Determination of the impact of rainfall on road accidents in Thailand. Issue 2 (February 2021)

• Record Type: Journal Article
• Authors: Sangkharat, Kamolrat; Thornes, John E.; Wachiradilok, Porntip; Pope, Francis D.
• Is Part Of: Heliyon. Volume 7:Issue 2(2021)
• Publication Date: 2021-02
• Subjects: Ambulance service -- Emergency service -- Rainfall -- Road accidents; Research -- Periodicals; Medical sciences -- Periodicals; Natural history -- Periodicals; Social sciences -- Periodicals; Earth sciences -- Periodicals; Physical sciences -- Periodicals; 507.2
• DOI: 10.1016/j.heliyon.2021.e06061
• Languages: English
• ISSNs: 2405-8440

Abstract

Abstract: The World Health Organization has highlighted that the number of deaths worldwide due to road accidents increases every year. It recommends that countries improve road safety for all people by providing sustainable and safe transport systems by 2030, efforts are especially required within Low Middle-Income Countries (LMICS). This study is the first to investigate the impact of rainfall on road accidents in Thailand. Thai emergency data were collected from the National Institute for Emergency Medicine (NIEM) between 2012 to 2018. A time-series design with generalized linear model (GLM) was applied to analyse the associations between road accidents and rainfall. The results are reported using relative risk (RR) at 95% confidence intervals compared with dry days. The effects of long-term trends, seasonality, day of the weeks, public holidays and other meteorological factors were controlled in the GLM. A meta-analysis was applied to summarise the estimate effect of rain groups stratified by the Northern and Southern provinces. Findings reported a significant increase in road accidents due to high rainfall levels both in the Southern and the Northern provinces. The pooled estimate risks in the Southern provinces have higher estimated risks than the Northern provinces. Both Northern and Southern provinces showed the rain group with 10–20 mm/day having the highest pooled estimated risk with RR = 1.052, (95% CI: 1.026–1.079) and RR = 1.062, (95% CI: 1.043–1.082), respectively, while surprisingly, heavy rain with more than 20 mm/day reported a reduction of risks. Road accidents can therefore be associated with rainfall. It is recommended that rainfall is factored into ambulance forecast models and warning systems, allowing for improvements in ambulance service efficiency. Policymakers need to integrate road safety policies that reduce road accidents in wet weather. Abstract : Ambulance service; Emergency service; Rainfall, Road accidents