The impact of frailty on mortality in non-surgical head and neck cancer treatment: Shifting the clinical paradigm

OBJECTIVE

Compare survival of head and neck cancer (HNC) patients treated with surgical or non-surgical management according to frailty, quantify frailty with the Risk Analysis Index (RAI), a validated 14-item instrument.

MATERIALS AND METHODS

Prospective cohort study of newly diagnosed HNC patients (≥18 years) who had frailty assessment from April 13, 2016 to September 30, 2016. Primary outcome was overall survival at 1- and 3-years. Cox proportional hazard models were utilized to examine mortality with predictor variables. Adjusted and unadjusted (Kaplan-Meier) survival curves stratified by either RAI scores or treatment modality were plotted. Kruskal-Wallis and likelihood ratio chi-square tests were used for comparing clinicodemographic variables.

RESULTS

Of 165 patients, 54 (32.7%) were managed non-surgically, 49 (29.7%) were treated with definitive surgery only, and 62 (37.6%) were treated with multimodality (surgery + adjuvant) therapy. Among the full cohort and subgroup analysis of the frail/very frail (RAI ≥ 37), non-surgical patients had worse or similar 3-year survival than those treated with surgery +/- adjuvant therapy. Multivariable Cox proportional hazard models demonstrate that frail patients treated non-surgically experienced worse survival than their counterparts treated with surgery (HR = 2.50, p = 0.015, 95% CI: 1.19, 5.23) or multimodality therapy (HR = 3.91, p < 0.001, 95% CI: 1.94-7.89).

CONCLUSION

Across all levels of frailty, long term survival of HNC patients treated without surgery is either worse than or like those treated with surgery. These findings (1) challenge current practices of steering patients "too frail for surgery" towards non-surgical, "non-invasive" therapy, and (2) suggest equipoise warranting randomized trials to clarify treatment of frail patients.

R.Graph: A new risk-based causal reasoning and its application to COVID-19 risk analysis

Various unexpected, low-probability events can have short or long-term effects on organizations and the global economy. Hence there is a need for appropriate risk management practices within organizations to increase their readiness and resiliency, especially if an event may lead to a series of irreversible consequences. One of the main aspects of risk management is to analyze the levels of change and risk in critical variables which the organization's survival depends on. In these cases, an awareness of risks provides a practical plan for organizational managers to reduce/avoid them. Various risk analysis methods aim at analyzing the interactions of multiple risk factors within a specific problem. This paper develops a new method of variability and risk analysis, termed R.Graph, to examine the effects of a chain of possible risk factors on multiple variables. Additionally, different configurations of risk analysis are modeled, including acceptable risk, analysis of maximum and minimum risks, factor importance, and sensitivity analysis. This new method's effectiveness is evaluated via a practical analysis of the economic consequences of new Coronavirus in the electricity industry.

Dynamics of antibiotics and antibiotic resistance genes in four types of kitchen waste composting processes

Kitchen waste might be a potential source of antibiotics and antibiotic resistance genes. Composting is recognized as an effective way for kitchen waste disposal. However, the effects of different kitchen waste composting types on the removal of antibiotics and antibiotic resistance genes haven't been systematically studied. In this study, the dynamics of antibiotics and antibiotic resistance genes from kitchen waste of four composting processes were compared. Results showed that although kitchen waste was composted, it remained an underestimated source of antibiotics (25.9-207.3 μg/kg dry weight) and antibiotic resistance genes (10¹²-10¹⁷ copies/kg dry weight). Dynamic composting processes (i.e., dynamic pile composting and mechanical composting) decreased the antibiotic removal efficiency and increased the abundance of some antibiotic resistance genes (5.35-8534.7% enrichment). Partial least-squares path model analysis showed that mobile genetic elements played a dominant role in driving antibiotic resistance genes dynamics. Furthermore, redundancy analysis revealed that temperature, pH, and water content considerably affected the removal of antibiotics and mobile genetic elements. This study provides further insights into exploring the effective strategies in minimizing the risk of antibiotic resistance from kitchen waste via composting process.

