Search results for: disaster risk assessment

Authors: Fei Gao, Rodolfo C. Raga Jr.

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This research proposal will ascertain the major risk factors for diabetes and to design a predictive model for risk assessment. The project aims to improve diabetes early detection and management by utilizing data science techniques, which may improve patient outcomes and healthcare efficiency. The phase relation values of each attribute were used to analyze and choose the attributes that might influence the examiner's survival probability using Diabetes Health Indicators Dataset from Kaggle’s data as the research data. We compare and evaluate eight machine learning algorithms. Our investigation begins with comprehensive data preprocessing, including feature engineering and dimensionality reduction, aimed at enhancing data quality. The dataset, comprising health indicators and medical data, serves as a foundation for training and testing these algorithms. A rigorous cross-validation process is applied, and we assess their performance using five key metrics like accuracy, precision, recall, F1-score, and area under the receiver operating characteristic curve (AUC-ROC). After analyzing the data characteristics, investigate their impact on the likelihood of diabetes and develop corresponding risk indicators.

Keywords: diabetes, risk factors, predictive model, risk assessment, data science techniques, early detection, data analysis, Kaggle

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Authors: Dianne Williams

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This study examined the peer/individual domain of the Risk Factor Prevention Paradigm (RFPP) to assess the risk and protective factors that impact criminal gang involvement among at-risk males residing in a juvenile home in Trinidad and Tobago. The RFPP allows for the identification of both risk and protective factors in a single, holistic framework to identify the relationship between risk factors, protective factors, and criminal gang involvement among at-risk male adolescents. Findings showed that having anti-social peers was the most significant risk factor associated with criminal gang involvement, while the most significant protective factor was having a positive social attitude. Moreover, while 65% of the boys reported never having been in a gang, 70% reported having hit, struck or used a weapon against someone, while 52% reported being involved in other violent incidents on more than two occasions. This suggests that while involvement with criminal gangs may not be common among this population, predisposing behavioral patterns are present. Results are expected to assist in the development of targeted strategies to reduce the attractiveness of gang membership.

Keywords: risk factor prevention paradigm, risk factors, protective factors, peer/individual domain, gang involvement, at-risk youth, trinidad and tobago, juvenile home

Procedia PDF Downloads 563

Authors: Eduard Fosch-Villaronga

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This paper pioneers Care Robot Impact Assessment (CRIA), a methodology used to identify, analyze, mitigate and eliminate the risks posed by the insertion of non-medical personal care robots (PCR) in medical care facilities. Its precedent instruments (Privacy and Surveillance Impact Assessment (PIA and SIA)) fall behind in coping with robots. Indeed, personal care robots change dramatically how care is delivered. The paper presents a specific risk-sector methodology, identifies which robots are under its scope and presents some of the challenges introduced by these robots.

Keywords: ethics, impact assessment, law, personal care robots

Procedia PDF Downloads 542

Authors: Kowser Ali Jan, R. Balaji

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A disaster hurts those affected. It also spares many in the affected areas, yet those spared may be indirectly affected. The analytical framework of prevention and coping has proved useful in many circumstances. Historically and currently, there has been limited quantitative information available on flood management in Jammu and Kashmir. This study focuses on the Cost-benefit Analysis (CBA) of flood management by District Disaster Management Kulgam, and the assessment is based on secondary pooled data collected from government offices, NGOs, published Journals, and local and national newspapers. It also described the scenario, the approach adopted, and the sources of flood damage cost information. The estimated total benefits account for 78686.18 lakh of rupees, and that of total costs account for 2218.75lakh of rupees. The Benefit-Cost ratio greater than one (>1) shows that Flood Management in District Kulgam was economically feasible and successfully managed. The State of Jammu and Kashmir takes essential prevention and management measures to bring down the damages due to floods to significant status.

Keywords: cost-benefit analysis, nature, flood management, disaster

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Authors: Ali Mortazavi

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The main objective of this research project is to delve into a multitude of geomechanical risks associated with various mining methods employed within the underground mining industry. Controlling geotechnical design parameters and operational factors affecting the selection of suitable mining techniques for a given underground mining condition will be considered from a risk assessment point of view. Important geomechanical challenges will be investigated as appropriate and relevant to the commonly used underground mining methods. Given the complicated nature of rock mass in-situ and complicated boundary conditions and operational complexities associated with various underground mining methods, the selection of a safe and economic mining operation is of paramount significance. Rock failure at varying scales within the underground mining openings is always a threat to mining operations and causes human and capital losses worldwide. Geotechnical design is a major design component of all underground mines and basically dominates the safety of an underground mine. With regard to uncertainties that exist in rock characterization prior to mine development, there are always risks associated with inappropriate design as a function of mining conditions and the selected mining method. Uncertainty often results from the inherent variability of rock masse, which in turn is a function of both geological materials and rock mass in-situ conditions. The focus of this research is on developing a methodology which enables a geomechanical risk assessment of given underground mining conditions. The outcome of this research is a geotechnical risk analysis algorithm, which can be used as an aid in selecting the appropriate mining method as a function of mine design parameters (e.g., rock in-situ properties, design method, governing boundary conditions such as in-situ stress and groundwater, etc.).

