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At the end of February 1957, the WHO announced that a highly contagious flu epidemic was raging in China, where hundreds of thousands of people had fallen ill. This flu then spreads with furious speed over the rest of the world and becomes known as the Asian flu. The main purpose of the essay is to use a qualitative content analysis to investigate and compare how the Asian flu pandemic was portrayed in the Swedish newspapers Norrskensflamman and Dagens Nyheter at its outbreak in 1957. The reason why these two newspapers have been chosen is due to their differences in quantity, political tendency and their geographical locations. Both dailies have also been available digitally. Based on own investigations in the thesis, as well as research on previous epidemics that have affected Sweden, three themes have been identified; panic, vaccines and societal change. These are a starting point for seeking answers to what the portrayal looks like, what differences there are between the newspapers and whether Norrbotten is affected in a different way compared to the rest of Sweden. The articles on the Asian flu that have been investigated have been located in the two newspapers and compared in relation to each other. The essay shows both similarities and differences in the newspapers' reporting of the Asian flu, where the most prominent are the panic aspects. Together, both newspapers report a much lower death toll from the flu than the actual one, but differ in how much responsibility they take to prevent public panic, for example through word choice. Their early reporting on the work with vaccines also helps to calm and convey that the situation is under control. On the other hand, the content of the articles changes quickly when it is clear that the infection is raging in Sweden. Information in the newspapers regarding societal changes is sparse and there are few indications that they are permanent.There are no clear indications that Norrbotten was hit much harder by the Asian flu than the rest of Sweden, quite the opposite.

This dissertation explores U.S. military surgeons’ purposeful efforts to alter how medical and line officers in the U.S. Army and Navy conceived of disease, appreciated surgeons’ roles, and organized medical war preparations through education, training, exposure, and medico-military professionalization between 1884 and 1918. It traces surgeons’ postwar efforts to change American military cultures in response to the revelations of the germ theory of disease and deadly typhoid fever epidemics in the American training camps of the Spanish-American War. Medical and line officers required academic education and practical lessons to contextualize disease, surgeons, and medical care, understand and appreciate germs’ role in medicine, and train to apply these lessons to benefit their soldiers and sailors. Surgeons also reinforced their scientific education and grew military medicine through postgraduate education and tactical training designed to enhance the line’s perception of surgeons and medical science.This dissertation rests on the contention that surgeons contributed to military preparation for the next war by effecting cultural change to prevent the epidemics of previous wars. This culture of medical preparation shaped how military medical departments recruited, organized, and trained medical officers, procured supplies, and managed civil-military relationships. Entwined cultural change and war preparation were expressed in the multiple mobilization activities through which surgeons validated the success or failure of their efforts. Troops participated in organized camps of instruction, maneuver camps, and major mobilizations to the U.S.-Mexico border, allowing surgeons to use the physical encampments, hospitals, and other surgeons to test assumptions, exercise and refine theory, validate operational principles, and improve from previous iterations. As the United States entered the Great War in 1917, epidemics of measles, influenza, and meningitis attacked Army and Navy recruit training camps. Rather than demonstrate failure, this dissertation positions the 1917 and 1918 epidemics to demonstrate medical officers’ successful military cultural change. A comparative approach between 1898 and 1918 also highlights cultural and medico-military evolution through the lenses of preparation and mobilization. Official military reports and archival sources illuminate cultural divisions between line and medical officers and track the curricular development of military hygiene and sanitation courses in undergraduate and professional military schools and specialized fields at military medical schools. This dissertation intervenes in military and medical historiographies by pushing the conversation beyond disease’s impact on war to center disease and changing perceptions of disease, culturally and medically, as features of military preparation. It also recasts military surgeons as central agents in the U.S. military’s turn-of-the-century professionalization and modernization efforts. As the world addresses the outcomes and aftermath of the COVID-19 pandemic, this dissertation demonstrates that physicians and societies met previous epidemics and pandemics on medical science’s past frontiers where the germ theory of disease had barely won acceptance. It also illustrates the power of individuals in subordinate classes to affect institutional cultures for the betterment of all. Lastly, as military operations during future pandemics are all but guaranteed, this dissertation proves that dedication and preparation are just as vital to epidemic defense as good science. / History

