Analytics and optimization for emergency healthcare processes

This thesis deals with the analysis and management of emergency healthcare processes through the use of advanced analytics and optimization approaches. Emergency processes are among the most complex within healthcare. This is due to their non-elective nature and their high variability. This thesis is divided into two topics. The first one concerns the core of emergency healthcare processes, the emergency department (ED). In the second chapter, we describe the ED that is the case study. This is a real case study with data derived from a large ED located in northern Italy. In the next two chapters, we introduce two tools for supporting ED activities. The first one is a new type of analytics model. Its aim is to overcome the traditional methods of analyzing the activities provided in the ED by means of an algorithm that analyses the ED pathway (organized as event log) as a whole. The second tool is a decision-support system, which integrates a deep neural network for the prediction of patient pathways, and an online simulator to evaluate the evolution of the ED over time. Its purpose is to provide a set of solutions to prevent and solve the problem of the ED overcrowding. The second part of the thesis focuses on the COVID-19 pandemic emergency. In the fifth chapter, we describe a tool that was used by the Bologna local health authority in the first part of the pandemic. Its purpose is to analyze the clinical pathway of a patient and from this automatically assign them a state. Physicians used the state for routing the patients to the correct clinical pathways. The last chapter is dedicated to the description of a MIP model, which was used for the organization of the COVID-19 vaccination campaign in the city of Bologna, Italy.

The role of technology at school: new perspectives on distance education and cyberbullying

The integration of digital technology in school is a complex phenomenon that affects both teaching and peer relationships. Accordingly, the main aim of this dissertation was to investigate the implementation of distance education among Italian teachers during the COVID-19 pandemic and analyze peer relationships concerning cyberbullying and bullying. While the theoretical section provided an overview of the phenomena, four empirical studies were presented. The first one tested a moderated moderation model among 178 secondary teachers on the interactions among perceived usefulness, perceived ease of use of technology and online teaching self-efficacy. Findings showed that each variable significantly predicted the intention to use technology. In addition, a moderation effect of online teaching self-efficacy on perceived usefulness was found. The second study analyzed the differences in factors promoting the integration of digital technology among 357 teachers of different levels and subjects and their positive and negative experiences with distance education. Results revealed several differences in the function of the grade and subjects taught. Moreover, four main themes emerged from the content analysis. The third study investigated the dyadic perception of bullying and cyberbullying among 50 students using the eye-tracker. Findings showed that, despite differences among different kinds of bullying and cyberbullying, the victim and bully were the most observed roles. Finally, the last study tested two multiple mediation models among 563 students on the association between bullying, cyberbullying, and well-being, considering three different variables related to the school context (peer network, teacher support and school connectedness). The results highlighted the importance of peer networks and school connectedness in mediating the association between victimization, cybervictimzation and well-being. Taken together, the findings provided a rich overview of digital technology integration in schools, highlighting positive and negative aspects and its implications for future research and school policies.

Essays in development and political economy

This thesis includes three papers studying diverse questions in development, economic history and political economy. The first two chapters, that fall under development and economic history, use novel forms of text data and analysis to answer the questions at hand. The first chapter studies the possible impact of a historically matrilineal and matrilocal caste group on present day outcomes of gender equality. It introduces a novel surname strategy using electoral data to deduce caste from the surnames of electors and overcomes the unavailability of caste data. It shows proof of persistence of caste in space. And finally, following a matching exercise it concludes that the effect of the matrilineal and matrilocal caste on present day gender outcomes might not be as strong as previously believed. The second paper studies how discriminatory fake news arises and spatially diffuses. It focuses on India at the onset of the COVID-19 pandemic: on March 30, a Muslim convention (the Tablighi Jamaat) in New Delhi became publicly recognized as a COVID hotspot, and the next day, fake news on Muslims intentionally spreading the virus spiked. Using Twitter data, it finds, in cross-sectional and difference-in-difference settings, that discriminatory fake news became much more widespread after March 30 (1) in New Delhi, (2) in districts closer to New Delhi, and (3) in districts with higher social media interactions with New Delhi. Further, it shows that, after March 30, discriminatory fake news was more common in districts historically exposed to attacks by Muslim groups. The final paper is a political economy paper that studies the short term and long term effect of earlier eligibility on voting in the context of a large North Italian municipality setting with little institutional barriers to voting. It also studies the differing mobilisation of members in the same household by newly eligible voters.