Assessment and validation of the Community Maternal Danger Score algorithm

Background

High rates of maternal mortality in low-and-middle-income countries (LMICs) are associated with the lack of skilled birth attendants (SBAs) at delivery. Risk analysis tools may be useful to identify pregnant women who are at risk of mortality in LMICs. We sought to develop and validate a low-cost maternal risk tool, the Community Maternal Danger Score (CMDS), which is designed to identify pregnant women who need an SBA at delivery.

Methods

To design the CMDS algorithm, an initial scoping review was conducted to identify predictors of the need for an SBA. Medical records of women who delivered at the Federal Medical Centre in Makurdi, Nigeria (2019–2020) were examined for predictors identified from the literature review. Outcomes associated with the need for an SBA were recorded: caesarean section, postpartum hemorrhage, eclampsia, and sepsis. A maternal mortality ratio (MMR) was determined. Multivariate logistic regression analysis and area under the curve (AUC) were used to assess the predictive ability of the CMDS algorithm.

Results

Seven factors from the literature predicted the need for an SBA: age (under 20 years of age or 35 and older), parity (nulliparity or grand-multiparity), BMI (underweight or overweight), fundal height (less than 35 cm or 40 cm and over), adverse obstetrical history, signs of pre-eclampsia, and co-existing medical conditions. These factors were recorded in 589 women of whom 67% required an SBA (n = 396) and 1% died (n = 7). The MMR was 1189 per 100,000 (95% CI 478–2449). Signs of pre-eclampsia, obstetrical history, and co-existing conditions were associated with the need for an SBA. Age was found to interact with parity, suggesting that the CMDS requires adjustment to indicate higher risk among younger multigravida and older primigravida women. The CMDS algorithm had an AUC of 0.73 (95% CI 0.69–0.77) for predicting whether women required an SBA, and an AUC of 0.85 (95% CI 0.67–1.00) for in-hospital mortality.

Conclusions

The CMDS is a low-cost evidence-based tool that uses 7 risk factors assessed on 589 women from Makurdi. Non-specialist health workers can use the CMDS to standardize assessment and encourage pregnant women to seek an SBA in preparation for delivery, thus improving care in countries with high rates of maternal mortality.

A cyber warfare perspective on risks related to health IoT devices and contact tracing

The wide use of IT resources to assess and manage the recent COVID-19 pandemic allows to increase the effectiveness of the countermeasures and the pervasiveness of monitoring and prevention. Unfortunately, the literature reports that IoT devices, a widely adopted technology for these applications, are characterized by security vulnerabilities that are difficult to manage at the state level. Comparable problems exist for related technologies that leverage smartphones, such as contact tracing applications, and non-medical health monitoring devices. In analogous situations, these vulnerabilities may be exploited in the cyber domain to overload the crisis management systems with false alarms and to interfere with the interests of target countries, with consequences on their economy and their political equilibria. In this paper we analyze the potential threat to an example subsystem to show how these influences may impact it and evaluate a possible consequence.

Risk analysis for radiotherapy at the Universitätsklinikum Erlangen

PURPOSE

Risk analysis is required by various laws and regulations in Germany and has an impact on each department of a large clinic. We provide an overview of the relevant laws and regulations in Germany and present the technical and organizational experience of introducing risk analysis in the Department of Radiation Oncology at the Universitätsklinikum Erlangen.

METHODS

Risk analysis was performed with an in-house developed extension of our intranet platform and ticketing system. Risks were classified according to occurrence and severity, each on a 5-level scale resulting into a risk matrix. An interdisciplinary team of six experienced members formed the core meeting weekly.

RESULTS

A total of 38 risks and 50 measures have been identified in 41 1h-meetings corresponding to approx. 260 working hours. Risk was distributed 8/20/13 to the categories critical (n=8), monitoring (n=20), and conditionally acceptable (n=13). Risk analysis has been evaluated before and after introducing measures.

CONCLUSION

The risk analysis method introduced has been successfully used in routine operations for over a year. Risk analysis takes time and effort. However, because experts from different disciplines meet each other every week, the overall workflow of the radiation oncology department can be improved efficiently and continuously.

