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The operational management of Water Distribution Systems (WDS), particularly under failure conditions when the behaviour of a WDS is not well understood, is a challenging problem. The research presented in this thesis describes the development of a methodology for risk-based diagnostics of failures in WDS and its application in a near real-time Decision Support System (DSS) for WDS’ operation. In this thesis, the use of evidential reasoning to estimate the likely location of a burst pipe within a WDS by combining outputs of several models is investigated. A novel Dempster-Shafer model is developed, which fuses evidence provided by a pipe burst prediction model, a customer contact model and a hydraulic model to increase confidence in correctly locating a burst pipe. A new impact model, based on a pressure driven hydraulic solver coupled with a Geographic Information System (GIS) to capture the adverse effects of failures from an operational perspective, is created. A set of Key Performance Indicators used to quantify impact, are aggregated according to the preferences of a Decision Maker (DM) using the Multi-Attribute Value Theory. The potential of distributed computing to deliver a near real-time performance of computationally expensive impact assessment is explored. A novel methodology to prioritise alarms (i.e., detected abnormal flow events) in a WDS is proposed. The relative significance of an alarm is expressed using a measure of an overall risk represented by a set of all potential incidents (e.g., pipe bursts), which might have caused it. The DM’s attitude towards risk is taken into account during the aggregation process. The implementation of the main constituents of the proposed risk-based pipe burst diagnostics methodology, which forms a key component of the aforementioned DSS prototype, are tested on a number of real life and semi-real case studies. The methodology has the potential to enable more informed decisions to be made in the near real-time failure management in WDS.

Background/Purpose: The American College of Cardiology/American Heart Association/Heart Failure Society of America guidelines for management of heart failure were recently updated to include use of sacubitril/valsartan due to its ability to reduce mortality and hospitalizations over the current standard of therapy. Based on these guideline updates, a champion research team at East Tennessee State University (ETSU) Family Medicine Associates worked to create and implement a process that identified patients with systolic heart failure and provided access to medications with mortality and morbidity benefits. The objective of this study is to improve provider knowledge of evidence-based heart failure pharmacotherapy and to assess provider acceptability of a process implemented at ETSU Family Medicine Associates. Methodology: This study was approved by the Institutional Review Board. On December 21, 2016 the champion research team presented a didactic session to all providers at ETSU Family Medicine Associates. Immediately prior to the education session, providers completed a pre-education clinical knowledge assessment on heart failure pharmacotherapy. A one-hour didactic session then followed focusing on evidence-based medication management of systolic heart failure and introduction of the new process being implemented. Following the presentation, providers completed a post-education clinical knowledge assessment and a pre-implementation process acceptability survey. Providers were then scheduled to complete a post-implementation process acceptability survey at two months post-process implementation and quarterly thereafter. A McNemars Test will be used to determine if statistically significant differences exist among pre- and post-education clinical knowledge assessments and pre- and post-implementation process acceptability surveys. Presentation Objective: Discuss the process implemented to improve provider knowledge of heart failure pharmacotherapy and improve patient access to evidence-based pharmacotherapy options. Self-Assessment: Did the one-hour didactic session improve provider knowledge of heart failure pharmacotherapy?

In Nigeria, 50% to 70% of construction projects are delayed due to unexpected events that are linked to lapses in performance, near misses, and surprises. While researchers have theorized on the impact of mindfulness and information systems management (ISM) on unexpected events, information is lacking on how project teams can combine ISM and mindfulness in response to unexpected events in construction projects. The purpose of this case study was to examine how project teams can combine mindfulness with ISM in response to unexpected events during the execution phase of Nigerian construction projects. The framework of High Reliability Theory revealed that unexpected events could be minimized by mindfulness defined by 5 cognitive processes: preoccupation with failure, reluctance to simplify, sensitivity to operations, commitment to resilience, and deference to expertise. In-depth semi-structured interviews elicited the views of 24 project experts on team behaviors, tactics, and processes for combining mindfulness with ISM. Data analysis was conducted by open coding to identify and reduce data into themes, and axial coding was used to identify and isolate categories. Findings were that project teams could combine mindfulness with ISM in response to unexpected events by integrating effective risk, team, and communication management with appropriate training and technology infrastructure. If policymakers, project clients, and practitioners adopt practices suggested in this study, the implications for social change are that project management practices, organizational learning, and the performance of construction projects may improve, construction wastes may be reduced, and taxpayers may derive optimum benefits from public funds committed to construction projects.