Keywords: geomechanical risk assessment, rock mechanics, underground mining, rock engineering

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Authors: Alexander Guzman Urbina, Atsushi Aoyama

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The sustainability of traditional technologies employed in energy and chemical infrastructure brings a big challenge for our society. Making decisions related with safety of industrial infrastructure, the values of accidental risk are becoming relevant points for discussion. However, the challenge is the reliability of the models employed to get the risk data. Such models usually involve large number of variables and with large amounts of uncertainty. The most efficient techniques to overcome those problems are built using Artificial Intelligence (AI), and more specifically using hybrid systems such as Neuro-Fuzzy algorithms. Therefore, this paper aims to introduce a hybrid algorithm for risk assessment trained using near-miss accident data. As mentioned above the sustainability of traditional technologies related with energy and chemical infrastructure constitutes one of the major challenges that today’s societies and firms are facing. Besides that, the adaptation of those technologies to the effects of the climate change in sensible environments represents a critical concern for safety and risk management. Regarding this issue argue that social consequences of catastrophic risks are increasing rapidly, due mainly to the concentration of people and energy infrastructure in hazard-prone areas, aggravated by the lack of knowledge about the risks. Additional to the social consequences described above, and considering the industrial sector as critical infrastructure due to its large impact to the economy in case of a failure the relevance of industrial safety has become a critical issue for the current society. Then, regarding the safety concern, pipeline operators and regulators have been performing risk assessments in attempts to evaluate accurately probabilities of failure of the infrastructure, and consequences associated with those failures. However, estimating accidental risks in critical infrastructure involves a substantial effort and costs due to number of variables involved, complexity and lack of information. Therefore, this paper aims to introduce a well trained algorithm for risk assessment using deep learning, which could be capable to deal efficiently with the complexity and uncertainty. The advantage point of the deep learning using near-miss accidents data is that it could be employed in risk assessment as an efficient engineering tool to treat the uncertainty of the risk values in complex environments. The basic idea of using a Near-Miss Deep Learning Approach for Neuro-Fuzzy Risk Assessment in Pipelines is focused in the objective of improve the validity of the risk values learning from near-miss accidents and imitating the human expertise scoring risks and setting tolerance levels. In summary, the method of Deep Learning for Neuro-Fuzzy Risk Assessment involves a regression analysis called group method of data handling (GMDH), which consists in the determination of the optimal configuration of the risk assessment model and its parameters employing polynomial theory.

Keywords: deep learning, risk assessment, neuro fuzzy, pipelines

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Authors: Hossam Shalabi, George Hadjisophocleous

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The Canadian Nuclear Power Plants (NPPs) use some portions of NUREG/CR-6850 in carrying out Fire Probabilistic Risk Assessment (PRA). An assessment for the applicability of NUREG/CR-6850 to CANDU reactors was performed and a CANDU Fire PRA was introduced. There are 19 operating CANDU reactors in Canada at five sites (Bruce A, Bruce B, Darlington, Pickering and Point Lepreau). A fire load density survey was done for all Fire Safe Shutdown Analysis (FSSA) fire zones in all CANDU sites in Canada. National Fire Protection Association (NFPA) Standard 557 proposes that a fire load survey must be conducted by either the weighing method or the inventory method or a combination of both. The combination method results in the most accurate values for fire loads. An updated CANDU Fire PRA model is demonstrated in this paper that includes the fuel survey in all Canadian CANDU stations. A qualitative screening step for the CANDU fire PRA is illustrated in this paper to include any fire events that can damage any part of the emergency power supply in addition to FSSA cables.

Keywords: fire safety, CANDU, nuclear, fuel densities, FDS, qualitative analysis, fire probabilistic risk assessment

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Authors: Abhijitsinh Gohil, Kaushal Wadhvaniya, Kuldipsinh Jadeja

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Road Safety is a multi-sectoral and multi-dimensional issue. An effective model can assess the risk associated with highway safety. A questionnaire survey is very essential to identify the events or activities which are causing unsafe condition for traffic on an urban highway. A questionnaire of standard questions including vehicular, human and infrastructure characteristics can be made. Responses from the age wise group of road users can be taken on field. Each question or an event holds a specific risk weightage, which contributes in creating an inappropriate and unsafe flow of traffic. The probability of occurrence of an event can be calculated from the data collected from the road users. Finally, the risk score can be calculated by considering the risk factor and the probability of occurrence of individual event and addition of all risk score for the individual event will give the total risk score of a particular road. Standards for risk score can be made and total risk score can be compared with the standards. Thus road can be categorized based on risk associated and traffic safety on it. With this model, one can assess the need for traffic safety improvement on a given road, and qualitative data can be analysed.

Keywords: probability of occurrence, questionnaire, risk factor, risk score

Procedia PDF Downloads 315

Authors: Soledad Natalia M. Dalisay, Mylene De Guzman

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In archipelagic countries like the Philippines, many communities thrive along coastal areas. The sea is the community members’ main source of livelihood and the site of many cultural activities. For these communities, the sea is their life and livelihood. Nevertheless, the sea also poses a hazard during the rainy season when typhoons frequent their communities. Coastal communities often encounter threats from storm surges and flooding that are common when there are typhoons. During such periods, disaster evacuation programs are implemented. However, in many instances, evacuation has been the bane of local government officials implementing such programs in their communities as resistance from community members is often encountered. Such resistance is often viewed by program implementers as due to the fact that people were hard headed and ignorant of the potential impacts of living in hazard prone areas. This paper argues that it is not for these reasons that people refused to evacuate. Drawing from data collected from fieldwork done in three sites in Central Philippines affected by super typhoon Haiyan, this study aimed to provide a contextualized understanding of peoples’ refusal to heed disaster evacuation warnings. This study utilized the multi-sited ethnography approach with in-depth episodic interviews, focus group discussions, participatory risk mapping and key informant interviews in gathering data on peoples’ experiences and insights specifically on evacuation during typhoon Haiyan. This study showed that people have priorities and considerations vital in their social lives that they are protecting in their refusal to leave their homes for pre-emptive evacuation. It is not that they are not aware of the risks when the face the hazard. It is more that they had faith in the local knowledge and strategies that they have developed since the time of their ancestors as a result of living and engaging with hazards in their areas for as long as they could remember. The study also revealed that risk in encounters with hazards was gendered. Furthermore, previous engagement with local government officials and the manner in which the pre-emptive evacuation programs were implemented had cast doubt on the value of such programs in saving their lives. Life in the designated evacuation areas can be as dangerous if not more compared with living in their coastal homes. There seems to be the impression that in the evacuation program of the government, people were being moved from hazard zones to death zones. Thus, this paper ends with several recommendations that may contribute to building more responsive evacuation programs that aim to build people’s resilience while taking into consideration the local moral world in communities in identified hazard zones.