Robotics cyber security: vulnerabilities, attacks, countermeasures, and recommendations

The recent digital revolution led robots to become integrated more than ever into different domains such as agricultural, medical, industrial, military, police (law enforcement), and logistics. Robots are devoted to serve, facilitate, and enhance the human life. However, many incidents have been occurring, leading to serious injuries and devastating impacts such as the unnecessary loss of human lives. Unintended accidents will always take place, but the ones caused by malicious attacks represent a very challenging issue. This includes maliciously hijacking and controlling robots and causing serious economic and financial losses. This paper reviews the main security vulnerabilities, threats, risks, and their impacts, and the main security attacks within the robotics domain. In this context, different approaches and recommendations are presented in order to enhance and improve the security level of robotic systems such as multi-factor device/user authentication schemes, in addition to multi-factor cryptographic algorithms. We also review the recently presented security solutions for robotic systems.

Exposure analysis of benzene in workplace control room A and B PT X

OBJECTIVE

The control room A and B employees are a high risk of benzene exposure, because they work close to the waste pit which is a source of benzene. This study is to analyze the magnitude of the health risk of benzene exposure to all employees.

METHODS

The data of this study were obtained from interviews and the results of environmental quality of PT X. Data were analyzed using Environmental Health Risk Analysis (EHRA) method which compared with RfC for non-carcinogenic effects and CSF for carcinogenic effects.

RESULTS

The results of individual calculations for the non-carcinogenic and carcinogenic effect of benzene are at a dangerous level in both real time and lifetime exposure.

CONCLUSIONS

In the calculation of carcinogenic and non-carcinogenic risk exposure in real time, half the populations are at risk of being affected and in lifetime the entire populations are at risk of being exposed to these effects.

Blood conservation outcomes and safety of tranexamic acid in coronary artery bypass graft surgery

BACKGROUND

The safety and blood management effects of Tranexamic acid (TXA) and its dose effects in coronary artery bypass graft (CABG) were still ambiguous. This study aimed to analyze these TXA effects.

METHODS

Overall, 42,010 patients undergoing CABG were enrolled in this retrospective cohort study. Patients were assigned to the TXA group (n = 29,536) and the no-TXA group (n = 12,474). Furthermore, the TXA group was divided into the high-dose (≥50 mg/kg) (16,488) and the low-dose (<50 mg/kg) (13,048) subgroup. Propensity score matching was performed in both groups respectively. The primary endpoint after CABG was composed of hospital death, perioperative myocardial infarction (PMI), stroke, acute kidney injury (AKI), and pulmonary embolism. The secondary endpoint included blood loss and blood transfusion after surgery.

RESULTS

TXA led to a 1.40-fold risk of PMI (p < 0.001). Patients in the TXA group had fewer re-operations for bleeding or tamponade [Odd ratio (OR) = 0.82, p = 0.044], less blood loss after surgery (p < 0.001), and a lower risk for blood transfusion exposure (OR = 0.45, p < 0.001) than those in the no-TXA group. The high-dose TXA reduced blood loss after cardiac surgery compared to the low-dose TXA (p < 0.001) with no associations with blood exposure or adverse events.

CONCLUSIONS

The use of TXA during CABG increased the risk of PMI despite better blood control after surgery. The high dose of TXA acquired better bleeding management. Meanwhile, it did not increase the risk of primary endpoint.

Operating procedures, risk management and challenges during implementation of adaptive and non-adaptive MR-guided radiotherapy: 1-year single-center experience

BACKGROUND

Main purpose was to describe procedures and identify challenges in the implementation process of adaptive and non-adaptive MR-guided radiotherapy (MRgRT), especially new risks in workflow due to the new technique. We herein report the single center experience for the implementation of (MRgRT) and present an overview on our treatment practice.

METHODS

Descriptive statistics were used to summarize clinical and technical characteristics of treatment and patient characteristics including sites treated between April 2019 and end of March 2020 after ethical approval. A risk analysis was performed to identify risks of the online adaptive workflow.

