您的位置:山东大学 -> 科技期刊社 -> 《山东大学学报(医学版)》

山东大学学报 (医学版) ›› 2023, Vol. 61 ›› Issue (6): 103-108.doi: 10.6040/j.issn.1671-7554.0.2022.1124

• 公共卫生与和管理学 • 上一篇    

基于“中暑”百度搜索指数评价济南市高温热浪健康风险预警模型

刘晶1,2,陈晨2,王彦文2,崔亮亮3,韩丹丹1,李湉湉2   

  1. 1.河北省公共卫生安全重点实验室 河北大学公共卫生学院, 河北 保定 071002;2.中国疾病预防控制中心环境与人群健康重点实验室 中国疾病预防控制中心环境与健康相关产品安全所, 北京 100021;3.济南市疾病预防控制中心环境健康所, 山东 济南 250021
  • 发布日期:2023-06-06
  • 通讯作者: 韩丹丹. E-mail:hdd@hbu.edu.cn李湉湉. E-mail:litiantian@nieh.chinacdc.cn
  • 基金资助:
    国家自然科学基金重大研究计划项目(92143202);中国疾病预防控制中心环境所青年科学基金(2020YSRF_02)

Evaluation on heat-health risk warning in Jinan based on Baidu heat stroke search index

LIU Jing1,2, CHEN Chen2, WANG Yanwen2, CUI Liangliang3, HAN Dandan1, LI Tiantian2   

  1. 1. Key Laboratory of Public Health Safety of Hebei Province, College of Public Health, Hebei University, Baoding 071002, Hebei, China;
    2. China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China;
    3. Department of Environmental Health, Jinan Center for Disease Control and Prevention, Jinan 250021, Shandong, China
  • Published:2023-06-06

摘要: 目的 基于“中暑”百度搜索指数(HSSI)评价济南市高温热浪健康风险预警(HHRW)模型的适用性,为其推广应用提供科学依据。 方法 收集济南市2018至2020年夏季(6~9月)HSSI和气象因素数据。采用广义线性模型分析预警等级分布与HSSI的关联性(β值),探讨各预警等级下的中暑发生风险。 结果 HHRW预警中重点关注、黄色、橙色、红色预警的频数分别为170、17、12、5。重点关注阶段评价结果显示,相较于一般关注,重点关注及以上阶段的β值为77.4(95%CI: 58.6~96.2)。预警阶段评价结果显示,相较于一般关注,重点关注和预警阶段的β值分别为69.7(95%CI: 55.0~84.4)、232.1(95%CI: 207.2~257.1)。三级预警评价结果显示,相较于一般关注,黄色橙色红色预警的β值分别为193.4(95%CI: 164.8~221.9)、254.2(95%CI: 220.6~287.8)、346.1(95%CI: 296.6~395.6)。HHRW与中国气象局的高温预警(HTW)的比较结果显示,HSSI与HHRW预警等级分布之间呈显著关联,而与HTW预警之间无显著关联。 结论 HHRW预警等级分布与中暑发生风险具有良好的递增关系,提示以死亡风险为核心建立的预警分级模式也适用于夏季中暑发生风险的预警。

关键词: 中暑, 百度搜索指数, 热浪, 预警

Abstract: Objective To evaluate the sensitivity of the heat-health risk warning(HHRW)model in Jinan based on the heat stroke search index(HSSI), and to provide scientific basis for its popularization and application. Methods The HSSI and meteorological data during summer(June to September)of 2018 to 2020 in Jinan were collected. The association(β value)between the distribution of warning ranks and HSSI was analyzed with generalized linear model, and the occurrence of heat stroke in different warning levels was explored. Results In the HHRW model, the frequency of key concern, yellow, orange and red warning levels were 170, 17, 12 and 5, respectively. The evaluation results of the key concern level showed that, the β value of key concern level and above was 77.4(95%CI: 58.6-96.2). The evaluation results of the warning level showed that, the β value of key concern level and warning level were 69.7(95%CI: 55.0-84.4)and 232.1(95%CI: 207.2-257.1), respectively. The evaluation results of the three-level warning showed that, the β value of yellow, orange and red warning levels were 193.4(95%CI: 164.8-221.9), 254.2(95%CI: 220.6-287.8)and 346.1(95%CI: 296.6-395.6), respectively. The comparison between HHRW and high temperature warning(HTW)of the China Meteorological Administration showed a significant association between HSSI and HHRW, but not between HSSI and HTW. Conclusion There was a good increasing relationship between the distribution of HHRW warning ranks and the occurrence of heat stroke, suggesting that the HHRW model based on death risk is also suitable for heat stroke risk warning during summer.

