates due to road accidents in every region9 and that ORs appeared to be the least evenly distributed of all hospital resources. This is due to the extensive process required to provide suitable sites, as well as surgical teams and equipment, making it more difficult to open ORs. In contrast, doctors in Thailand were more evenly distributed than other resources, and this could be because Thailand has tried to allocate enough doctors to each province based on population. HCRs were previously allocated based on the number of people in each county. Therefore, Bangkok, which had the most population, had the most HCRs per 100,000 inhabitants. Physicians and nurses could be reassigned appropriately, and the provision of other facilities, such as ORs and ICUs, could be integrated into health care policies, taking into account the numbers of RTMs in each province and consideration for trauma teams and facilities.

Associated Factors

Gross National Income (GNI), urban speed limits, road quality and regular road infrastructure inspections all appear to be influential factors in the number of RTMs40,41,42,43.44. Countries with high GNI per capita have fewer deaths per 100,000 population, even though they have more vehicles, while countries with low GNI per capita have higher death rates per 100,000 population, despite having fewer vehicles4.

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It has been repeatedly shown that road injuries 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 found to correlate with RTMs in this study were income, number of registered vehicles and amount of precipitation. RTIs in Thailand have been shown to move in the same direction as the country’s economy45.

Precipitation amounts did not correlate with RTMs in our study, unlike another study previously conducted in Thailand that found a significant increase in road accidents due to heavy rainfall. These conflicting results were probably due to differences in data collection and analysis: our study calculated the amount of rainfall throughout the year and found no correlation with RTMs, while the previous study grouped different rainfall intensities as measured by daily precipitation amounts46.

Strong and weak points

One of the main strengths of this study was that it provided the largest data available across all 77 provinces in Thailand from a variety of reliable government sources and collected it over an 11-year period. We have also divided the population into adults and children so that Thailand can have data on different age groups, which will be helpful when allocating medical staff, as children and adults require different types of medical care.

Another strength of this study is that we showed which hospital resources were most unevenly distributed to help prioritize which resources needed to be adjusted first.

The limitations of this article were that while we had the number of RTMs for each province, we did not know the exact location where the accidents occurred; therefore we could not assess factors such as road types that have been shown to be associated with RTMs. We also had no details on the level of alcohol consumption or helmet use in the reported RTMs, both of which affect mortality. We reported RTM rates for children, but did not subgroup physicians into pediatricians and emergency department physicians, so we could not determine how effectively trauma cases are treated in each province. The times when the accidents occurred were not available and we did not divide the period into weekdays, weekends and long holidays, so we could not analyze these risk factors of RTMs as this was not within the scope of the study.



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