Teaching informatics to novices: big ideas and the necessity of optimal guidance

This thesis reports on the two main areas of our research: introductory programming as the traditional way of accessing informatics and cultural teaching informatics through unconventional pathways. The research on introductory programming aims to overcome challenges in traditional programming education, thus increasing participation in informatics. Improving access to informatics enables individuals to pursue more and better professional opportunities and contribute to informatics advancements. We aimed to balance active, student-centered activities and provide optimal support to novices at their level. Inspired by Productive Failure and exploring the concept of notional machine, our work focused on developing Necessity Learning Design, a design to help novices tackle new programming concepts. Using this design, we implemented a learning sequence to introduce arrays and evaluated it in a real high-school context. The subsequent chapters discuss our experiences teaching CS1 in a remote-only scenario during the COVID-19 pandemic and our collaborative effort with primary school teachers to develop a learning module for teaching iteration using a visual programming environment. The research on teaching informatics principles through unconventional pathways, such as cryptography, aims to introduce informatics to a broader audience, particularly younger individuals that are less technical and professional-oriented. It emphasizes the importance of understanding informatics's cultural and scientific aspects to focus on the informatics societal value and its principles for active citizenship. After reflecting on computational thinking and inspired by the big ideas of science and informatics, we describe our hands-on approach to teaching cryptography in high school, which leverages its key scientific elements to emphasize its social aspects. Additionally, we present an activity for teaching public-key cryptography using graphs to explore fundamental concepts and methods in informatics and mathematics and their interdisciplinarity. In broadening the understanding of informatics, these research initiatives also aim to foster motivation and prime for more professional learning of informatics.

Portfolio optimization in the energy market

Let’s put ourselves in the shoes of an energy company. Our fleet of electricity production plants mainly includes gas, hydroelectric and waste-to-energy plants. We also sold contracts for the supply of gas and electricity. For each year we have to plan the trading of the volumes needed by the plants and customers: better to fix the price of these volumes in advance with the so-called forward contracts, instead of waiting for the delivery months, exposing ourselves to price uncertainty. Here’s the thing: trying to keep uncertainty under control in a market that has never shown such extreme scenarios as in recent years: a pandemic, a worsening climate crisis and a war that is affecting economies around the world have made the energy market more volatile than ever. How to make decisions in such uncertain contexts? There is an optimization problem: given a year, we need to choose the optimal planning of volume trading times, to meet the needs of our portfolio at the best prices, taking into account the liquidity constraints given by the market and the risk constraints imposed by the company. Algorithms are needed for the generation of market scenarios over a finite time horizon, that is, a probabilistic distribution that allows a view of all the dates between now and the end of the year of interest. Algorithms are needed to solve the optimization problem: we have proposed more than one and compared them; a very simple one, which avoids considering part of the complexity, moving on to a scenario approach and finally a reinforcement learning approach.

La nuova eGovernance sanitaria europea: verso una piena integrazione della digitalizzazione nei sistemi sanitari degli Stati membri

