Related Experiment Video
Updated: Mar 31, 2026

An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
Using risk elasticity to prioritize risk reduction strategies for geographical areas and industry sectors
1Graduate Institute of Environmental Engineering, National Taiwan University, 71 Chou-Shan Road, Taipei 106, Taiwan.
Abstract:
The total quantity of chemical emissions does not take into account their chemical toxicity, and fails to be an accurate indicator of the potential impact on human health. The sources of released contaminants, and therefore, the potential risk, also differ based on geography. Because of the complexity of the risk, there is no integrated method to evaluate the effectiveness of risk reduction. Therefore, this study developed a method to incorporate the spatial variability of emissions into human health risk assessment to evaluate how to effectively reduce risk using risk elasticity analysis. Risk elasticity analysis, the percentage change in risk in response to the percentage change in emissions, was adopted in this study to evaluate the effectiveness and efficiency of risk reduction. The results show that the main industry sectors are different in each area, and that high emission in an area does not correspond to high risk. Decreasing the high emissions of certain sectors in an area does not result in efficient risk reduction in this area. This method can provide more holistic information for risk management, prevent the development of increased risk, and prioritize the risk reduction strategies.
Related Concept Videos
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
Design Example: Analyzing Capacity Contours for Flood Risk Assessment
Relative Risk
Applications of GIS: Disaster Management and Emergency Response
Strategies for Assessing and Addressing Confounding
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
Hazard Rate