Determination of the impact of rainfall on road accidents in Thailand.
Determination of the impact of rainfall on road accidents in Thailand.
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DOI：
10.1016/j.heliyon.2021.e06061
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发表时间：
2021-03
期刊：
影响因子：
4
通讯作者：
Pope FD
中科院分区：
文献类型：
--
作者：
Sangkharat K;Thornes JE;Wachiradilok P;Pope FD
世界卫生组织强调，全世界因道路事故死亡的人数每年都在增加。它建议各国到2030年通过提供可持续和安全的交通系统来改善所有人的道路安全，特别是在中低收入国家（LMICS）内。这项研究是第一次调查降雨对泰国道路交通事故的影响。泰国的紧急数据是从2012年至2018年期间的国家急诊医学研究所（NIEM）收集的。采用广义线性模型（GLM）的时间序列设计，分析了道路交通事故与降雨量之间的关系。结果报告使用相对风险（RR）在95%置信区间与干燥天相比。长期趋势、季节性、星期几、公共假日和其他气象因素的影响在GLM中得到控制。采用荟萃分析总结了按北方和南方省份分层的雨组的估计效果。调查结果显示，由于南部和北方省份降雨量大，道路事故显着增加。南方各省的合并估计风险比北方各省的估计风险高。北方和南方省份均显示，降雨量为10-20 mm/d的降雨组具有最高的合并估计风险，RR = 1.052，（95% CI：1.026-1.079）和RR = 1.062，（95% CI：1.043-1.082），而令人惊讶的是，降雨量超过20 mm/d的大雨报告了风险降低。因此，道路事故可能与降雨有关。建议将降雨因素纳入救护车预测模型和警报系统，以提高救护车服务效率。决策者需要整合道路安全政策，减少潮湿天气下的道路事故。救护车服务;紧急服务;降雨，交通事故
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. Ambulance service; Emergency service; Rainfall, Road accidents
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