[ES] La definición que entrega el diccionario de la Real Academia Española de la Lengua sobre Epidemiología indica que ésta es una ciencia y como tal, tiene aquellos elementos propios de un conjunto sistematizado de conocimientos entre los que se destaca la metodología, aquella que analiza los procedimientos usados en el objeto de estudio. Desde el surgimiento del ser humano se ha podido evidenciar, a lo largo de la historia, cómo se ha hecho uso del agua en el abastecimiento tanto a nivel de sustento y salud, como en el nivel industrial. Igualmente, se puede evidenciar la evolución de la epidemiología para analizar las enfermedades que principalmente se transmiten por aguas contaminadas y cómo la metodología ha hecho avances tan significativos que permiten predecir el comportamiento de los patógenos y mitigar las consecuencias de un posible contagio. El desarrollo de la epidemiología se ha volcado principalmente en el área de la medicina en la cual ha mostrado una enorme evolución al afrontar grandes retos como la propagación de las enfermedades infecciosas y el replanteamiento continuo de los modelos de análisis. No obstante, esta ciencia se puede adaptar a cualquier área del conocimiento humano como la gestión de los recursos hídricos y más concretamente en la gestión de las redes de abastecimiento de agua urbana. La puesta en marcha de una red de abastecimiento de agua en una ciudad, cuyas dimensiones y construcción generalmente son monumentales, implica un diseño y una operabilidad que surge de la aplicación de modelos matemáticos y/o estadísticos, los cuales permiten analizar las distintas condiciones de funcionamiento antes de iniciar obras. Ese comportamiento puede caracterizarse a partir de métodos de resolución basados en los procedimientos epidemiológicos y que han sido contrastados ampliamente en forma empírica y funcional. En toda red de suministro existen dos componentes independientes e interdependientes, como lo son la gestión de la demanda y la gestión de fallos. En ambos hay incertidumbres que, generalmente, provienen de variables externas, aleatorias, que dificultan su cuantificación y por lo mismo, su predicción. Para la gestión de la demanda, resulta importante la aplicación de modelos de estimación de la demanda precisos, pues con ellos se pueden determinar las capacidades y cargas que soporte la red. A la par, para la gestión de fallos en las redes, resultan importantes modelos de estimación precisos que ayuden a mitigar el impacto de contingencias generadas por fallos en cascada y la propagación de éstos hasta un posible colapso. En los procesos de gestión de demanda se vienen utilizando principalmente los modelos de series temporales, llegando a la aplicación de modelos que impliquen el algoritmo SAX. En los procesos de gestión de fallos se han aplicado métodos como el análisis de supervivencia y más recientemente, las redes neuronales, llegando a los sistemas multiagente con los modelos SIR, SIRS y SEIR. El desarrollo de los modelos SAX se pueden apreciar en un caso de estudio de la ciudad de Franca en Brasil, en la que se combinan patrones de similitud entre sectores con patrones de las MINDIST que respaldan los métodos predictivos, mejorando su precisión y facilitando la detección de lecturas anormales en los medidores de flujo e incluso la presencia de usos o fugas inesperados. El Modelo Basado en Agentes (MBA) se puede desarrollar mediante, por ejemplo, la herramienta NetLogo, y su aplicación en una red de suministro resulta muy efectiva para determinar el comportamiento de los posibles fallos en cascada; ejemplo de ello se aprecia en el caso de estudio de la ciudad de Coro en Venezuela en la que se pueden establecer momentos para cada comportamiento: susceptibilidad, infección (fallo) y recuperación; proporcionando así un modelo predictivo mejorado para este tipo de situaciones. / [CAT] La definició que lliura el diccionari de la Reial Acadèmia Espanyola de la Llengua sobre l'Epidemiologia indica que aquesta és una ciència i com a tal té aquells elements propis d'un conjunt sistematitzat de coneixements entre els quals es destaca la metodologia, aquella que analitza els procediments usats en l'objecte d'estudi. Des del sorgiment de l'ésser humà s'ha pogut evidenciar al llarg de la història, com s'ha fet ús de l'aigua en l'abastament tant pel que fa al suport i la salut, com al nivell industrial. Igualment, es pot evidenciar l'evolució de l'epidemiologia per analitzar les malalties que principalment es transmeten per aigües contaminades i com la metodologia ha fet avanços tan significatius que permeten predir el comportament dels patògens i mitigar les conseqüències d'un possible contagi. El desenvolupament de l'epidemiologia s'ha abocat principalment a l'àrea de la medicina on ha mostrat una enorme evolució en afrontar grans reptes com la propagació de les malalties infeccioses i el replantejament continu dels models d'anàlisi. Això no obstant, aquesta ciència es pot adaptar a qualsevol àrea del coneixement humà com la gestió dels recursos hídrics i més concretament en la gestió de les xarxes d'abastament d'aigua urbana. La posada en marxa d'una xarxa d'abastament d'aigua en una ciutat, les dimensions i la construcció de la qual generalment són monumentals, implica un disseny i una operativitat que sorgeix de l'aplicació de models matemàtics i/o estadístics, els quals permeten analitzar les diferents condicions de funcionament abans d'iniciar obres. Aquest comportament es pot caracteritzar a partir de mètodes de resolució basats en els procediments epidemiològics i que han estat contrastats àmpliament en forma empírica i