高温热浪致死风险的人群和城市分异及保险费率厘定的研究

doi:10.12006/j.issn.1673-1719.2018.046

摘要/Abstract

摘要：

在全球变暖背景下,高温热浪事件在世界各地频繁发生且大大加剧了人群致死的风险。基于3个研究地区（南京、广州和重庆）1951—2015年的逐日气象数据和2007—2013年逐日死亡数据,首先设计了热浪强度指数来量化热浪特征;其次采用分布滞后非线性模型构建高温热浪灾害下人群的脆弱性模型;最后采用蒙特卡洛仿真方法模拟随机高温热浪事件,并在此基础上开展概率风险评估与高温热浪生命保险费率的厘定。研究发现：老年人的高温热浪死亡风险与对应的费率水平是年轻人的9~28倍;其中,高温热浪费率水平与社会经济发展水平呈反比,即经济发展水平较高的地区费率水平较低。该研究成果为指数生命/健康保险产品的研发,为政府采取综合性的风险管理措施以减少公众健康风险等提供了一定的借鉴和参考。

关键词: 高温热浪, 死亡风险, 分布滞后非线性模型（DLNM), 指数保险

Abstract:

Under the background of global warming, heat wave events have frequently occurred around the world and increased the mortality risk greatly. Based on the daily meteorological data from 1951 to 2015 and daily mortality data from 2007 to 2013 in three cities (Nanjing, Chongqing, Guangzhou), a heat wave intensity index was firstly designed to quantify the heat waves, and then a distributed lag non-linear model (DLNM) was used to develop the vulnerability models of population under the heat wave events. Finally, Monte Carlo simulation method was run to assess the probabilistic heat wave risk and rated the premiums for heat wave life insurance. The results show that, the heat wave mortality risks and pure premium rates for the elder are both 9 to 28 times that of the young and the pure premium rates are inversely proportional to the level of socioeconomic development. The results in this study can provide guidance for developing weather index-based individual life/health insurance products and give support for the government to adopt comprehensive risk management measures to reduce public health risks.

Key words: Heat wave, Mortality risk, Distributed lag non-linear model (DLNM), Index insurance

张领雁,张朝,侯斌. 高温热浪致死风险的人群和城市分异及保险费率厘定的研究[J]. 气候变化研究进展, 2018, 14(5): 475-484.

Ling-Yan ZHANG,Zhao ZHANG,Bin HOU. Mortality risk of heat wave between different groups and cities and the corresponding insurance ratemaking[J]. Climate Change Research, 2018, 14(5): 475-484.

图/表 10

图1 研究区域

Fig. 1 Location of the study areas

Table 1 Summary mortality, weather statistics and social-economic data from 2007 to 2013 in the study areas

图2 高温热浪生命险费率厘定技术流程

Fig. 2 Technical flow chart of ratemaking for heat wave life insurance

Table 2 The localized heat wave definition and the parameters of the probability distribution for heat wave in each study area

图3 各研究区1951—2015年热浪的年频次和HWII特征

Fig. 3 Annual frequency and HWII of heat waves identified from 1951 to 2015 in each study area: (a) box plot for annul frequency of heat waves, (b) box plot for intensity index of heat waves. (The boxes present the 25- to 75-percentile, whiskers present the 10- to 90-percentile, hollow square and thick dash in boxes are mean and median values, and black dots are outliers)

图4 各研究区1951—2015年热浪年频次与年平均HWII的时间变化

Fig. 4 Annual frequency and annual average intensity index of heat waves from 1951 to 2015 in each study area

图5 各研究区域分年龄组人群在高温热浪事件下的脆弱性曲线

Fig. 5 Vulnerability curves for different age groups under heat wave events in each study area (the shaded areas represent 95% confidence intervals)

图6 各研究区域分年龄组人群随机1万年保额损失率的超越概率曲线

Fig. 6 Exceeding probability curves of stochastic 10000 years’ LCR for different age groups in each study area (The gray areas represent 95% confidence intervals)

Table 3 Pure premiums and risk premium loadings under different return periods for different age groups in each study area (The numbers in parentheses represent 95% confidence intervals)

图7 各研究区域分年龄组人群的纯费率水平与2007—2013年平均人均GDP水平

Fig. 7 Pure premiums for different age groups and average per capita GDP from 2007 to 2013 in each study area

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