Nicotine, in the form of cigarette smoking, chewing tobacco, and most recently as vapor smoking, is one of the most heavily used addictive drugs in the world. Since smoking imposes a significant health-care and economic burden on the population, there have been sustained and significant efforts for the past several decades to control it. However, smoking epidemic is a complex and "policy-resistant" problem that has proven difficult to control. Despite the known importance of social networks in the smoking epidemic, there has been no network-centric intervention available for controlling the smoking epidemic yet. The long-term goal of this work is the development and implementation of an environment needed for developing network-centric interventions for controlling the smoking contagion. In order to develop such an environment we essentially need: an operationalized model of smoking that can be simulated, to determine the role of online social networks on smoking behavior, and actual methods to perform network-centric interventions. The objective of this thesis is to take first steps in all these categories. We perform Twitter-based surveillance of smoking-related tweets, and use mathematical modeling and simulation techniques to achieve our objective. Specifically, we use Twitter data to infer sentiments on smoking and electronic cigarettes, to estimate the proportion of user population that gets exposed to smoking-related messaging that is underage, and to identify statistically anomalous clusters of counties where people discuss about electronic cigarette a lot more than expected. In other work, we employ mathematical modeling and simulation approach to study how different factors such as addictiveness and peer-influence together contribute to smoking behavior diffusion, and also develop two methods to stymie social contagion. This lead to a total of four smoking contagion-related studies. These studies are just a first step towards the development of a network-centric intervention environment for controlling smoking contagion, and also to show that such an environment is realizable. / Ph. D.

This dissertation employs management systems engineering principles, data science, and industrial systems engineering techniques to address pressing challenges in emergency department (ED) efficiency, infectious disease management at mass gatherings, and student self-efficacy. It is structured into three essays, each contributing to a distinct domain of research, and utilizes industrial and systems engineering approaches to provide data-driven insights and recommend solutions. The first essay used data analytics and regression analysis to understand how patient length of stay (LOS) in EDs could be influenced by multi-level variables integrating patient, service, and organizational factors. The findings suggested that specific demographic variables, the complexity of service provided, and staff-related variables significantly impacted LOS, offering guidance for operational improvements and better resource allocation. The second essay utilized system dynamics simulations to develop a modified SEIR model for modeling infectious diseases during mass gatherings and assessing the effectiveness of commonly implemented policies. The results demonstrated the significant collective impact of interventions such as visitor limits, vaccination mandates, and mask wearing, emphasizing their role in preventing health crises. The third essay applied machine learning methods to predict student self-efficacy in Muslim societies, revealing the importance of socio-emotional traits, cognitive abilities, and regulatory competencies. It provided a basis for identifying students with varying levels of self-efficacy and developing tailored strategies to enhance their academic and personal success. Collectively, these essays underscore the value of data-driven and evidence-based decision- making. The dissertation's broader impact lies in its contribution to optimizing healthcare operations, informing public health policy, and shaping educational strategies to be more culturally sensitive and psychologically informed. It provides a roadmap for future research and practical applications across the healthcare, public health, and education sectors, fostering advancements that could significantly benefit society. / Doctor of Philosophy / Divided into three essays, this dissertation uses industrial and systems engineering and data science to help make emergency departments more efficient, manage the spread of diseases at large events, and predict students' belief in their abilities. The first essay investigates factors that influence how long patients stay in emergency departments, including patient demographics, triage level, the complexity of care they receive, and number of emergency department staff when patient arrived. The essay offers suggestions to improve these services and better manage resources. The second essay models the spread of COVID-19 during the Hajj, a religious mass gathering, and evaluates the effectiveness of three safety measures: limiting the number of attendees, vaccinations, and wearing masks. This essay shows how different strategies can work together to prevent outbreaks. The third essay uses artificial intelligence and machine learning to understand what affects Muslim students' confidence in their abilities, focusing on emotional intelligence, thinking skills, and self-discipline. The findings could help to identify students who need extra support and to create more personalized programs that will help them succeed. Overall, this dissertation contributes to advancing industrial and systems engineering and data science knowledge by addressing complex issues in healthcare, public health, and education, leading to more informed decisions and better strategies. Its broader impact includes improving hospital operations, guiding public health decisions, and helping develop educational programs and interventions that consider cultural and psychological factors.