Key words: Heat stroke, Baidu search index, Heatwave, Early warning

中图分类号: 

  • R122.2
[1] Robine JM, Cheung SLK, Le RS, et al. Death toll exceeded 70 000 in Europe during the summer of 2003 [J]. CR Biol, 2008, 331(2): 171-178.
[2] World Health Organization. Quantitative risk assessment of the effects of climate change on selected causes of death, 2030s and 2050s [M]. Genève: World Health Organization, 2014.
[3] Li Y, Li C, Luo S, et al. Impacts of extremely high temperature and heatwave on heatstroke in Chongqing, China [J]. Environ Sci Pollut Res Int, 2017, 24(9): 8534-8540.
[4] World Meteorological Organization and World Health Organization. Heatwaves and health: guidance on warning-system development [M]. Genève: World Meteorological Organization and World Health Organization, 2015.
[5] IPCC. Climate change 2014: impacts, adaptation, and vulnerability. part a: global and sectoral aspects. working group II to the fifth assessment report of the intergovernmental panel on climate change [M]. Cambridge and New York: Cambridge University Press, 2014.
[6] 陈晨, 刘晶, 仲宇, 等. 基于人群健康风险的高温热浪预警研究进展[J]. 中华预防医学杂志, 2022, 56(10): 1461-1466. CHEN Chen, LIU Jing, ZHONG Yu, et al. A review on heat-wave early warning based on population health risk [J]. Chinese Journal of Preventive Medicine, 2022, 56(10): 1461-1466.
[7] Casanueva A, Burgstall A, Kotlarski S, et al. Overview of existing heat-health warning systems in Europe [J]. Int J Environ Res Public Health, 2019, 16(15): 2657. doi: 10.3390/ijerph16152657.
[8] Toloo G, FitzGerald G, Aitken P, et al. Evaluating the effectiveness of heat warning systems: systematic review of epidemiological evidence [J]. Int J Public Health, 2013, 58(5): 667-681.
[9] 中国气象局气候变化中心. 中国气候变化蓝皮书(2021)[M]. 北京: 科学出版社, 2021.
[10] Li T, Chen C, Cai W. The global need for smart heat-health warning systems [J]. Lancet, 2022, 400(10362): 1511-1512.
[11] 济南市疾病预防控制中心环境健康所(地方病管理办公室). 市疾控中心建成高温热浪健康风险预警预测平台并向公众发布 [EB/OL].(2021-08-26)[2022-08-21]. http://www.jncdc.cn/index.php?m=content&c=index&a=show&catid=659&id=25705.
[12] Li T, Ding F, Sun Q, et al. Heat stroke internet searches can be a new heatwave health warning surveillance indicator [J]. Sci Rep, 2016, 6: 37294. doi: 10.1038/srep37294.
[13] Wang Y, Song Q, Du Y, et al. A random forest model to predict heatstroke occurrence for heatwave in China [J]. Sci Total Environ, 2018, 650(Pt2):3048-3053.
[14] Han Q, Liu Z, Jia J, et al. Web-based data to quantify meteorological and geographical effects on heat stroke: case study in China [J]. Geohealth, 2022, 6(8): e2022GH000587. doi: 10.1029/2022GH000587.