RESULTS

A summary of the processes on the MR-Linac including workflows, quality assurance and possible pitfalls is presented. 111 patients with 124 courses were treated during the first year of MR-guided radiotherapy. The most commonly treated site was the abdomen (42% of all treatment courses). 73% of the courses were daily online adapted and a high number of treatment courses (75%) were treated with stereotactic body irradiation. Only 4/382 fractions could not be treated due to a failing online adaptive quality assurance. In the risk analysis for errors, the two risks with the highest risk priority number were both in the contouring category, making it the most critical step in the workflow.

CONCLUSION

Although challenging, establishment of MRgRT as a routinely used technique at our department was successful for all sites and daily o-ART was feasible from the first day on. However, ongoing research and reports will have to inform us on the optimal indications for MRgRT because careful patient selection is necessary as it continues to be a time-consuming treatment technique with restricted availability. After risk analysis, the most critical workflow category was the contouring process, which resembles the need of experienced staff and safety check paths.

Toward practical causal epidemiology

Population attributable fraction (PAF), probability of causation, burden of disease, and related quantities derived from relative risk ratios are widely used in applied epidemiology and health risk analysis to quantify the extent to which reducing or eliminating exposures would reduce disease risks. This causal interpretation conflates association with causation. It has sometimes led to demonstrably mistaken predictions and ineffective risk management recommendations. Causal artificial intelligence (CAI) methods developed at the intersection of many scientific disciplines over the past century instead use quantitative high-level descriptions of networks of causal mechanisms (typically represented by conditional probability tables or structural equations) to predict the effects caused by interventions. We summarize these developments and discuss how CAI methods can be applied to realistically imperfect data and knowledge - e.g., with unobserved (latent) variables, missing data, measurement errors, interindividual heterogeneity in exposure-response functions, and model uncertainty. We recommend that CAI methods can help to improve the conceptual foundations and practical value of epidemiological calculations by replacing association-based attributions of risk to exposures or other risk factors with causal predictions of the changes in health effects caused by interventions.

Integrated approach for legionellosis risk analysis in touristic-recreational facilities

Legionellosis is a severe pneumonia caused by the inhalation of aerosols containing Legionella, Gram-negative bacteria present in the water systems of touristic-recreational facilities. The purpose of this study was to develop a scoring tool to predict the risk of both environmental contamination and Legionnaires' disease cases in such facilities in the Apulia region of southern Italy. We analyzed 47 structural and management parameters/risk factors related to the buildings, water systems, and air conditioning at the facilities. A Poisson regression model was used to compute an overall risk score for each facility with respect to three outcomes: water samples positive for Legionella (risk score range: 7-54), water samples positive for Legionella with an average load exceeding 1000 colony-forming units per liter (CFU/L) (risk score range: 22-179,871), and clinical cases of Legionnaire's disease (risk score range: 6-31). The cut-off values for three outcomes were determined by receiver operating characteristic curves (first outcome, samples positive for Legionella in a touristic-recreational facility: 19; second outcome, samples positive for Legionella in a touristic-recreational facility with an average load exceeding 1000 CFU/L: 2062; third outcome, clinical cases of Legionnaire's disease in a touristic-recreational facility: 22). Above these values, there was a significant probability of observing the outcome. We constructed this predictive model using 70% of a large dataset (18 years of clinical and environmental surveillance) and tested the model on the remaining 30% of the dataset to demonstrate its reliability. Our model enables the assessment of risk for a touristic facility and the creation of a conceptual framework to link the risk analysis with prevention measures.

Thinking about Causation: A Thought Experiment with Dominos

We argue that population attributable fractions, probabilities of causation, burdens of disease, and similar association-based measures often do not provide valid estimates or surrogates for the fraction or number of disease cases that would be prevented by eliminating or reducing an exposure because their calculations do not include crucial mechanistic information. We use a thought experiment with a cascade of dominos to illustrate the need for mechanistic information when answering questions about how changing exposures changes risk. We suggest that modern methods of causal artificial intelligence (CAI) can fill this gap: they can complement and extend traditional epidemiological attribution calculations to provide information useful for risk management decisions.

