Final Risk Index Research Articles

Development of a framework for assessing climate risk in water supply and its computation for the Districts of Maharashtra, India

ABSTRACT The paper discusses the development of a composite index for assessing the risks faced by rural communities because of disruptions in water supply caused by natural hazards such as droughts, floods, and landslides. The various parameters considered for developing the three dimensions of the risk index, namely, hazard, exposure, and vulnerability, the rationale for choosing those parameters, and the manner in which these parameters influence them are discussed. The index uses 29 variables: 5 for hazard, 15 for exposure, and the remaining 9 for vulnerability. The variables are natural, physical, socioeconomic, and institutional or policy-related. The quantitative criteria for assigning values for various parameters and the analytical procedure for computing the sub-indices and the final risk index are also discussed. The paper also presents the results of a mapping of climate-induced risk to water supply in 35 districts of the state of Maharashtra in western India, done using district level data on the various parameters concerned, and identifying the district where water supply systems are highly prone to climate-induced risks.

Climate-Risk Assessment Framework for Airports under Extreme Precipitation Events: Application to Selected Italian Case Studies

Extreme weather phenomena are increasing due to climate change and having a severe impact on critical infrastructure, including airports. In this context, conducting climate risk assessments is an essential step to implement appropriate adaptation strategies. In the present study, a climate-risk assessment framework is applied to evaluate the risk of extreme precipitation events for specific Italian airports: Malpensa, Bergamo, Linate, Fiumicino, Ciampino, Napoli, Catania, Palermo, and Cagliari. This analysis is based on the definition of risk as reported by Sixth Assessment Report of IPCC. The assessment of the climate hazard over the recent-past period (1981–2010) is evaluated through indicators developed from re-analysis data, using the Uncertainties in Ensemble of Regional Re-Analyses dataset are provided by Copernicus Climate Change Service. The expected climate variations are evaluated using an ensemble of high-resolution climate projections from the EURO-CORDEX initiative for the short- (2021–2050), medium- (2041–2070), and long-term future period (2071–2100), under RCP 2.6, RCP 4.5, and RCP 8.5 climate scenarios. The information related to exposure and vulnerability indicators are collected from official documents and website of selected airports, and are freely available. The final risk index provides elements allowing stakeholders to implement adaptation measures to increase their resilience.

Application of climate risk assessment framework for selected Italian airports: A focus on extreme temperature events

Due to increased extreme weather events as a consequence of climate change, climate risk analysis has become an essential issue for all critical infrastructures, including airports. The aim of this paper is to apply a climate risk assessment framework to evaluate the impacts of extreme temperatures on several Italian airports: Malpensa, Linate, Bergamo, Ciampino, Fiumicino, Napoli, Catania, Palermo, and Cagliari. According to the risk definition recommended in the Fifth Assessment Report of IPCC (2014), specific hazard, exposure and vulnerability indicators were identified. The hazard indicators were calculated using the UERRA regional reanalysis for the observed period (1981–2010), and then their climate variations were evaluated by means an ensemble of high-resolution climate projections from the EURO-CORDEX initiative for the near (2021–2050), medium (2041–2070), and long-term future period (2071–2100), under RCP 2.6, RCP 4.5, and RCP 8.5 scenarios. Exposure and vulnerability data were collected from multiple sources, such as official airports documents or websites. The final risk index obtained from the combination of these three factors allowed us to identify which of the selected airports are probable to face the major impacts due to extreme temperature events. This paper provides the knowledge base on risk assessment on Italian airports, with the aim to support the stakeholders for the selection and implementation of appropriate adaptation strategies and measures in relation to extreme temperatures.

Risk-Based Inspection and Rehabilitation Planning of Service Connections in Intermittent Water Supply Systems for Leakage Management in Arid Regions

Most of the leakage in water distribution systems operating with plastic pipes occurs at service connections (SCs), while the existing tools plan rehabilitation of pipes. With limited water resources, intermittent supplies in arid regions further enhance the failure vulnerability of metal fittings on water mains due to scale formation and large pressure transients. The present research developed a risk-based methodology for the proactive maintenance of SCs in intermittent water supply systems. A five-generation bottom-up hierarchical approach aggregated the basic hydraulic, physical, and water quality factors to determine the vulnerability of structural failures of SCs. Hydraulic parameters (pressure and velocity) were estimated by simulating a distribution network of 366 water mains of diameters ranging from 110 mm to 225 mm serving 371 SCs in a residential neighborhood located in the Qassim region of Saudi Arabia. Age, depth, and length of SCs’ estimated the condition index, while soil corrosivity and condition of the water mains were also counted when assessing the structural failure index for each SC. Water quality parameters, e.g., pH, turbidity, and iron, that can contribute to the vulnerability of an SC’s failure were also included. Fuzzy-based methods first assessed the relative importance weights of the basic input parameters at the bottom of the hierarchy and the risk factors in the middle of the hierarchy. Subsequently, the performance and condition scores were aggregated to develop respective indices. As the consequence of structural failure is high for the SCs serving households with a large number of residents, the final risk index aggregates the vulnerability and consequence at the hierarchy’s top. The developed model was effectively validated by comparing the SCs of high priority with the leaking and repaired SCs in the past. The method will be a useful tool for planning proactive inspection and rehabilitation of SCs of intermittent supply systems to minimize water losses (less than 8% of the national benchmark) in Saudi Arabia and elsewhere.