The U.S. healthcare system is facing many public health challenges that affect population health, societal well-being, and quality of healthcare. Infant mortality, opioid overdose death, and hospital readmission after stroke are some of these important public health concerns that can impact the effectiveness and outcomes of the healthcare system. We analyze these problems through the industrial engineering and data analytics lens. The major goal of this dissertation is to enhance understanding of these three challenges and related interventions using different levels of analysis to improve the health outcomes. To attain this objective, I introduced three stand-alone papers to answer the related research questions. In essay 1, we focused on the performance of the state's healthcare systems in reducing unfavorable birth outcomes such as infant mortality, preterm birth, and low birthweight using Data Envelopment Approach. We constructed a unique state-level dataset to answer this main research question: what does make a healthcare system more successful in improving the birth outcomes? Our results indicated that socioeconomic and demographic factors may facilitate or obstruct health systems in improving their outcomes. We realized that states with a lower rate of poverty and African-American women were more successful in effectively reduce unfavorable birth outcomes. In the second essay, we looked into the trends of the opioid overdose mortalities in each state from 2008 to 2017. We investigated the effect of four state laws and programs that have been established to curb the epidemic (i.e., dose and duration limitations on the initial prescription, pain management clinic laws, mandated use of prescription drug monitoring programs, and medical cannabis laws) in short and long-term, while we controlled for several protentional risk factors. The results of fixed-effect regression and significant tests indicated that state policies and laws were unlikely to result in an immediate reduction in overdose mortalities and comprehensive interventions were needed to restrain the epidemic. The third essay investigated the risk factors of 30-day readmission in patients with ischemic stroke at an individual level. We aimed to identify the main risk factors of stroke readmissions and prioritized them using machine learning techniques and logistic regression. We also introduced the most effective predictive model based on different performance metrics. We used the electronic health records of stroke patients extracted from two stroke centers within the Geisinger Health System from 2015 to 2018. This data set included a comprehensive list of clinical features, patients' comorbidities, demographical characteristics, discharge status, and type of health insurance. One of the major findings of this study was that stroke severity, insert an indwelling urinary catheter, and hypercoagulable state were more important than generally known diagnoses such as diabetes and hypertension in the prediction of stroke 30-day readmission. Furthermore, machine learning-based models can be designed to provide a better predictive model. Overall, this dissertation provided new insights to better understand the three major challenges of the U.S. healthcare system and improve its outcomes. / Doctor of Philosophy / The major goal of a healthcare system can be summarized in three main objectives: preventing preterm birth and premature mortality, advancing the quality of life, and preparing for a good death. Despite all the national efforts to achieve these goals, the U.S. healthcare system still faces many obstacles and crises and suffers from inefficiencies. The U.S. infant mortality rate is still higher than any other comparable advanced country. The opioid overdose death rate has been steadily increasing since 1999 and has risen exponentially in recent years. Hospital readmissions especially in stroke patients impose a substantial cost burden on the healthcare system in the U.S. Also, readmitted stroke patients are at higher risk of mortality compared to the first admission. I believe that industrial engineering and data analytics approaches can help in advancing the understanding of these health challenges, their important risk factors, and effective interventions. In this dissertation, the main focus was on the performance, trends, variations, and processes of the healthcare systems. We applied innovative methods to provide answers to the following questions in three essays: What does make a healthcare system more successful in improving the birth outcomes? What factors do explain mortality from opioid painkillers? What are the determinants of state variations in mortalities from an opioid overdose? What is the impact of states' laws and programs and opioid prescription rates and overdose mortality rates? What are the most important contributors to stroke readmissions? The results of the first essay showed that not all the state's healthcare systems perform the same in terms of reducing unfavorable birth outcomes. States with lower people in poverty and lower African American women were more successful in improving their birth outcomes. The second study revealed that states with a higher share of uninsured people and binge drinkers were suffering from higher opioid overdose deaths. Also, our results implied that in addition to upstream prevention policies, states need to implement downstream programs to curb the epidemic. Finally, the third study showed that the top predictors of stroke readmissions within 30 days consist of the severity of the stroke, insert an indwelling urinary catheter, being overweight, and malnourished. The results of this dissertation can help to educate policymakers and practitioners at state and organizational level in a way to better serve the society and ultimately enhance the population health, quality of healthcare, and societal well-being.