funcional. En tota xarxa de subministrament hi ha dos components independents i interdependents, com ho són la gestió de la demanda i la gestió de fallades. En tots dos hi ha incerteses que generalment provenen de variables externes, aleatòries, que dificulten la quantificació i, per tant, la seva predicció. Per a la gestió de la demanda, és important l'aplicació de models d'estimació de la demanda precisos, ja que s'hi poden determinar les capacitats i les càrregues que suporti la xarxa. Alhora, per a la gestió d'errors a les xarxes, són importants els models d'estimació precisos que ajudin a mitigar l'impacte de contingències generades per errors en cascada i la propagació d'aquests fins a un possible col·lapse. En els processos de gestió de demanda, s'utilitzen principalment els models de sèries temporals, arribant a l'aplicació de models que impliquin l'algorisme SAX. En els processos de gestió de fallades s'han aplicat mètodes com l'anàlisi de supervivència i, més recentment, les xarxes neuronals; arribant als sistemes multiagent amb els models SIR, SIRS i SEIR. El desenvolupament dels models SAX es poden apreciar en un cas d'estudi de la ciutat de Franca al Brasil, en què es combinen patrons de similitud entre sectors amb patrons de MINDIST que donen suport als mètodes predictius millorant-ne la precisió i facilitant la detecció de lectures anormals als mesuradors de flux i fins i tot la presència d'usos o fugues inesperades. El Model Basat en Agents (MBA) es pot desenvolupar mitjançant l'eina NetLogo i la seva aplicació en una xarxa de subministrament resulta molt efectiva per determinar el comportament de les possibles fallades en cascada. Exemple d'això s'aprecia en el cas d'estudi de la ciutat de Coro a Veneçuela en què es poden establir moments per a cada comportament: susceptibilitat, infecció (fallida) i recuperació, proporcionant així un model predictiu millorat per a aquest tipus de situacions. / [EN] The definition of Epidemiology given by the dictionary of the Real Academia Española de la Lengua states that it is a science and, as such, it exhibits those elements of a systematized set of knowledge, among which the methodology, which analyzes the procedures used in the object of study, stands out. Since the emergence of the human being, it has been possible to demonstrate throughout history, how water has been used in supply at the level of both sustenance and health, as well as at the industrial level. Likewise, the evolution of epidemiology can be evidenced to analyze diseases that are mainly transmitted by contaminated water and how the methodology has made such significant advances that allow predicting the behavior of pathogens and mitigating the consequences of possible contagion. The development of epidemiology has focused mainly on the area of medicine, in which it has shown enormous evolution when facing great challenges such as the spread of infectious diseases and the continuous rethinking of analysis models. However, this science can be adapted to any area of human knowledge, such as the management of water resources and more specifically the management of urban water supply networks. Implementing a water supply network in a city, whose dimensions and construction are generally monumental, implies design and operability aspects that arise from applying mathematical and/or statistical models, which allow the analysis of the different conditions of operation before starting its operation. This behavior can be characterized by resolution methods based on epidemiological procedures, which have been widely contrasted empirically and functionally. In any supply network, there are two independent and interdependent components, such as demand management and fault management. In both, there are uncertainties that generally come from external, random variables, which make it difficult to quantify and therefore to predict. Regarding demand management, the application of accurate demand estimation models is essential, since the capacities and loads supported by the network can be determined by using them. At the same time, for network failure management, accurate estimation models are also key to help mitigate the impact of contingencies generated by cascading failures and their propagation until a possible collapse. In demand management processes, time series models have been mainly used, including the application of models that involve the SAX algorithm. In failure management processes, methods such as survival analysis and, more recently, neural networks have been applied; reaching multi-agent systems with the SIR, SIRS, and SEIR models. The development of SAX models can be seen in a case study from the city of Franca in Brazil, in which patterns of similarity between districts are combined with MINDIST patterns that support predictive methods, improving their accuracy and facilitating the detection of errors, abnormal readings on flow meters and even the presence of unexpected uses or leaks. The Agent-Based Model (MBA) can be developed using, for example, the NetLogo tool, and its application in a supply network is very effective in determining the behavior of possible cascading failures. An example can be seen in the case study of the city de Coro in Venezuela in which moments for each behavior can be established: susceptibility, infection (failure), and recovery. This provides an improved predictive model for this type of situation. / Navarrete López, CF. (2023). Metodologías epidemiológicas de análisis de datos para la operación y gestión de redes de abastecimiento urbano de agua [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/195739