Chongqing Economic and Social Development Research Institute, Chongqing 400041, China.
Key Laboratory of Mountain Hazards and Earth Surface Processes, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610041, China.
Int J Environ Res Public Health. 2022 Dec 7;19(24):16393. doi: 10.3390/ijerph192416393.
Understanding disaster risk perception is vital for community-based disaster risk reduction (DRR). This study was set to investigate the correlations between disaster risk perception and the population at risk. To address this research question, the current study conducted an interdisciplinary approach: a household survey for measuring variables and constructed an Agent-based model for simulating the population at risk. Therefore, two correlations were defined, (1) between risk perception and willingness to evacuate, and (2) between willingness to evacuate and the population at risk. The willingness to evacuate was adopted as a mediator to determine the relationship between risk perception and the population at risk. The results show that the residents generally have a higher risk perception and willingness to evacuate because the study area frequently suffered from debris flow and flash floods. A positive correlation was found between risk perception and willingness to evacuate, and a negative correlation to the population at risk. However, a marginal effect was observed when raising public risk perception to reduce the number of the population at risk. This study provides an interdisciplinary approach to measuring disaster risk perception at the community level and helps policymakers select the most effective ways to reduce the population at risk.
了解灾害风险认知对于基于社区的灾害风险管理（DRR）至关重要。本研究旨在调查灾害风险认知与受灾人口之间的相关性。为了解决这个研究问题，本研究采用了跨学科的方法：通过家庭调查来测量变量，并构建了一个基于代理的模型来模拟受灾人口。因此，定义了两个相关性，（1）风险认知与撤离意愿之间的相关性，以及（2）撤离意愿与受灾人口之间的相关性。将撤离意愿作为中介来确定风险认知与受灾人口之间的关系。结果表明，由于研究区域经常遭受泥石流和山洪暴发，居民普遍具有更高的风险认知和撤离意愿。风险认知与撤离意愿之间存在正相关关系，与受灾人口之间存在负相关关系。然而，当提高公众风险认知以减少受灾人口数量时，观察到了一个边际效应。本研究提供了一种跨学科的方法来测量社区层面的灾害风险认知，有助于决策者选择最有效的方法来减少受灾人口。