Keywords: coastal communities, disaster evacuation, disaster risk perception, social and cultural responses to hazards

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Authors: Rifaldy, Misbahudin, Khalid Rizky, Ricky Aryanto, M. Alfiyan Bagus, Fahri Septianto, Firman Najib Wibisana, Excobar Arman

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Indonesia is a country that has a high level of disaster because it is on the ring of fire, and there are several regions with three major plates meeting in the world. So that disaster analysis must always be done to see the potential disasters that might always occur, especially in this research are landslides and liquefaction. This research was conducted to analyze areas that are vulnerable to landslides and liquefaction hazards and their relationship with the assessment of the issue of moving the new capital of the Republic of Indonesia to the island of Kalimantan with a total area of 612,267.22 km². The method in this analysis uses the Analytical Hierarchy Process and consistency ratio testing as a complex and unstructured problem-solving process into several parameters by providing values. The parameters used in this analysis are the slope, land cover, lithology distribution, wetness index, earthquake data, peak ground acceleration. Weighted overlay was carried out from all these parameters using the percentage value obtained from the Analytical Hierarchy Process and confirmed its accuracy with a consistency ratio so that a percentage of the area obtained with different vulnerability classification values was obtained. Based on the analysis results obtained vulnerability classification from very high to low vulnerability. There are (0.15%) 918.40083 km² of highly vulnerable, medium (20.75%) 127,045,44815 km², low (56.54%) 346,175.886188 km², very low (22.56%) 138,127.484832 km². This research is expected to be able to map landslides and liquefaction disasters on the island of Kalimantan and provide consideration of the suitability of regional development of the new capital of the Republic of Indonesia. Also, this research is expected to provide input or can be applied to all regions that are analyzing the vulnerability of landslides and liquefaction or the suitability of the development of certain regions.

Keywords: analytic hierarchy process, Borneo Island, landslide and liquefaction, vulnerability analysis

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Authors: Wei-Kuang Liu, Ya-Hsu Chiang

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In the coming of an aging society, the issues of living quality, health care, and social security for the elderly have been gradually taken seriously. In order to maintain favorable living condition, urban societies are also facing the challenge of disasters caused by extreme climate change. However, in the practice of disaster prevention, elderly people are always weak due to their physiological conditions. That is to say, in the planning of resilient urbanism, the aging society is relatively in need of more care. Thus, this research aims to map areas where have high-density elderly population and fragile environmental condition in Taiwan, and to understand the actual situation of disaster prevention management in these areas, so as to provide suggestions for the development of intellectual resilient urban management. The research takes the cities of Taoyuan and Taichung as examples for explorations. According to GIS mapping of areas with high aging index, high-density population and high flooding potential, the communities of Sihai and Fuyuan in Taoyuan and the communities of Taichang and Nanshih in Taichung are highlighted. In these communities, it can be found that there are more elderly population and less labor population with high-density living condition. In addition, they are located in the areas where they have experienced severe flooding in the recent past. Based on a series of interviews with community organizations, there is only one community out of the four using flood information mobile app and Line messages for the management of disaster prevention, and the others still rely on the traditional approaches that manage the works of disaster prevention by their community security patrol teams and community volunteers. The interview outcome shows that most elderly people are not interested in learning the use of intellectual devices. Therefore, this research suggests to keep doing the GIS mapping of areas with high aging index, high-density population and high flooding potential for grasping the high-risk communities and to help develop smart monitor and forecast systems for disaster prevention practice in these areas. Based on case-study explorations, the research also advises that it is important to develop easy-to-use bottom-up and two-way immediate communication mechanism for the management of aging society’s disaster prevention.

Keywords: aging society, disaster prevention, GIS, resilient, Taiwan

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Authors: Keigh D. Guinto, Ma. Romina M. Santos

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One of the most catastrophic natural disasters in the Philippines is floods. Twelve (12) million people reside in Metro Manila, National Capital Region (NCR), prone to flooding. A flood can cause widespread devastation resulting in damaged properties and infrastructures and loss of life. By using the analytical hierarchy process, six (6) parameters were selected, namely elevation, slope, lithology, distance from the river, river network density, and flow accumulation. Ranking of these parameters demonstrates that distance from the river with 25.31% and river density with 17.30% ranked the highest causative factor to flooding. This is followed by flow accumulation with 16.72%, elevation with 15.33%, slope with 13.53%, and the least flood causative factor is lithology with 11.8%. The generated flood susceptibility map of Mandaluyong has three (3) classes: high susceptibility, moderate susceptibility, and low susceptibility. The flood susceptibility map generated in this study can be used as an aid for planning flood mitigation, land use planning, and general public awareness. This study can also be used for emergency management and can be applied in the disaster risk management of Mandaluyong.

Keywords: analytical hierarchy process, assessment, flood, geographic information system

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Authors: Luojie Tang

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The article takes the "7.20 Heavy Rainstorm in Zhengzhou" as a starting point, collects relevant disaster data, reproduces the entire process of the disaster, and identifies the main problems exposed by the city in responding to super-standard rain and flood disasters. Based on the review of resilience theory, the article proposes a shift in thinking about the response to super-standard rain and flood disasters from the perspective of resilience, clarifies the differences in the emphasis on resilience at different stages of disasters, and preliminarily constructs a response system for super-standard rain and flood disasters based on the guidance of resilience theory. Finally, combined with the highlighted problems in the 7.20 Heavy Rainstorm in Zhengzhou, the article proposes targeted response strategies from three perspectives: institutional management, technological support, and infrastructure, under the perspective of resilience.