Assessing the risk of COVID-19 in high-risk personnel of the police forces using rapid risk analysis technique

Background and Aim: Given the rapid spread of COVID-19 disease around the world, determining the risk of disease in the workplace is one of the essential factors to improve management of this infectious disease. Therefore, this study was conducted to assess the risk of COVID-19 disease in high-risk personnel of the police forces using rapid risk analysis technique. Methods: This study was a descriptive, analytical, and cross-sectional study conducted in Winter 2021 in Tehran. Participants were 474 police officers randomly selected from three different sub-groups including»P« police,»R« police and»A« police (shown as and in Farsi manuscript, respectively). A rapid risk analysis technique was used to collect data. The data collection tool was a questionnaire based on the mentioned technique, which includes three components of disease probability, severity (consequence), and level of health belief. Adjustments and responses were scored based on the Likert scale. Then, the scores obtained from estimating the three components were multiplied and the result represented the final risk index for COVID-19. Data were analyzed using SPSS software version 24 and using the mentioned technique. In this study, Analysis of Variance and Bonferroni post hoc test with a significance level of 0.05 was used. Results: The risk index score of more than 95% of»P« police officers and more than 88% of»R« police officers and more than 93% of»A« police officers were above 40(unacceptable). The minimum (4.86) and maximum (890.62) risk index was related to»R« police. Based on univariate analysis of variance, there was no significant difference between the risk of COVID-19 disease in the three occupational groups (F=0.13 and p-value=0.87). Comparing the level of three components effective in estimating the risk index, there was no significant difference between the components of the level of disease probability and level of health belief in the three occupational groups, however, there was a significant difference in the level of severity (consequence) component of all three groups. In addition, 47.2%»P« police, 45.7%»R« police, and 35.5%»A« police group were suspected to be sick. Conclusion: According to the findings of this study, all three occupational groups were at risk for COVID-19 disease. Therefore, in order to control the COVID-19 epidemic, employers must implement infection control strategies based on accurate and technical assessment of the risk of disease in order to prevent the occurrence of disease and consequently reduce lost working days by performing appropriate, timely, and low-cost control activities. © 2021 Baqiyatallah University of Medical Sciences. All rights reserved.

Development of an Aggregated Risk Index for the Management of Investment in Safety Measures on the Belgian Rail Network

In order to take up new challenges regarding the management of a wide range of parameters impacting the risk of accidents at rail crossings on the Belgian railway network, we have developed an innovative multicriteria decision making framework based upon the pairwise comparison PROMETHEE (Preference Ranking METHod for Enrichment and Evaluation). The framework allows the evaluation of a global risk index based upon a wide range of indicators thanks to a “two-steps” aggregation process including the definition of sensitivity parameters. Around 50 indicators are classified into three main clusters related to three specific risk sources, namely: the road network, the rail network and the town planning related aspects. These three clusters are then aggregated into the final risk index. Within the frame of the Belgian rail network, this index provides the responsible public body with an actual strategic investment handbook regarding the most risky locations. An user friendly excel tool has been developed in order to make that new decision framework easily understandable by the final users.

Analytical Modeling for Underground Risk Assessment in Smart Cities

In the developed world, underground facilities are increasing day-by-day, as it is considered as an improved utilization of available space in smart cities. Typical facilities include underground railway lines, electricity lines, parking lots, water supply systems, sewerage network, etc. Besides its utility, these facilities also pose serious threats to citizens and property. To preempt accidental loss of precious human lives and properties, a real time monitoring system is highly desirable for conducting risk assessment on continuous basis and timely report any abnormality before its too late. In this paper, we present an analytical formulation to model system behavior for risk analysis and assessment based on various risk contributing factors. Based on proposed analytical model, we have evaluated three approximation techniques for computing final risk index: (a) simple linear approximation based on multiple linear regression analysis; (b) hierarchical fuzzy logic based technique in which related risk factors are combined in a tree like structure; and (c) hybrid approximation approach which is a combination of (a) and (b). Experimental results shows that simple linear approximation fails to accurately estimate final risk index as compared to hierarchical fuzzy logic based system which shows that the latter provides an efficient method for monitoring and forecasting critical issues in the underground facilities and may assist in maintenance efficiency as well. Estimation results based on hybrid approach fails to accurately estimate final risk index. However, hybrid scheme reveals some interesting and detailed information by performing automatic clustering based on location risk index.