Results of a 2020 Survey on Reporting Requirements and Practices for Biocontainment Laboratory Accidents

Biosafety laboratory accidents are a normal part of laboratory science, but the frequency of such accidents is unclear due to current reporting standards and processes. To better understand accident reporting, a survey was created, with input from ABSA International, which included a series of questions about standards, requirements, and likely motivations for reporting or nonreporting. A total of 60 biosafety officers completed the survey. Respondents reported working with more than 5,000 people in laboratories, including more than 40 biosafety level 3 or animal biosafety level 3 laboratories, which work with higher-risk pathogens. Most of the respondents were located in the United States, Canada, or New Zealand, or did not identify their location. Notable results included that 97% of surveyed biosafety officers oversee laboratories that require reporting exposure to at least some pathogens. However, 63% relayed that the reports are not usually sent outside of the institution where they occurred. A slight majority (55%) stated that paper reports were used, with the rest reporting they used a variety of computer systems. Even in laboratories that used paper-based reporting systems, 67% relayed that these reports were used alongside, or entered into, a digital system. While 82% of these biosafety officers agreed that workers understood the importance of reporting for their own safety, 82% also agreed that a variety of disincentives prevent laboratory workers from reporting incidents, including concerns about job loss and loss of funding.

Regional agricultural water resources management with respect to fuzzy return and energy constraint under uncertainty: An integrated optimization approach

In this study, an integrated framework is proposed for agricultural water and land resources management under uncertain circumstances and energy-water nexus. The framework has two components: the optimized interval solutions generation of unknown market quotation and environment situation through the novel interval fuzzy-expectation programming, and the post-optimization decision-making of the tradeoff between system risk and return through risk-explicit interval programming. An optimization model based on the framework was developed from a real description for agricultural water resources system of Guangdong province under considering various crop, multiple water sources, and the related energy consumption in irrigation and drainage. The impact of energy consumption and risk level control on water resources allocation among different crops and system benefits were analyzed. The results indicated that the preference for surface water resources as the main water sources can effectively reduce regional irrigation energy consumption, and the planting area of each crop would have different variations duo to resources endowment constraints. Risk tradeoff-based results can provide valuable information and additional concern for developing low carbon-oriented agricultural water resources management schemes.

Analysis of seroprevalence data on Hepatitis E virus and Toxoplasma gondii in wild ungulates for the assessment of human exposure to zoonotic meat-borne pathogens

Seroprevalence data for Toxoplasma gondii and Hepatitis E virus (HEV) in wild boar (Sus scrofa), roe deer (Capreolus capreolus), red deer (Cervus elaphus), mouflon (Ovis aries/musimon) and chamois (Rupicapra rupicapra) hunted/culled in northern Italy were used to fit seroprevalence distributions describing the exposure and co-exposure of the species to the two pathogens. The higher proportion of T. gondii and HEV seropositive animals was observed in wild boars with point estimate seroprevalence of 49% (N = 331) and 15% (N = 326) respectively. Data allowed comparisons by area (pre-Alpine Vs Alpine environment) for roe deer, red deer and mouflons. Contrasts between the distributions describing the uncertainty in seroprevalence suggest roe deer, red deer and mouflons have higher probability of being seropositive to T. gondii in pre-Alps. When considering HEV, few seropositive animals were detected and contrasts were symmetrically centred to zero for roe deer and red deer; mouflons shown higher probability of being seropositive in Alpine environment. HEV seropositive animals also included chamois (P = 5.1%, N = 97) in the Alpine districts, confirming circulation of HEV in remote areas. Evidence of HEV and T. gondii co-exposure was limited except for wild boars where it was observed in 30 samples representing 60% of the overall HEV-positive samples. Seroprevalence data of single infection and co-infection are extremely useful to investigate circulation of zoonotic pathogens in wild animals and estimate the foodborne risk of human exposure, however, these type of data do not directly translate into the presence/absence of the pathogen in seropositive and seronegative animals. At benefit of future development of quantitative risk assessments aiming at estimating the risk of human infection/co-infection via consumption of game meat, we developed and made available an online application that allows estimating the probability of the pathogen(s) being present as a function of seroprevalence data.