Keywords: resilient city, exceedance-based stormwater management, disaster risk reduction, megalopolis

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Authors: Freddy Houndekindo

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A study was carried out to evaluate the flood risk in the district of Malanville located along the Niger River. The knowledge produce by this study is useful in the implementation of adaptation and/or mitigation measures to alleviate the impact of the flooding on the populations, the economy and the environment. Over the course of the study, the lack of data in the area of interest has been one of the main challenges encountered. Therefore, in the analysis of the flood hazard different sources of remotely sensed data were used. Moreover, the flood hazard was analysed by applying a 1D hydraulic model: HEC-RAS. After setting up the model for the study area, the different flood scenarios considered were simulated and mapped using ArcGIS and the HEC-GEORAS extension. The result of the simulation gave information about the inundated areas and the water depths at each location. From the analysis of the flood hazard, it was found that between 47% and 50% of the total area of the district of Malanville would be flooded in the different flood scenarios considered, and the water depth varies between 1 and 7 m. The townships of Malanville most at risk of flooding are Momkassa and Galiel, located in a high-risk and very high-risk zone, respectively. Furthermore, the assessment of the flood risk showed that the most vulnerable sector to the inundations is the agricultural sector. Indeed, the cultivated floodplains were the most affected areas by the floodwater in every flood scenarios. Knowing that a high proportion of the population of the district relies on their farmlands in these floodplains for their livelihood, the floods pose a challenge not only to the food security in the area but also to its development.

Keywords: flood risk management, Niger, remote sensing, vulnerability

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Authors: Pırıl Tekin, Rızvan Erol

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Risk management has become very important and popular in developing countries in recent years. Especially making patient and employee health and safety issues compulsory in the hospitals, raised the number of studies in Turkey. Also risk management become more important for hospital senior management from clinics to the laboratories. Because quality is really important to be chosen for both patients to consult and employees to prefer to work. And also risk management studies can lead to hospital management team about future works and methods. By this point of view, this study is the risk assessment carried out in the biggest dental hospital in the south part of Turkey. This study was conducted as a research case study, covering two different health care place; A Clinic and A Laboratory. It shows that the problems in this dental hospital and how it can solve all.

Keywords: risk management, healthcare, dental hospital, quality management

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Authors: Haykal. Kay-Anne

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The health and well-being of students is a priority for the Faculty of Medicine at the University of Ottawa. The demands of medical studies are extreme, and many studies confirm that the prevalence of psychological distress is very high among medical students and that it is higher than that of the general population of the same age. The main goal is to identify risk factors for mental health among medical students at the University of Ottawa. The secondary objectives are to determine the variation of these risk factors according to demographic variables, as well as to determine if there is a change in the mental health of students during the 1st and 3rd years of their study. Medical students have a mandatory first and third-year wellness check meeting. This assessment includes a questionnaire on demographic information, mental health, and risk factors such as physical health, sleep, social support, financial stress, education and career, stress and drug use and/or alcohol. Student responses were converted to numerical values and analyzed statistically. The results show that 61% of the variation in the mean of the mental health score is explained by the following risk factors (R2 = 0.61, F (9.396) = 67.197, p < 0.01): lack of sleep and fatigue (β = 0.281, p < 0.001), lack of social support (β = 0.217, p <0.001), poor study or career development (β = 0.195, p < 0.001) and an increase stress and drug and alcohol use (β = -0.239, p < 0.001). No demographic variable has a significant effect on the presence of risk factors. In addition, fixed-effects regression demonstrated significantly lower mental health (p < 0.1) among first-year students (M = 0.587, SD = 0.072) than among third-year students (M = 0.719, SD = 0.071). This preliminary study indicates the need to continue data collection and analysis to increase the significance of the study results. As risk factors are present at the beginning of medical studies, it is important to offer resources to students very early in their medical studies and to have close monitoring and supervision.

Keywords: assessment of mental health, medical students, risk factors for mental health, wellness assessment

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Authors: Guldana Zhigerbayeva, Ming Yang

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Transportation of hazardous materials (HAZMAT) is inevitable in the process industries. The statistics show a significant number of accidents has occurred during the transportation of HAZMAT. This makes risk management of HAZMAT transportation an important topic. The tree-based methods including fault-trees, event-trees and cause-consequence analysis, and Bayesian network, have been applied to risk management of HAZMAT transportation. However, there is limited work on the development of a systematic approach. The existing approaches fail to build up the linkages between the regulatory requirements and the safety measures development. The analysis of historical data from the past accidents’ report databases would limit our focus on the specific incidents and their specific causes. Thus, we may overlook some essential elements in risk management, including regulatory compliance, field expert opinions, and suggestions. A systematic approach is needed to translate the regulatory requirements of HAZMAT transportation into specified safety measures (both technical and administrative) to support the risk management process. This study aims to first adapt the House of Quality (HoQ) to House of Safety (HoS) and proposes a new approach- Safety Function Deployment (SFD). The results of SFD will be used in a multi-criteria decision-support system to develop find an optimal route for HazMats transportation. The proposed approach will be demonstrated through a hypothetical transportation case in Kazakhstan.