L’elaborato approfondisce il diritto alla salute nell’ordinamento dell’Unione europea, con la consapevolezza che il settore della sanità, nella complessità di una tensione perdurante tra la sua matrice sociale e l’applicazione di logiche europee di mercato, rappresenta un ambito da sempre sottratto all’intervento diretto e vincolante delle istituzioni. Contemporaneamente, prende spunto dall’osservazione della transizione digitale dei sistemi sanitari nazionali per proporre una rilettura dei tradizionali equilibri istituzionali tra ordinamenti e constatare il grado di influenza dell’Unione oltre la dimensione transfrontaliera. Infatti, per le attuali esigenze di sostenibilità dei sistemi di tutela della salute e per il valore aggiunto riconosciuto alle azioni europee nel corso della gestione della pandemia da Covid-19, l’eHealth ha rappresentato l’occasione per una vigorosa intrusione delle istituzioni europee entro prerogative tipicamente statuali, fino all’emersione di una eGovernance sanitaria europea. Pertanto, la trattazione compie un percorso evolutivo che muove dalla Direttiva 2011/24 sull’assistenza transfrontaliera e l’assistenza sanitaria online, in combinato disposto con il complesso degli atti di soft law connessi, per verificarne l’esiguo impatto sui sistemi sanitari degli Stati membri e, alla luce dei recenti investimenti strategici ed interventi normativi rilevanti in tema di tecnologie applicate alla sanità, riconoscerne il sostanziale superamento. In particolare, il confronto tra l’insufficiente livello di digitalizzazione raggiunto finora nei sistemi sanitari degli Stati membri ed il tenore della Proposta di regolamento sullo European Health Data Space suggerisce l’evoluzione dell’impianto di governo dei dati sanitari stabilito nella Direttiva, a partire dalla previsione di una disciplina comune sulla cartella sanitaria. A questo proposito, l’interoperabilità tra tecnologie diviene un presupposto operativo indefettibile, che corrobora la natura ‘tecnologicamente condizionata’ del diritto alla salute e propone l’idea che la sanità digitale rappresenti un passo in avanti verso un’assistenza europea uniforme.

Obesità infantile: abitudini alimentari e stili di vita delle famiglie. Un'analisi sociologica sul territorio riminese

L'obesità infantile può essere considerata una delle maggiori sfide sanitarie del XXI secolo. In Italia, la fascia d'età più colpita è quella tra i 6 e gli 11 anni. L'infanzia e l'adolescenza non solo influenzano lo sviluppo fisico, cognitivo e sociale dell'adulto, ma anche l'aspettativa di vita. Inoltre, l'interruzione dell'insegnamento in classe e le misure di contenimento di Covid-19 hanno aumentato il comfort food, la sedentarietà e la vulnerabilità socio-economica delle famiglie. Lo scopo del lavoro di ricerca è stato quello di studiare i fattori sociali che hanno influenzato le abitudini alimentari e gli stili di vita delle famiglie con bambini di età compresa tra i 6 e gli 11 anni, all'interno dell'ambiente di socializzazione primario (famiglia) e secondario (scuola e altre istituzioni) anche durante la pandemia di COVID-19. La ricerca è stata condotta in Emilia-Romagna nella città di Rimini e poi estesa al contesto europeo contemporaneo. Per indagare questo punto, è stata utilizzata una metodologia in parte qualitativa e in parte quantitativa. L'approccio mosaico composto da 15 interviste semi-strutturate; 8 focus group e 5 etnografie ha permesso di costruire un questionario, online e cartaceo, somministrato a 361 genitori. I principali risultati rivelano che (1) i bambini sono ingrassati durante il periodo di Covid; (2) esiste una correlazione tra il peso della madre e il peso del bambino; (3) le madri sottovalutano l'obesità dei figli.

Youth psychosocial adjustment in the context of parental illness: risk and protective factors