[15] 中国气象科普网. 高温预警信号及防御指南 [EB/OL].(2021-02-01)[2022-08-21]. http://www.qxkp.net/qxbk/yjxhjfyzn/202103/t20210312_2948454.html.
[16] 李传玺, 刘起勇, 马伟. 广州市极端降水事件对不同特征人群登革热发病的影响 [J]. 山东大学学报(医学版), 2021, 59(12): 151-157. LI Chuanxi, LIU Qiyong, MA Wei. Effects of extreme precipitation events on the incidence of dengue fever in different characteristic populations in Guangzhou [J]. Journal of Shandong University(Health Sciences), 2021, 59(12): 151-157.
[17] 薛莉, 胡文琦, 魏然, 等. 2011~2013年高温热浪对苍南县高血压门诊就诊量的影响 [J]. 山东大学学报(医学版), 2018, 56(8): 63-69. XUE Li, HU Wenqi, WEI Ran, et al. Impacts of heatwaves on the number of hypertensive outpatient visits in Cangnan County during 2011 and 2013 [J]. Journal of Shandong University(Health Sciences), 2018, 56(8): 63-69.
[18] Kalkstein LS, Jamason PF, Greene JS, et al. The Philadelphia hot weather-health watch/warning system: development and application, summer 1995 [J]. Bull Am Meteorol Soc, 1996, 77(7): 1519-1528.
[19] Public Health England. Heatwave plan for England [M]. London: Public Health England, 2019.
[20] Pascal M, Laaidi K, Ledrans M, et al. Frances heat health watch warning system [J]. Int J Biometeorol, 2006, 50(3): 144-153.
[21] Mancha CL. Plan nacional de actuaciones preventivas de los efectos del exceso de temperaturas sobre la salud [M]. CastillaLa Mancha: Consejería de Salud y Bienestar Social Dirección General de Salud Pública, 2010.
[22] IPCC. Climate change 2022: impacts, adaptation, and vulnerability. contribution of working group II to the sixth assessment report of the intergovernmental panel on climate change [M]. Cambridge and New York: Cambridge University Press, 2022.
[1] 徐小明,孔裔婷,刘川,明英,况利. 青少年和年轻成人自杀预警系统研究进展[J]. 山东大学学报 (医学版), 2022, 60(2): 69-74.
[2] 李湉湉,王情,孙庆华. 加强环境健康风险预警研究,推动风险预警公共卫生服务[J]. 山东大学学报 (医学版), 2021, 59(12): 1-5.
[3] 陆开来,班婕,费鲜芸,周珍,李湉湉. 2005~2017年中国热浪事件及人口暴露水平趋势[J]. 山东大学学报 (医学版), 2021, 59(12): 158-164.
[4] 黄存瑞,邓诗舟. 气候变化下的新发传染病风险[J]. 山东大学学报 (医学版), 2020, 58(10): 7-12.
[5] 石婉荧,班婕,杜宗豪,王琼,刘霞,姜超,韩联宇,王锐,崔亮亮. 济南市三城区居民热浪健康风险感知水平及影响因素[J]. 山东大学学报 (医学版), 2019, 57(1): 107-113.
[6] 薛莉,胡文琦,魏然,张安然,林君芬,马伟. 2011~2013年高温热浪对苍南县高血压门诊就诊量的影响[J]. 山东大学学报 (医学版), 2018, 56(8): 63-69.
[7] 张安然,胡文琦,李佳蔚,魏然,马伟. 热浪对居民循环系统疾病死亡影响的病例交叉研究[J]. 山东大学学报 (医学版), 2018, 56(8): 56-62.
[8] 黄存瑞,何依伶,马锐,苏亚男. 高温热浪的健康效应:从影响评估到应对策略[J]. 山东大学学报 (医学版), 2018, 56(8): 14-20.
[9] 韩京,张军,周林,房巧玲,刘守钦,张济,张颖. 极端气温对济南市心脑血管疾病死亡的影响[J]. 山东大学学报(医学版), 2017, 55(11): 71-74.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!