Keywords: hazardous materials, risk assessment, risk management, quality function deployment

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Authors: Chaiyaset Promsri

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Based on the synthesis of related literatures, this research found thirteen related dimensions that involved the development of natural disaster preparedness awareness including hazard knowledge, hazard attitude, training for disaster preparedness, rehearsal and practice for disaster preparedness, cultural development for preparedness, public relations and communication, storytelling, disaster awareness game, simulation, past experience to natural disaster, information sharing with family members, and commitment to the community (time of living).  The 40-item of natural disaster preparedness awareness questionnaire was developed based on these thirteen dimensions. Data were collected from 595 participants in Bangkok metropolitan and vicinity. Cronbach's alpha was used to examine the internal consistency for this instrument. Reliability coefficient was 97, which was highly acceptable.  Exploratory Factor Analysis where principal axis factor analysis was employed. The Kaiser-Meyer-Olkin index of sampling adequacy was .973, indicating that the data represented a homogeneous collection of variables suitable for factor analysis. Bartlett's test of Sphericity was significant for the sample as Chi-Square = 23168.657, df = 780, and p-value < .0001, which indicated that the set of correlations in the correlation matrix was significantly different and acceptable for utilizing EFA. Factor extraction was done to determine the number of factors by using principal component analysis and varimax.  The result revealed that four factors had Eigen value greater than 1 with more than 60% cumulative of variance. Factor #1 had Eigen value of 22.270, and factor loadings ranged from 0.626-0.760. This factor was named as "Knowledge and Attitude of Natural Disaster Preparedness".  Factor #2 had Eigen value of 2.491, and factor loadings ranged from 0.596-0.696. This factor was named as "Training and Development". Factor #3 had Eigen value of 1.821, and factor loadings ranged from 0.643-0.777. This factor was named as "Building Experiences about Disaster Preparedness".  Factor #4 had Eigen value of 1.365, and factor loadings ranged from 0.657-0.760. This was named as "Family and Community". The results of this study provided support for the reliability and construct validity of natural disaster preparedness awareness for utilizing with populations similar to sample employed.

Keywords: natural disaster, disaster preparedness, disaster awareness, Thai citizens

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Authors: Saeed Pourhassan, Nastaran Maghbouli

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Statement of the problem: The relationship between obesity and cardiovascular diseases has been studied widely(1). The distribution of fat tissue gained attention in relation to cardiovascular risk factors during lang-time research (2). American College of Cardiology/American Heart Association (ACC/AHA) is widely and the most reliable tool to be used as a cardiovascular risk (CVR) assessment tool(3). This study aimed to determine which anthropometric index is better in discrimination of high CVR patients from low risks using ACC/AHA score in addition to finding the best index as a CVR predictor among both genders in different races and countries. Methodology & theoretical orientation: The literature in PubMed, Scopus, Embase, Web of Science, and Google Scholar were searched by two independent investigators using the keywords "anthropometric indices," "cardiovascular risk," and "obesity." The search strategy was limited to studies published prior to Jan 2022 as full-texts in the English language. Studies using ACC/AHA risk assessment tool as CVR and those consisted at least 2 anthropometric indices (ancient ones and novel ones) are included. Study characteristics and data were extracted. The relative risks were pooled with the use of the random-effect model. Analysis was repeated in subgroups. Findings: Pooled relative risk for 7 studies with 16,348 participants were 1.56 (1.35-1.72) for BMI, 1.67(1.36-1.83) for WC [waist circumference], 1.72 (1.54-1.89) for WHR [waist-to-hip ratio], 1.60 (1.44-1.78) for WHtR [waist-to-height ratio], 1.61 (1.37-1.82) for ABSI [A body shape index] and 1.63 (1.32-1.89) for CI [Conicity index]. Considering gender, WC among females and WHR among men gained the highest RR. The heterogeneity of studies was moderate (α²: 56%), which was not decreased by subgroup analysis. Some indices such as VAI and LAP were evaluated just in one study. Conclusion & significance: This meta-analysis showed WHR could predict CVR better in comparison to BMI or WHtR. Some new indices like CI and ABSI are less accurate than WHR and WC. Among women, WC seems to be a better choice to predict cardiovascular disease risk.

Keywords: obesity, cardiovascular disease, risk assessment, anthropometric indices

Procedia PDF Downloads 78

Authors: Bronwen Wade

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Over the last half-century, child welfare systems have increasingly relied on quantitative risk assessment tools, such as actuarial or predictive risk tools. These tools are developed by performing statistical analysis of how attributes captured in administrative data are related to future child maltreatment. Some scholars argue that attributes in administrative data can serve as proxies for race and that quantitative risk assessment tools reify racial bias in decision-making. Others argue that these tools provide more “objective” and “scientific” guides for decision-making instead of subjective social worker judgment. This study performs a systematic review of the literature on the impact of quantitative risk assessment tools on racial disproportionality; it examines methodological biases in work on this topic, summarizes key findings, and provides suggestions for further work. A search of CINAHL, PsychInfo, Proquest Social Science Premium Collection, and the ProQuest Dissertations and Theses Collection was performed. Academic and grey literature were included. The review includes studies that use quasi-experimental methods and development, validation, or re-validation studies of quantitative risk assessment tools. PROBAST (Prediction model Risk of Bias Assessment Tool) and CHARMS (CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies) were used to assess the risk of bias and guide data extraction for risk development, validation, or re-validation studies. ROBINS-I (Risk of Bias in Non-Randomized Studies of Interventions) was used to assess for bias and guide data extraction for the quasi-experimental studies identified. Due to heterogeneity among papers, a meta-analysis was not feasible, and a narrative synthesis was conducted. 11 papers met the eligibility criteria, and each has an overall high risk of bias based on the PROBAST and ROBINS-I assessments. This is deeply concerning, as major policy decisions have been made based on a limited number of studies with a high risk of bias. The findings on racial disproportionality have been mixed and depend on the tool and approach used. Authors use various definitions for racial equity, fairness, or disproportionality. These concepts of statistical fairness are connected to theories about the reason for racial disproportionality in child welfare or social definitions of fairness that are usually not stated explicitly. Most findings from these studies are unreliable, given the high degree of bias. However, some of the less biased measures within studies suggest that quantitative risk assessment tools may worsen racial disproportionality, depending on how disproportionality is mathematically defined. Authors vary widely in their approach to defining and addressing racial disproportionality within studies, making it difficult to generalize findings or approaches across studies. This review demonstrates the power of authors to shape policy or discourse around racial justice based on their choice of statistical methods; it also demonstrates the need for improved rigor and transparency in studies of quantitative risk assessment tools. Finally, this review raises concerns about the impact that these tools have on child welfare systems and racial disproportionality.