Young carers might experience both psychological distress and positive changes from living with their chronically ill parent. However, little is known about why some young carers do well with their situation and experience positive outcomes, whereas others do not. In this regard, this dissertation aims to investigate how parental chronic illness affects young carers’ psychosocial adjustment through risk (i.e., unmet needs) and protective factors (i.e., benefit finding, emotion regulation). This main goal has been addressed by conducting three studies presented in Chapters 2–4. Chapter 2 has examined the mediating role of unmet needs on the relationship between illness unpredictability and youth psychosocial adjustment (i.e., quality of life and internalizing problems). In this regard, it has been found that levels of unmet needs significantly mediated the relationship between illness unpredictability and offspring health-related quality of life. In the systematic review with meta-analysis presented within Chapter 3, it has been sought to investigate the mediating role of the protective factors (i.e., benefit finding and emotion regulation) in the relationship between caregiving components and youth psychosocial adjustment in young carers. This study has shown the significant associations between caregiving components and psychosocial adjustment in young carers not only directly, but also indirectly through protective factors. Finally, to expand on previous findings, a qualitative study in Chapter 4 has examined the unique experiences of young carers, as well as the effects of the COVID-19 global pandemic. This study has yielded a deeper understanding of how protective factors may be operated during young carers’ lived experiences before and during the COVID-19 global pandemic. Overall, this dissertation has shed light on the pivotal role played by risk and protective factors in caregiving components that serve as key determinants that can enhance positive psychosocial outcomes as well as concurrently mitigate adverse psychosocial consequences among young carers.

Audience attitudes towards simil sync: a pilot study

This thesis is based on a pilot investigation which explores the attitudes of a sample of Italian viewers towards the simil sync technique which in Italy is used for the dub of non-fictional television contents. The thesis seeks to analyse and define the characteristics of this dubbing modality which is often considered by scholars and professionals in the dubbing industry a hybrid modality of standard synchronised dubbing and voice-over. In order to investigate viewers’ attitudes, I organised 4 focus groups sessions which, due to the impact of Covid-19 pandemic, were carried out online. The online recruitment of participants, which was a difficult task, resulted in a small sample of eighteen participants (and two interviewees). The four online focus groups revealed that participants were aware of the simil sync technique. They recognised that the clips were dubbed in a different modality from standard synchronised dubbing. The characteristic that was mostly mentioned for detecting simil sync was the original soundtrack that was audible below the dub, followed by the identification of the genre of the programme in the clip and the absence of lip sync. Moreover, while simil sync with a barely audible original soundtrack received neutral or positive attitudes, simil sync with a more audible original soundtrack, instead, was tolerated or considered annoying. Simil sync passed unnoticed in the in-depth interviews in which the discussion about dubbing was not focused on the distinction between two dubbing modalities, for instance simil sync versus standard synchronised dubbing, but rather on the distinction between programmes that originated in Italian and those that were translated into Italian from another language and then dubbed.

Framing climate change: a planetary health perspective on the pediatric age

This thesis analyzes an analysis of the risk perception of Italian paediatricians and parents regarding the impact of climate change on pediatric health. The consequences of climate change are now before our eyes; the recent pandemic has highlighted the impact that the destruction of ecosystems and global warming can have on our health. Fragile subjects will pay the most for the consequences of this crisis: children, the elderly, pregnant women. According to the World Health Organization (WHO), 88% of the disease burden linked to climate change falls on children under the age of 5. Climate change poses a challenge of equity not only between different areas of the world but also between generations: the worst consequences will weigh on those who have not caused damage to the ecosystem. This study began by studying the risk perceptions of the two main caregivers who deal with the child's health: parents and paediatricians. The study analyzed a mixed methods approach, exploiting quantitative and qualitative approaches. Two surveys were carried out in collaboration with the Italian Society of Pediatrics (SIP) and AGE, the Italian Parents' Association, using a tool already consolidated in the literature and adapted according to the needs of the thesis. Sixty semi-structured interviews were then conducted with pediatricians of different age groups and different regions of Italy. The collected data were then compared with the literature on the subject, in order to understand differences and similarities. This work is part of a still rather scarce, but growing, field of literature and represents the first study of this type in Italy.

