Risk and Quantification: A Linguistic Study

A study on the probabilistic quantification of heavy-truck crash risk under the influence of multi-factors

In order to manage and reduce a specific risk, its quantitative analysis is necessary. The key objective of this study is to illustrate the prevalence of multi-factors in fatal crashes involving heavy trucks and to quantify the crash risk under the influence of multi-factors. Data from a recent, nationally representative sample of fatal crashes was investigated to identify the risk factors contributing to crash causations and a novel risk index was obtained to develop a criterion for crash risk quantification. Then, based on the mutual information theory, the mutual dependence between risk factors was calculated to quantify the crash risk under different risk factor combinations. The results reveal that most heavy-truck fatal crashes are the result of co-occurring multi-factors rather than a single factor, and are mainly caused by simultaneous occurrence of two or three contributing factors. Moreover, crash risk increases with the increase of the number of risk factors influencing the driver. Furthermore, multi-factor interaction between certain risk factors, such as environmental and vehicular factors, makes incremental contribution to the crash risk by further increasing the crash probability. Specifically, when driver's aberrant behaviors (errors and/or violations) are exposed to both environmental and vehicular factors, driver's likelihood of being involved in a fatal crash increases significantly. This suggests that in addition to the number of risk factors, the crash risk also depends on the multi-factor interactions between different risk factors. Therefore, the effects of individual risk factors should be controlled at the outset to prevent the incremental effects of multi-factors on crash risk, in turn enabling risk minimization..

Risk Stratification in Noninvasive Respiratory Support Failure: A Narrative Review

TOPIC/CLINICAL RELEVANCE

The use of noninvasive respiratory support, including noninvasive ventilation and high-flow nasal cannula therapy, has increased over the years. Failure of noninvasive respiratory support, defined as the need for invasive mechanical ventilation, increases the mortality rate.

PURPOSE

To familiarize critical care nurses with available risk stratification assessments and identify common concepts and limitations.

CONTENT COVERED

Few risk stratification assessments are available to identify patients at risk of failure of noninvasive respiratory support. Although many studies have analyzed risk, substantial variation in study design, definitions, terminology, and outcomes have led to a wide range of findings, making clinical application difficult. Further study is needed to broaden known assessments to general patient populations, determine diagnostic accuracy during critical periods, and analyze noninvasive ventilation and high-flow nasal cannula therapy. Risk stratification could allow for better implementation of preventive strategies and patient education.

CONCLUSION

Future research opportunities include improving study design for risk stratification and implementing preventive strategies for patients requiring noninvasive respiratory support. Clinically, risk stratification can provide an opportunity to share knowledge and facilitate conversations with patients and families.

Optimal Investment in Prevention and Recovery for Mitigating Epidemic Risks

The worldwide healthcare and economic crisis caused by the COVID-19 pandemic highlights the need for a deeper understanding of investing in the mitigation of epidemic risks. To address this, we built a mathematical model to optimize investments into two types of measures for mitigating the risks of epidemic propagation: prevention/containment measures and treatment/recovery measures. The new model explicitly accounts for the characteristics of networks of individuals, as a critical element of epidemic propagation. Subsequent analysis shows that, to combat an epidemic that can cause significant negative impact, optimal investment in either category increases with a higher level of connectivity and intrinsic loss, but it is limited to a fraction of that total potential loss. However, when a fixed and limited mitigation investment is to be apportioned among the two types of measures, the optimal proportion of investment for prevention and containment increases when the investment limit goes up, and when the network connectivity decreases. Our results are consistent with existing studies and can be used to properly interpret what happened in past pandemics as well as to shed light on future and ongoing events such as COVID-19.

The Need to Reconcile Concepts that Characterize Systems Facing Threats

Desirable system performance in the face of threats has been characterized by various management concepts. Through semistructured interviews with editors of journals in the fields of emergency response and systems management, a literature review, and professional judgment, we identified nine related and often interchangeably used system performance concepts: adaptability, agility, reliability, resilience, resistance, robustness, safety, security, and sustainability. A better understanding of these concepts will allow system planners to pursue management strategies best suited to their unique system dynamics and specific objectives of good performance. We analyze expert responses and review the linguistic definitions and mathematical framing of these concepts to understand their applications. We find a lack of consensus on their usage between interview subjects, but by using the mathematical framing to enrich the linguistic definitions, we formulate comparative visualizations and propose distinct definitions for the nine concepts. We present a conceptual framing to relate the concepts for management purposes.