Keywords: actuarial risk, child welfare, predictive risk, racial disproportionality

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Authors: Majid Bayatian, Mohammadreza Ashouri

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Releasing hazardous chemicals is one of the major problems for office buildings in the chemical industry and, therefore, environmental risks are inherent to these environments. The adverse health effects of the airborne concentration of benzene have been a matter of significant concern, especially in oil refineries. The chronic and acute adverse health effects caused by benzene exposure have attracted wide attention. Acute exposure to benzene through inhalation could cause headaches, dizziness, drowsiness, and irritation of the skin. Chronic exposures have reported causing aplastic anemia and leukemia at the occupational settings. Association between chronic occupational exposure to benzene and the development of aplastic anemia and leukemia were documented by several epidemiological studies. Numerous research works have investigated benzene emissions and determined benzene concentration at different locations of the refinery plant and stated considerable health risks. The high cost of industrial control measures requires justification through lifetime health risk assessment of exposed workers and the public. In the present study, a Computational Fluid Dynamics (CFD) model has been proposed to assess the exposure risk of office building around a refinery due to its release of benzene. For simulation, GAMBIT, FLUENT, and CFD Post software were used as pre-processor, processor, and post-processor, and the model was validated based on comparison with experimental results of benzene concentration and wind speed. Model validation results showed that the model is highly validated, and this model can be used for health risk assessment. The simulation and risk assessment results showed that benzene could be dispersion to an office building nearby, and the exposure risk has been unacceptable. According to the results of this study, a validated CFD model, could be very useful for decision-makers for control measures and possibly support them for emergency planning of probable accidents. Also, this model can be used to assess exposure to various types of accidents as well as other pollutants such as toluene, xylene, and ethylbenzene in different atmospheric conditions.

Keywords: health risk assessment, office building, Benzene, numerical simulation, CFD

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Authors: Hafiz Muhammad Tayyab Bhatti, Munazza Usmani

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One of nature's most destructive occurrences, floods do immense damage to communities and economic losses. Nigeria country, specifically southern Nigeria, is known for being prone to flooding. Even though periodic flooding occurs in Nigeria frequently, the floods of 2022 were the worst since those in 2012. Flood vulnerability analysis and mapping are still lacking in this region due to the very limited historical hydrological measurements and surveys on the effects of floods, which makes it difficult to develop and put into practice efficient flood protection measures. Remote sensing and Geographic Information Systems (GIS) are useful approaches to detecting, determining, and estimating the flood extent and its impacts. In this study, NOAA VIIR has been used to extract the flood extent using the flood water fraction data and afterward fused with GIS data for some zonal statistical analysis. The estimated possible flooding areas are validated using satellite imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS). The goal is to map and studied flood extent, flood hazards, and their effects on the population, schools, and health facilities for each state of Nigeria. The resulting flood hazard maps show areas with high-risk levels clearly and serve as an important reference for planning and implementing future flood mitigation and control strategies. Overall, the study demonstrated the viability of using the chosen GIS and remote sensing approaches to detect possible risk regions to secure local populations and enhance disaster response capabilities during natural disasters.

Keywords: flood hazards, remote sensing, damage assessment, GIS, geospatial analysis

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Authors: Jessy Rugeyo, William Donner

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This research delves into the resilience of Rwanda's public health infrastructure amidst natural disasters, a critical issue given that the Northern Province alone has witnessed no fewer than 1500 cases of disaster ranging from floods and landslides in the last five years, with more than 200 people killed and thousands of homes destroyed, according to MINEMA. In an era where climate change escalates the frequency and intensity of such disasters, fortifying the resilience of public health systems is paramount. This study offers a comprehensive analysis of the existing state of Rwanda's public health infrastructure and its ability to manage such crises. Employing a mix of literature review, case studies, and policy analysis, the study discerns key vulnerabilities and brings to light the intricacies of disaster management in Rwanda. Case studies centered around past natural disasters in Rwanda provide critical insights into the strengths and weaknesses of the existing disaster response mechanisms. A thorough critique of related disaster management and public health infrastructure policies reveals areas of commendable practice, along with gaps calling for policy enhancements. Findings guide the proposition of targeted strategies to bolster the resilience of Rwanda's public health infrastructure. This research serves as a significant contribution to the domains of disaster studies and public health, offering valuable insights for policymakers, public health and disaster management professionals in Rwanda and similar contexts. It presents actionable recommendations for improvement, underscoring the potential for enhancing Rwanda's disaster management capacity. By advocating for the strengthening of public health infrastructure resilience, the research highlights the potential for improved public health outcomes following natural disasters, thereby showcasing significant implications for public health and disaster management in the country, particularly in the face of a changing climate.

Keywords: public health infrastructure, disaster resilience, natural disaster, disaster management, emergency preparedness, health policy

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Authors: Haïfa Ben Mna, Ayed Added

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To evaluate the trace metals contamination status in the Gulf of Tunis, forty one sediment samples were analyzed using different approaches. According to certain contamination and ecological risk indices (Contamination Factor, Geoaccumulation index and Ecological risk index), Hg has the highest contamination level while pollution by Ni, Pb, Cd and Cr was absent. The highest concentrations of trace metals were found in sediments collected from the offshore and coastal areas located opposite the main exchange points with the gulf particularly, the Mejerda and Meliane Rivers, the Khalij Channel, Ghar El Melh and El Malah lagoons, Tunis Lake and Sebkhat Ariana. However, further ecological indices (Potential ecological risk index, Toxic unit and Mean effect-range median quotient) and comparison with sediment quality guidelines suggest that in addition to Mercury, Cr, Pb and Ni concentrations are detrimental to biota in both the offshore and areas near to the exchange points with the gulf. Moreover, in these areas the results from sequential extraction and individual contamination factor calculation pointed to the mobility and bioavailability of Cr, Pb and Ni.