Internet of healthcare (law): privacy and data protection aspects in an internet of everything

The purpose of this research study is to discuss privacy and data protection-related regulatory and compliance challenges posed by digital transformation in healthcare in the wake of the COVID-19 pandemic. The public health crisis accelerated the development of patient-centred remote/hybrid healthcare delivery models that make increased use of telehealth services and related digital solutions. The large-scale uptake of IoT-enabled medical devices and wellness applications, and the offering of healthcare services via healthcare platforms (online doctor marketplaces) have catalysed these developments. However, the use of new enabling technologies (IoT, AI) and the platformisation of healthcare pose complex challenges to the protection of patient’s privacy and personal data. This happens at a time when the EU is drawing up a new regulatory landscape for the use of data and digital technologies. Against this background, the study presents an interdisciplinary (normative and technology-oriented) critical assessment on how the new regulatory framework may affect privacy and data protection requirements regarding the deployment and use of Internet of Health Things (hardware) devices and interconnected software (AI systems). The study also assesses key privacy and data protection challenges that affect healthcare platforms (online doctor marketplaces) in their offering of video API-enabled teleconsultation services and their (anticipated) integration into the European Health Data Space. The overall conclusion of the study is that regulatory deficiencies may create integrity risks for the protection of privacy and personal data in telehealth due to uncertainties about the proper interplay, legal effects and effectiveness of (existing and proposed) EU legislation. The proliferation of normative measures may increase compliance costs, hinder innovation and ultimately, deprive European patients from state-of-the-art digital health technologies, which is paradoxically, the opposite of what the EU plans to achieve.

La paradoja de Maastricht. Los distintos modelos económicos y políticos para el futuro integrador de la UE

La crisis existencial del proyecto de integración europea constituye el principal reto al que debe enfrentarse la Comunidad en su futuro más inmediato puesto que se alza como toda una amenaza para la continuidad del sistema establecido desde el Tratado fundacional de Roma (1957). Las tres crisis acontecidas durante los primeros años del siglo XXI, véase la gran crisis económica del año 2008, la pandemia global de la Covid-19 y la actual intervención de la Federación Rusa en Ucrania, están poniendo constantemente a prueba la firmeza de los cimientos y valores sobre los cuales se ha construido la Comunidad durante todos estos años. Esta tesis doctoral pretende ser una contribución académica al debate abierto en las sociedades comunitarias acerca de por donde debe de transitar la evolución del proyecto de integración europea en los próximos años. Para conseguir alcanzar este objetivo, la investigación se retrotrae hasta los orígenes del proceso de integración y avanza en la línea temporal hasta nuestros días, analizando con ello las posibles causas que pudieran encontrarse detrás de la crisis existencial actual. A su vez, , la investigación estudia con detenimiento los múltiples efectos que está generando la problemática existencial en los Estados miembros en los últimos años, tales como el aumento del apoyo social a favor de actores considerados populistas o el fenómeno de la creciente desafección ciudadana. Esta investigación analiza los distintos escenarios propuestos por la Comisión Europea en su Libro Blanco sobre el futuro de Europa para determinar cuál podría ser el mejor escenario que concordara con la nueva realidad económica y sociopolítica que actualmente impera en los Estados miembro. Lo que se persigue es formular una propuesta que pueda dar por terminada la crisis existencial de la Comunidad abriendo con ello una nueva etapa en la historia de la integración europea.

Data surveillance for infectious diseases: models, complex networks and machine learning

In this thesis, we investigate the role of applied physics in epidemiological surveillance through the application of mathematical models, network science and machine learning. The spread of a communicable disease depends on many biological, social, and health factors. The large masses of data available make it possible, on the one hand, to monitor the evolution and spread of pathogenic organisms; on the other hand, to study the behavior of people, their opinions and habits. Presented here are three lines of research in which an attempt was made to solve real epidemiological problems through data analysis and the use of statistical and mathematical models. In Chapter 1, we applied language-inspired Deep Learning models to transform influenza protein sequences into vectors encoding their information content. We then attempted to reconstruct the antigenic properties of different viral strains using regression models and to identify the mutations responsible for vaccine escape. In Chapter 2, we constructed a compartmental model to describe the spread of a bacterium within a hospital ward. The model was informed and validated on time series of clinical measurements, and a sensitivity analysis was used to assess the impact of different control measures. Finally (Chapter 3) we reconstructed the network of retweets among COVID-19 themed Twitter users in the early months of the SARS-CoV-2 pandemic. By means of community detection algorithms and centrality measures, we characterized users’ attention shifts in the network, showing that scientific communities, initially the most retweeted, lost influence over time to national political communities. In the Conclusion, we highlighted the importance of the work done in light of the main contemporary challenges for epidemiological surveillance. In particular, we present reflections on the importance of nowcasting and forecasting, the relationship between data and scientific research, and the need to unite the different scales of epidemiological surveillance.