Development of a preliminary risk index to identify trauma patients at risk for an unplanned intubation

The development of respiratory failure requiring an emergent unplanned intubation (UI) is a potentially preventable complication associated with increased morbidity and mortality. The objective of this study was to develop a clinical risk index for UI based on readily available clinical data to assist in the identification of trauma patients at risk for this complication. We also sought to determine the impact of UI on patient outcomes. This is a 3-year retrospective analysis of our Level 1 trauma center registry to identify all patients requiring a UI. Patients who required a UI were compared with patients who were never intubated. An additive risk index consisting of 10 clinical variables was created using the final significant variables from a stepwise logistic regression model. The sensitivity and specificity of every possible index score were calculated and added together to calculate the "gain in certainty" values. During the 3-year period, 7,552 patients were admitted, of whom 967 (12.8%) required intubation. Of these, 55 (5.7%) underwent a UI. The final risk index consisted of 10 variables as follows: age 55 years to 64 years, age 65 years or older, male sex, Glasgow Coma Scale (GCS) score of 9 to 13, seizures, chronic obstructive pulmonary disease, traumatic brain injury, four or more rib fractures, spine fractures, and long-bone fractures. Gain in certainty was maximized at an index score of 4, with the highest combined sensitivity and specificity of 86.0% and 74.9%, respectively. The probability of UI increased from 0.9% at a score of 1 to 2.9% at 4 and 43% at 9. UI was associated with increased overall complications, length of stay, and mortality (p < 0.001). UI is a potentially preventable adverse event associated with poor outcomes. Identification of patients at risk for this complication may be possible through the development of an additive risk index. Prospective validation of the risk index is potentially warranted. Diagnostic study, level III.

Wildfire Occurrence: Integrated Model for Risk Analysis and Operative Suppression Aspects Management

Generally forest fires are related to human activities and need an effective fire prevention and suppression organization, based on a deep knowledge of the territory, fire behaviour and suppression system resources network. To organise monitoring, prevention and fire fighting operations, the knowledge of the risk level for different areas is important. To evaluate the probability that a forest fire occurs and to organise prevention and management of fire fighting activities, both simple and easy-to-use risk and operational difficulty indices were implemented. CNR-IBIMET and DISTAF Dept., on commitment of Tuscany Region, developed a multistep process for the evaluation of the risk, that can be used to assess land planning and to organise seasonal fire fighting resources. This model is called Final Risk Index (FRI); it is the result of the combination of the following two indices, which are initially developed separately. The concerned indices are the Global Risk Index (GRI), and Operational Difficulty Index in Fire Fighting (ODIF). The fire risk index processes different parameters to generate two hazards: static and dynamic, merged to obtain the Global Risk Index (GRI). It is very helpful to estimate the probability of forest fire occurrence, but it does not provide information on forest fire extinction difficulties. The operational difficulty index in fire fighting (ODIF) resumes all the factors affecting fire fighting activity by air and by ground and suggests the extinction efficiency of forest fires in a given area. Thus FRI improves aspects of the fire prevention planning, focused to the needs of a public operative structure. The objective was modelling the links between the main components in ignition and fire fighting actions to produce an easy to use tool to face the emergences, also foreseeing forest fires regime changes in the coming decades.

Developing an Additive Risk Model for Predicting Academic Index: School Factors and Academic Achievement

The impact of school factors on academic achievement has become an important focus for identifying, preventing, and intervening with youth at-risk for academic failure. This study was designed to develop and test a more comprehensive school factor risk index. Specifically, the relationship between cumulative grade point average (GPA) and an additive risk index (ARI) were tested and an analysis of the index is presented. School factors that been shown in previous research to impact academic achievement were tested. Those factors were included in the final risk index if they met the criteria of (1) having a correlation with GPA, (2) containing a difference in outcomes between the risk and non-risk groups, and (3) making a unique contribution to the overall index. The risk and protective factors included in the creation of the ARI were attendance, academic self-efficacy, academic expectations, grade retention, music instruction, and school behaviors. The interplay between risk and protective factors was shown to have a significant relationship with GPA.

Early assessment of risk in patients with acute myocardial infarction.

In 360 patients with acute myocardial infarction, non-invasive clinical parameters were recorded during the first 24 h following admission. Serum enzymes (CK, CK-MB, ASA T and LDH) were serially measured at 4 h intervals during three days. Forty-two patients (12%) died within two weeks of hospitalization. The study population was divided into training (159 patients) and control (201 patients) groups. As individual variables, age, previous history of infarction (PI) or angina, conduction disturbances and left ventricular impairment exerted an unfavourable influence on the short-term prognosis. Serum LDH activity observed at the time of CK peak was a better predictor of risk than ASAT and CK peak levels. No significant difference was demonstrated for CK-MB peak level between survivors and non-survivors. Stepwise logistic discrimination was applied to all parameters (clinical and biochemical) recorded within 24 h after admission in the patients of the training group. Only three variables were retained in the selection procedure namely, LDH at CK peak, age and number of previous infarctions. These variables jointly provide the best prediction of high and low risk patients. The final risk index based on the three selected parameters, i.e. R=000189LDH+0.0978age+1.37PI−11-9,was validated on the patients of the control sample. According to the risk R obtained, all patients were allocated into four classes of increasing risk. Two well-defined groups of patients could be identified readily at the end of the first day following admission: one with high risk of mortality (60% death) and one with good prognosis (37% of the total population, mortality rate <1%), the latter consisting of patients who might benefit from early discharge from the coronary care unit.