Evaluating the sensitivity of SARS-CoV-2 infection rates on college campuses to wastewater surveillance

As college campuses reopened in fall 2020, we saw a large-scale experiment unfold on the efficacy of various strategies to contain the SARS-CoV-2 virus. Traditional individual surveillance testing via nasal swabs and/or saliva is among the measures that colleges are pursuing to reduce the spread of the virus on campus. Additionally, some colleges are testing wastewater on their campuses for signs of infection, which can provide an early warning signal for campuses to locate COVID-positive individuals. However, a representation of wastewater surveillance has not yet been incorporated into epidemiological models for college campuses, nor has the efficacy of wastewater screening been evaluated relative to traditional individual surveillance testing, within the structure of these models. Here, we implement a new model component for wastewater surveillance within an established epidemiological model for college campuses. We use a hypothetical residential university to evaluate the efficacy of wastewater surveillance for maintaining low infection rates. We find that wastewater sampling with a 1-day lag to initiate individual screening tests, plus completing the subsequent tests within a 4-day period can keep overall infections within 5% of the infection rates seen with traditional individual surveillance testing. Our results also indicate that wastewater surveillance can effectively reduce the number of false positive cases by identifying subpopulations for surveillance testing where infectious individuals are more likely to be found. Through a Monte Carlo risk analysis, we find that surveillance testing that relies solely on wastewater sampling can be fragile against scenarios with high viral reproductive numbers and high rates of infection of campus community members by outside sources. These results point to the practical importance of additional surveillance measures to limit the spread of the virus on campus and the necessity of a proactive response to the initial signs of outbreak.

A global-scale screening of non-native aquatic organisms to identify potentially invasive species under current and future climate conditions

The threat posed by invasive non-native species worldwide requires a global approach to identify which introduced species are likely to pose an elevated risk of impact to native species and ecosystems. To inform policy, stakeholders and management decisions on global threats to aquatic ecosystems, 195 assessors representing 120 risk assessment areas across all six inhabited continents screened 819 non-native species from 15 groups of aquatic organisms (freshwater, brackish, marine plants and animals) using the Aquatic Species Invasiveness Screening Kit. This multi-lingual decision-support tool for the risk screening of aquatic organisms provides assessors with risk scores for a species under current and future climate change conditions that, following a statistically based calibration, permits the accurate classification of species into high-, medium- and low-risk categories under current and predicted climate conditions. The 1730 screenings undertaken encompassed wide geographical areas (regions, political entities, parts thereof, water bodies, river basins, lake drainage basins, and marine regions), which permitted thresholds to be identified for almost all aquatic organismal groups screened as well as for tropical, temperate and continental climate classes, and for tropical and temperate marine ecoregions. In total, 33 species were identified as posing a 'very high risk' of being or becoming invasive, and the scores of several of these species under current climate increased under future climate conditions, primarily due to their wide thermal tolerances. The risk thresholds determined for taxonomic groups and climate zones provide a basis against which area-specific or climate-based calibrated thresholds may be interpreted. In turn, the risk rankings help decision-makers identify which species require an immediate 'rapid' management action (e.g. eradication, control) to avoid or mitigate adverse impacts, which require a full risk assessment, and which are to be restricted or banned with regard to importation and/or sale as ornamental or aquarium/fishery enhancement.

Future Directions in Robotic Neurosurgery

In this paper, we highlight promising technologies in each phase of a robotic neurosurgery operation, and identify key factors affecting how quickly these technologies will mature into products in the operating room. We focus on specific technology trends in image-guided cranial and spinal procedures, including advances in imaging, machine learning, robotics, and novel interfaces. For each technology, we discuss the required effort to overcome safety or implementation challenges, as well as identifying example regulatory approved products in related fields for comparison. The goal is to provide a roadmap for clinicians as to which robotic and automation technologies are in the developmental pipeline, and which ones are likely to impact their practice sooner, rather than later.

Risk management in occupational safety: A systematic mapping

BACKGROUND

Occupational safety risk management is a systemic process capable of promoting technical engineering solutions, considering a wide range of predictable, unexpected and subjective factors related to accident occurrences. In Brazil, the behavior of managers in relation to risk management tends to be reactive, and facilitates access to information for crucial practical and academic purposes when it comes to changing the attitude of managers, so that their actions become increasingly more proactive.