Keywords: sediment, trace metals, contamination assessment, ecological risk, Tunis gulf

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Authors: N. Nivedita, S. Durbha

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Critical Infrastructure (CI) consists of services and technological networks such as healthcare, transport, water supply, electricity supply, information technology etc. These systems are necessary for the well-being and to maintain effective functioning of society. Critical Infrastructures can be represented as nodes in a network where they are connected through a set of links depicting the logical relationship among them; these nodes are interdependent on each other and interact with each at other at various levels, such that the state of each infrastructure influences or is correlated to the state of another. Disruption in the service of one infrastructure nodes of the network during a disaster would lead to cascading and escalating disruptions across other infrastructures nodes in the network. The operation of Healthcare Infrastructure is one such Critical Infrastructure that depends upon a complex interdependent network of other Critical Infrastructure, and during disasters it is very vital for the Healthcare Infrastructure to be protected, accessible and prepared for a mass casualty. To reduce the consequences of a disaster on the Critical Infrastructure and to ensure a resilient Critical Health Infrastructure network, knowledge, understanding, modeling, and analyzing the inter-dependencies between the infrastructures is required. The paper would present inter-dependencies related to Healthcare Critical Infrastructure based on Hierarchical Coloured Petri Nets modeling approach, given a flood scenario as the disaster which would disrupt the infrastructure nodes. The model properties are being analyzed for the various state changes which occur when there is a disruption or damage to any of the Critical Infrastructure. The failure probabilities for the failure risk of interconnected systems are calculated by deriving a reachability graph, which is later mapped to a Markov chain. By analytically solving and analyzing the Markov chain, the overall vulnerability of the Healthcare CI HCPN model is demonstrated. The entire model would be integrated with Geographic information-based decision support system to visualize the dynamic behavior of the interdependency of the Healthcare and related CI network in a geographically based environment.

Keywords: critical infrastructure interdependency, hierarchical coloured petrinet, healthcare critical infrastructure, Petri Nets, Markov chain

Procedia PDF Downloads 495

Authors: Bibiana Matilde Bernal Gómez, Manuel Salvador Rodríguez Susa, Mildred Fernanda Lemus Perez

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In chlorinated drinking water, Haloacetic acids have been identified and are classified as disinfection byproducts originating from reaction between natural organic matter and/or bromide ions in water sources. These byproducts can be generated through a variety of chemical and pharmaceutical processes. The term ‘Total Haloacetic Acids’ (THAAs) is used to describe the cumulative concentration of dichloroacetic acid, trichloroacetic acid, monochloroacetic acid, monobromoacetic acid, and dibromoacetic acid in water samples, which are usually measured to evaluate water quality. Chronic presence of these acids in drinking water has a risk of cancer in humans. The detection of THAAs for the first time in 15 municipalities of Boyacá was accomplished in 2023. Aim is to describe the correlation between the levels of THAAs and digestive cancer in Tunja, a city in Colombia with higher rates of digestive cancer and to compare the risk across 15 towns, taking into account factors such as water quality. A research project was conducted with the aim of comparing water sources based on the geographical features of the town, describing the disinfection process in 15 municipalities, and exploring physical properties such as water temperature and pH level. The project also involved a study of contact time based on habits documented through a survey, and a comparison of socioeconomic factors and lifestyle, in order to assess the personal risk of exposure. Data on the levels of THAAs were obtained after characterizing the water quality in urban sectors in eight months of 2022. This, based on the protocol described in the Stage 2 DBP of the United States Environmental Protection Agency (USEPA) from 2006, which takes into account the size of the population being supplied. A cancer risk assessment was conducted to evaluate the likelihood of an individual developing cancer due to exposure to pollutants THAAs. The assessment considered exposure methods like oral ingestion, skin absorption, and inhalation. The chronic daily intake (CDI) for these exposure routes was calculated using specific equations. The lifetime cancer risk (LCR) was then determined by adding the cancer risks from the three exposure routes for each HAA. The risk assessment process involved four phases: exposure assessment, toxicity evaluation, data gathering and analysis, and risk definition and management. The results conclude that there is a cumulative higher risk of digestive cancer due to THAAs exposure in drinking water.

Keywords: haloacetic acids, drinking water, water quality, cancer risk assessment

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Authors: Vinu Elias Jacob, Manoj Kumar Kini

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Disasters of all types are occurring more frequently and are becoming more costly than ever due to various manmade factors including climate change. A better utilisation of the concept of governance and management within disaster risk reduction is inevitable and of utmost importance. There is a need to explore the role of pre- and post-disaster public policies. The role of urban planning/design in shaping the opportunities of households, individuals and collectively the settlements for achieving recovery has to be explored. Governance strategies that can better support the integration of disaster risk reduction and management has to be examined. The main aim is to thereby build the resilience of individuals and communities and thus, the states too. Resilience is a term that is usually linked to the fields of disaster management and mitigation, but today has become an integral part of planning and design of cities. Disaster resilience broadly describes the ability of an individual or community to 'bounce back' from disaster impacts, through improved mitigation, preparedness, response, and recovery. The growing population of the world has resulted in the inflow and use of resources, creating a pressure on the various natural systems and inequity in the distribution of resources. This makes cities vulnerable to multiple attacks by both natural and man-made disasters. Each urban area needs elaborate studies and study based strategies to proceed in the discussed direction. Cochin in Kerala is the fastest and largest growing city with a population of more than 26 lakhs. The main concern that has been looked into in this paper is making cities resilient by designing a framework of strategies based on urban design principles for an immediate response system especially focussing on the city of Cochin, Kerala, India. The paper discusses, understanding the spatial transformations due to disasters and the role of spatial planning in the context of significant disasters. The paper also aims in developing a model taking into consideration of various factors such as land use, open spaces, transportation networks, physical and social infrastructure, building design, and density and ecology that can be implemented in any city of any context. Guidelines are made for the smooth evacuation of people through hassle-free transport networks, protecting vulnerable areas in the city, providing adequate open spaces for shelters and gatherings, making available basic amenities to affected population within reachable distance, etc. by using the tool of urban design. Strategies at the city level and neighbourhood level have been developed with inferences from vulnerability analysis and case studies.