Den här rapporten syftar till att undersöka hur upphovspersoner som sysselsätter sig med produktionsmusik identifierar sig med sitt komponerande och arbete, detta med hjälp av de organisationerna som de försörjer sig genom. De två organisationerna är STIM, Svenska Tonsättares Internationella Musikbyrå, eller Epidemic Sound. Skillnaden mellan de två organisationerna är huvudsakligen att hos STIM upplåter upphovspersonerna sitt verk till organisationen och de i sin tur får ansvaret att förvalta verket och samla in ersättning för upphovspersonens räkning, hos Epidemic Sound överlåter upphovspersonerna sitt verk för en engångsersättning. Epidemic Sound äger sedan verket och kan hyra ut musiken till olika produktionsbolag som vill ha musiken i sina produktioner. Till undersökningen har fyra kompositörer från STIM och fyra kompositörer från Epidemic Sound, samt en förläggare och en representant från STIM intervjuats. I rapporten framgår det att de som var anslutna till STIM har jobbat med musik länge, det är nästintill ett “kall” för dem, de ser verken som konstverk mer än som hantverk, de värdesätter upphovsrätten högt och ser ersättningen som en sekundär anledning till varför de sysselsätter sig med komponerandet. De från Epidemic Sound däremot ser sina verk mer som ett hantverk och den mer säkra lönen som går att få av Epidemic Sound är en stor anledning till varför de valt denna organisation. Med hjälp av organisations-, motivations och identitetsteorier har samband funnits mellan teorierna och val av ersättningsmodell. Denna studie påvisar att det skett en förändring på den svenska marknaden för produktionsmusik efter det att Epidemic Sound kom till år 2009. En förändring har skett gällande det institutionaliserade tillvägagångssättet att traditionellt licensera ut sin musik till produktionsbolag. Denna förändring har gett en ny typ av upphovspersoner med en annan arbetsidentitet en möjlighet att kunna försörja sig på sin musik. Detta har kunnat påvisas genom att studera hur upphovspersonerna identifierar sig med sitt arbete och komponerande beroende på vilken av modellerna de använder. / This essay aims to examine how composers who specializes in production music identify themselves with their composing and work, this with help from the organisations that they support themselves through. The two organisations are STIM, The Swedish Composers International Musicbureu, or Epidemic Sound. The difference between the two are mainly that with STIM the composers let them manage the administration and to collect their income with Epidemic Sound is that they sell their righs to Epidemic Sound for a flat-fee. Because of this transaction the composition is now owned by the company and they can rent it out to other production companies who would like to have the music in their productions. To the study four composers from STIM, four composers from Epidemic Sound, one publisher and one representative from STIM have been interviewed. In the report it emerges that the composers that are from STIM have worked with music for a long time, the work is almost like their destiny, they see their compositions as artwork than as a craftmanship, they put big value to the copyright law, and the commission is a secondary reason to why they do what they do. The composers for Epidemic Sound on the other hand see their work more like craftmanship and the more secure salary are the reason why the composers choose Epidemic Sound. With the help from organizational-, motivational- and identitybased theories connections has been made between the theories and revenue model. This study shows that there’s been a change within the swedish market for production music since Epidemic Sound was founded in 2009. A change has occurd regarding the institutionalized approach to traditionally license music to production companies. This change has given a new type of composers with another work identity an opportunity to provide themselves on their music. This has been detected by studying how the composers identify themselves with their work and their composing depending on what revenue model they choose.