The predictive role of the human gut microbiota in covid-19: implications for disease severity and post-covid syndrome

The COVID-19 pandemic, sparked by the SARS-CoV-2 virus, stirred global comparisons to historical pandemics. Initially presenting a high mortality rate, it later stabilized globally at around 0.5-3%. Patients manifest a spectrum of symptoms, necessitating efficient triaging for appropriate treatment strategies, ranging from symptomatic relief to antivirals or monoclonal antibodies. Beyond traditional approaches, emerging research suggests a potential link between COVID-19 severity and alterations in gut microbiota composition, impacting inflammatory responses. However, most studies focus on severe hospitalized cases without standardized criteria for severity. Addressing this gap, the first study in this thesis spans diverse COVID-19 severity levels, utilizing 16S rRNA amplicon sequencing on fecal samples from 315 subjects. The findings highlight significant microbiota differences correlated with severity. Machine learning classifiers, including a multi-layer convoluted neural network, demonstrated the potential of microbiota compositional data to predict patient severity, achieving an 84.2% mean balanced accuracy starting one week post-symptom onset. These preliminary results underscore the gut microbiota's potential as a biomarker in clinical decision-making for COVID-19. The second study delves into mild COVID-19 cases, exploring their implications for ‘long COVID’ or Post-Acute COVID-19 Syndrome (PACS). Employing longitudinal analysis, the study unveils dynamic shifts in microbial composition during the acute phase, akin to severe cases. Innovative techniques, including network approaches and spline-based longitudinal analysis, were deployed to assess microbiota dynamics and potential associations with PACS. The research suggests that even in mild cases, similar mechanisms to hospitalized patients are established regarding changes in intestinal microbiota during the acute phase of the infection. These findings lay the foundation for potential microbiota-targeted therapies to mitigate inflammation, potentially preventing long COVID symptoms in the broader population. In essence, these studies offer valuable insights into the intricate relationships between COVID-19 severity, gut microbiota, and the potential for innovative clinical applications.

Integrating the age factor in designing industrial environments and workstations in the workforce ageing era

As people spend a third of their lives at work and, in most cases, indoors, the work environment assumes crucial importance. The continuous and dynamic interaction between people and the working environment surrounding them produces physiological and psychological effects on operators. Recognizing the substantial impact of comfort and well-being on employee satisfaction and job performance, the literature underscores the need for industries to implement indoor environment control strategies to ensure long-term success and profitability. However, managing physical risks (i.e., ergonomic and microclimate) in industrial environments is often constrained by production and energy requirements. In the food processing industry, for example, the safety of perishable products dictates storage temperatures that do not allow for operator comfort. Conversely, warehouses dedicated to non-perishable products often lack cooling systems to limit energy expenditure, reaching high temperatures in the summer period. Moreover, exceptional events, like the COVID-19 pandemic, introduce new constraints, with recommendations impacting thermal stress and respiratory health. Furthermore, the thesis highlights how workers' variables, particularly the aging process, reduce tolerance to environmental stresses. Consequently, prolonged exposure to environmental stress conditions at work results in cardiovascular disease and musculoskeletal disorders. In response to the global trend of an aging workforce, the thesis bridges a literature gap by proposing methods and models that integrate the age factor into comfort assessment. It aims to present technical and technological solutions to mitigate microclimate risks in industrial environments, ultimately seeking innovative ways to enhance the aging workforce's comfort, performance, experience, and skills. The research outlines a logical-conceptual scheme with three main areas of focus: analyzing factors influencing the work environment, recognizing constraints to worker comfort, and designing solutions. The results significantly contribute to science by laying the foundation for new research in worker health and safety in an ageing working population's extremely current industrial context.