Keywords: disaster management, resilience, spatial planning, spatial transformations

Procedia PDF Downloads 261

Authors: Sara Hasani

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This research focuses on natural sudden onset disasters characterised as ‘occurring with little or no warning and often cause excessive injuries far surpassing the national response capacities’. Based on the panel analysis of the historic record of 4,252 natural onset disasters between 1980 to 2015, a predictive method was developed to predict the human impact of the disaster (fatality, injured, homeless) with less than 3% of errors. The geographical dispersion of the disasters includes every country where the data were available and cross-examined from various humanitarian sources. The records were then filtered into 4252 records of the disasters where the five predictive variables (disaster type, HDI, DRI, population, and population density) were clearly stated. The procedure was designed based on a combination of pattern recognition techniques and rule-based clustering for prediction and discrimination analysis to validate the results further. The result indicates that there is a relationship between the disaster human impact and the five socio-economic characteristics of the affected country mentioned above. As a result, a framework was put forward, which could predict the disaster’s human impact based on their severity rank in the early hours of disaster strike. The predictions in this model were outlined in two worst and best-case scenarios, which respectively inform the lower range and higher range of the prediction. A necessity to develop the predictive framework can be highlighted by noticing that despite the existing research in literature, a framework for predicting the human impact and estimating the needs at the time of the disaster is yet to be developed. This can further be used to allocate the resources at the response phase of the disaster where the data is scarce.

Keywords: disaster management, natural disaster, pattern recognition, prediction

Procedia PDF Downloads 128

Authors: Henry Pariaman, Iwa Garniwa, Isti Surjandari, Bambang Sugiarto

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Availability of a complex system of thermal power plant is strongly influenced by the reliability of spare parts and maintenance management policies. A reliability-centered maintenance (RCM) technique is an established method of analysis and is the main reference for maintenance planning. This method considers the consequences of failure in its implementation, but does not deal with further risk of down time that associated with failures, loss of production or high maintenance costs. Risk-based maintenance (RBM) technique provides support strategies to minimize the risks posed by the failure to obtain maintenance task considering cost effectiveness. Meanwhile, condition-based maintenance (CBM) focuses on monitoring the application of the conditions that allow the planning and scheduling of maintenance or other action should be taken to avoid the risk of failure prior to the time-based maintenance. Implementation of RCM, RBM, CBM alone or combined RCM and RBM or RCM and CBM is a maintenance technique used in thermal power plants. Implementation of these three techniques in an integrated maintenance will increase the availability of thermal power plants compared to the use of maintenance techniques individually or in combination of two techniques. This study uses the reliability, risks and conditions-based maintenance in an integrated manner to increase the availability of thermal power plants. The method generates MPI (Priority Maintenance Index) is RPN (Risk Priority Number) are multiplied by RI (Risk Index) and FDT (Failure Defense Task) which can generate the task of monitoring and assessment of conditions other than maintenance tasks. Both MPI and FDT obtained from development of functional tree, failure mode effects analysis, fault-tree analysis, and risk analysis (risk assessment and risk evaluation) were then used to develop and implement a plan and schedule maintenance, monitoring and assessment of the condition and ultimately perform availability analysis. The results of this study indicate that the reliability, risks and conditions-based maintenance methods, in an integrated manner can increase the availability of thermal power plants.

Keywords: integrated maintenance techniques, availability, thermal power plant, MPI, FDT

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Authors: Masoud Ghahvechi Pour

Abstract:

Risk management is a systematic and regular process of identifying, analyzing and responding to risks throughout the project's life cycle in order to achieve the optimal level of elimination, reduction or control of risk. The purpose of project risk management is to increase the probability and effect of positive events and reduce the probability and effect of unpleasant events on the project. Risk management is one of the most fundamental parts of project management, so that unmanaged or untransmitted risks can be one of the primary factors of failure in a project. Effective risk management does not apply to risk regression, which is apparently the cheapest option of the activity. However, the main problem with this option is the economic sensitivity, because what is potentially profitable is by definition risky, and what does not pose a risk is economically interesting and does not bring tangible benefits. Therefore, in relation to the implemented project, effective risk management is finding a "middle ground" in its management, which includes, on the one hand, protection against risk from a negative direction by means of accurate identification and classification of risk, which leads to analysis And it becomes a comprehensive analysis. On the other hand, management using all mathematical and analytical tools should be based on checking the maximum benefits of these decisions. Detailed analysis, taking into account all aspects of the company, including stakeholder analysis, will allow us to add what will become tangible benefits for our project in the future to effective risk management. Identifying the risk of the project is based on the theory that which type of risk may affect the project, and also refers to specific parameters and estimating the probability of their occurrence in the project. These conditions can be divided into three groups: certainty, uncertainty, and risk, which in turn support three types of investment: risk preference, risk neutrality, specific risk deviation, and its measurement. The result of risk identification and project analysis is a list of events that indicate the cause and probability of an event, and a final assessment of its impact on the environment.

Keywords: risk, management, knowledge, risk management

Procedia PDF Downloads 29