L'épidémie de VIH a introduit la question du risque et de la maladie dans les rapports entre les femmes et les hommes. Parmi les stratégies mises en place du niveau individuel au niveau collectif, différentes selon les situations et inscrites dans des représentations infléchies par le contexte culturel, celles relatives aux personnes atteintes par le VIH sont primordiales. Ce « traitement social » est marqué par des différences et des similitudes entre les hommes et les femmes, qui induisent certaines recompositions des rapports entre hommes et femmes. Cette recherche, qui relève simultanément de l'anthropologie médicale et de l'anthropologie du genre, décrit et analyse la dimension du genre dans le traitement social de l'infection à VIH dans le système de soin au Cameroun. L'analyse des représentations de la maladie à travers les messages sanitaires des années 1980 à 2000 révèle les stéréotypes de genre prévalent dans la société camerounaise et leurs usages dans la prévention. L'expérience d'hommes et de femmes vivant avec le VIH dans le système de soin montre ensuite des différences entre leurs perceptions et conduites, qu'ils soient patients ou professionnels de santé, de l'annonce du statut jusqu'à sa révélation au partenaire. Puis c'est à travers l'expérience du traitement antirétroviral que des différences entre les hommes et les femmes apparaissent dans le système de soin. Enfin, l'étude de la gestion de la sexualité, de la procréation et de l'allaitement montre comment les rôles sociaux des hommes et des femmes se construisent de manière particulière pour des personnes vivant avec le VIH, dévoilant un aspect du genre dans la société camerounaise / The HIV epidemic has brought the issue of risk and disease into relations between women and men. Among the strategies set up from the individual to the collective level, varied in different situations and shaped by culturally framed representations, those relating to people living with HIV are crucial. This "social treatment" is marked by differences and similarities between men and women, which induce some reconstructions of the relationships between men and women. This research, which belongs simultaneously to the fields of medical anthropology and anthropology of gender, describes and analyzes the gender dimension of the social treatment of HIV infection in the health care system in Cameroon. The analysis of disease representations through health messages from 1980 to 2000 reveals the gender stereotypes prevalent in the Cameroonian society and their use in prevention. The experience of men and women living with HIV in the health care system then shows the differences between their perceptions and behavior, whether patients or health professionals, from announcement of HIV status by health professionnals to disclosure to partner. Then men and women’s experience of antiretroviral therapy reveal gender dimensions in the health care system. Finally, the study of the management of sexuality, pregnancy and infant feeding shows how the social roles of men and women are built in a special way for people living with HIV, as a window an aspect of gender in Cameroonian society

Le calcul des valeurs propres intervient dans des modèles de maladies d’épidémiques et pourrait être utilisé comme un allié des campagnes de vac- cination dans les actions menées par les organisations de soins de santé. La modélisation épidémique peut être considérée, par analogie, comme celle des viruses d’ordinateur qui dépendent de l’état de graphe sous-jacent à un moment donné. Nous utilisons PageRank comme méthode pour étudier la propagation de l’épidémie et d’envisager son calcul dans le cadre de phé- nomène petit-monde. Une mise en œuvre parallèle de méthode multiple de "implicitly restar- ted Arnoldi method" (MIRAM) est proposé pour calculer le vecteur propre dominant de matrices stochastiques issus de très grands réseaux réels. La grande valeur de "damping factor" pour ce problème fait de nombreux algo- rithmes existants moins efficace, tandis que MIRAM pourrait être promet- teuse. Nous proposons également dans cette thèse un générateur de graphe parallèle qui peut être utilisé pour générer des réseaux synthétisés distri- bués qui présentent des structures "scale-free" et petit-monde. Ce générateur pourrait servir de donnée pour d’autres algorithmes de graphes également. MIRAM est mis en œuvre dans le cadre de trilinos, en ciblant les grandes données et matrices creuses représentant des réseaux sans échelle, aussi connu comme les réseaux de loi de puissance. Hypergraphe approche de partitionnement est utilisé pour minimiser le temps de communication. L’al- gorithme est testé sur un grille national de Grid5000. Les expériences sur les très grands réseaux tels que Twitter et Yahoo avec plus de 1 milliard de nœuds sont exécutées. Avec notre mise en œuvre parallèle, une accélération de 27× est satisfaite par rapport au solveur séquentiel / The eigenvalue equation intervenes in models of infectious disease prop- agation and could be used as an ally of vaccination campaigns in the ac- tions carried out by health care organizations. The epidemiological model- ing techniques can be considered by analogy, as computer viral propagation which depends on the underlying graph status at a given time. We point out PageRank as method to study the epidemic spread and consider its calcula- tion in the context of small-world phenomenon. A parallel implementation of multiple implicitly restarted Arnoldi method (MIRAM) is proposed for calculating dominant eigenpair of stochastic matrices derived from very large real networks. Their high damp- ing factor makes many existing algorithms less efficient, while MIRAM could be promising. We also propose in this thesis a parallel graph gen- erator that can be used to generate distributed synthesized networks that display scale-free and small-world structures. This generator could serve as a testbed for graph related algorithms. MIRAM is implemented within the framework of Trilinos, targeting big data and sparse matrices representing scale-free networks, also known as power law networks. Hypergraph partitioning approach is employed to minimize the communication overhead. The algorithm is tested on a nation wide cluster of clusters Grid5000. Experiments on very large networks such as twitter and yahoo with over 1 billion nodes are conducted. With our parallel implementation, a speedup of 27× is met compared to the sequential solver