OBJECTIVE

To identify, classify, analyze, and discuss the existing literature related to the topic, produced from 2008 to 2020, besides contributing to a broader understanding of risk management in occupational safety.

METHODS

We did a systematic literature mapping. The research process was documented starting by the planning stage. Afterwards, the focus was on research conduction and information synthesis.

RESULTS

Knowledge systematization and stratification about OHS risk management through various perspectives to identify, analyze and manage risks in the workplace. Were identified 37 tools for identifying and analyzing risks, management-related practices and future research trends.

CONCLUSIONS

The set of tools and management practices identified can be used as a support for decision making in the selection process of tools and practices to reduce risks and improve occupational safety. Also, the results can help target future research.

Bus crash risk evaluation: An adjusted framework and its application in a real network

Greater attention to bus safety can lead to relevant benefits for public transport companies in terms of higher service performance, reliability, and lower insurance costs. Therefore, measuring the crash risk on bus routes provides an opportunity to improve the safety performance of transit operators. Previous research has explored the effects of many factors regarding the frequency and severity of bus crashes, whereas only a handful of studies have defined some crash risk indexes. Conversely, to the best of our knowledge, almost no research has been done regarding the crash risk in the bus transit network that integrates frequency, severity, and the exposure factors. This paper proposes a new framework to assess the crash risk for each transit bus route by the integration of safety factors, prediction models and risk methods. More precisely, this framework identifies several safety factors and specifies the risk components in terms of frequency, severity and exposure factors that may affect bus crashes. Then, it models their relationships to build a bus crash risk function. Lastly, according to the values returned by the previous function, the crash risk for each route is computed and a safety performance ranking for each route is provided. The feasibility of this framework is demonstrated in a real case study by using bus crash data provided by a mid-sized Italian bus operator. The findings show that transit managers could implement this framework in a road traffic safety management system to evaluate the risk of crashes on routes, monitor the safety performance of each route and qualify each route according to recent safety norms.

Risk management recommendations for environmental releases of gene drive modified insects

The ability to engineer gene drives (genetic elements that bias their own inheritance) has sparked enthusiasm and concerns. Engineered gene drives could potentially be used to address long-standing challenges in the control of insect disease vectors, agricultural pests and invasive species, or help to rescue endangered species. However, risk concerns and uncertainty associated with potential environmental release of gene drive modified insects (GDMIs) have led some stakeholders to call for a global moratorium on such releases or the application of other strict precautionary measures to mitigate perceived risk assessment and risk management challenges. Instead, we provide recommendations that may help to improve the relevance of risk assessment and risk management frameworks for environmental releases of GDMIs. These recommendations include: (1) developing additional and more practical risk assessment guidance to ensure appropriate levels of safety; (2) making policy goals and regulatory decision-making criteria operational for use in risk assessment so that what constitutes harm is clearly defined; (3) ensuring a more dynamic interplay between risk assessment and risk management to manage uncertainty through closely interlinked pre-release modelling and post-release monitoring; (4) considering potential risks against potential benefits, and comparing them with those of alternative actions to account for a wider (management) context; and (5) implementing a modular, phased approach to authorisations for incremental acceptance and management of risks and uncertainty. Along with providing stakeholder engagement opportunities in the risk analysis process, the recommendations proposed may enable risk managers to make choices that are more proportionate and adaptive to potential risks, uncertainty and benefits of GDMI applications, and socially robust.

[Application of a new methodology of a priori risk analysis in a radiotherapy department]

Since 2017, IRSN has been developing a new proactive risk analysis method. The Work Complexity Sharing and Exploration Spaces (EPECT in French) were tested for the first time in 2020 in the radiotherapy department of the Gustave Roussy Institute. The EPECT method makes it possible to anchor the analysis of risks incurred by patients in daily work situations and to involve the top management. The time required to involve the teams is comparable to or even less than that required for a conventional risk analysis. The cost/benefit ratio of the method seems to be advantageous because it provides access to numerous information on daily activities, which makes it possible to improve the safety of patient care in radiotherapy. The information gathered allows relevant actions to be envisaged at both the technical and organizational levels, and to be linked to departmental projects.