In loco parentis, or “in place of the parent,” was the model that formerly governed the relationship between student and university. Student behavior on campus was closely monitored, as if each pupil were the son or daughter of the dean. The university was granted power to regulate the lives of its students closely, but was also charged with responsibility for their welfare. The cultural revolution of the 1960s changed this. Student rebellions aimed against any and all authority, coupled with judicial interference that severely hindered the university’s capacity to act as parent, effectively killed off the doctrine of in loco parentis. Now the relationship between university and student more closely resembles that of landlord and tenant. These phenomena have coincided with the rise of the “campus rape epidemic,” or the notion that roughly 20 percent of women will be sexually assaulted during their college years. By comparing the sexual assault rate at schools that continue to practice in loco parentis to those that do not, this report will show that a return to the doctrine of university as parent can solve the problem of sexual assault on college campuses. In a survey of 657 colleges and universities around the nation, this paper will demonstrate that the sexual assault rate is lower at schools that attempt to regulate the lives of their students, such as with regard to alcohol and living arrangements. This is, in a sense, to state the obvious – or, at least, what was once obvious. Alcohol is involved in over half of all sexual assaults on campus, and 90 percent of sexual assaults occur in dorm rooms. By reducing the availability of alcohol on campus and by limiting the residence interactions between the sexes, the university can put an end to the campus rape epidemic.

Parasites are thought to have large effects on their host populations, driving genetic change, population density changes, speciation and be a major selective force maintaining sexual reproduction. Indirect signatures of parasite-mediated selection are common, but explicit examples of parasite-mediated selection in nature are lacking. In this thesis I examine parasite-mediated dynamics in a natural population of Daphnia magna that experiences an annual epidemic of the bacterial pathogen Pasteuria ramosa. I also test a novel hypothesis investigating the relationship between parasitism and the production of resting eggs. In chapter 2 a combined field study and laboratory infection experiment illustrates one of the best examples of parasite-mediated selection in a natural population, with Daphnia collected after a parasite epidemic having higher levels of parasite resistance than those collected before. This chapter also explored the relationship between parasitism and resting eggs, which are only produced during the sexual phase of reproduction. Daphnia that were reproducing sexually in the field prior to the parasite epidemic were more susceptible, supporting higher levels of parasite growth, than their asexual counterparts. This supports the idea that some genotypes invest in sex at the expense of parasite resistance. In chapter 3 I used molecular markers to investigate genotype frequency changes in the same population in relation to the parasite epidemic. The parasite epidemic was found to be associated with genetic change in the population, and a laboratory infection experiment revealed that the genotype most resistant to the parasite was also most common following the peak of the parasite epidemic. While chapter 2 explored a genetic relationship between susceptibility and resting eggs, chapter 4 explores whether crowding conditions, cues indicating parasite prevalence in the population, or direct exposure to parasite spores can induce resting egg production. I found that crowding conditions or parasite prevalence enhance levels of male and resting egg production, but patterns were entirely dependent on Daphnia genotypes. There was no indication that exposure to parasite spores affects levels of sexual reproduction.

Background: Dengue is a viral infectious disease that is transmitted by mosquitoes. The disease causes a significant health burden in tropical countries, and has been a public health burden in Singapore for several decades. Severe complications such as hemorrhage can develop and lead to fatal outcomes. Before tetravalent vaccine and drugs are available, vector control is the key component to control dengue transmission. Vector control activities need to be guided by surveillance of outbreak and implement timely action to suppress dengue transmission and limit the risk of further spread. This study aims to explore the feasibility of developing a dengue early warning system using temperature and rainfall as main predictors. The objectives were to 1) analyze the relationship between dengue cases and weather predictors, 2) identify the optimal lead time required for a dengue early warning, 3) develop forecasting models, and 4) translate forecasts to dengue risk indices. Methods: Poisson multivariate regression models were established to analyze relative risks of dengue corresponding to each unit change of weekly mean temperature and cumulative rainfall at lag of 1-20 weeks. Duration of vector control for localized outbreaks was analyzed to identify the time required by local authority to respond to an early warning. Then, dengue forecasting models were developed using Poisson multivariate regression. Autoregression, trend, and seasonality were considered in the models to account for risk factors other than temperature and rainfall. Model selection and validation were performed using various statistical methods. Forecast precision was analyzed using cross-validation, Receiver Operating Characteristics curve, and root mean square errors. Finally, forecasts were translated into stratified dengue risk indices in time series formats. Results: Findings showed weekly mean temperature and cumulative rainfall preceded higher relative risk of dengue by 9-16 weeks and that a forecast with at least 3 months would provide sufficient time for mitigation in Singapore. Results showed possibility of predicting dengue cases 1-16 weeks using temperature and rainfall; whereas, consideration of autoregression and trend further enhance forecast precision. Sensitivity analysis showed the forecasting models could detect outbreak and non-outbreak at above 90% with less than 20% false positive. Forecasts were translated into stratified dengue risk indices using color codes and indices ranging from 1-10 in calendar or time sequence formats. Simplified risk indices interpreted forecast according to annual alert and outbreak thresholds; thus, provided uniform interpretation. Significance: A prediction model was developed that forecasted a prognosis of dengue up to 16 weeks in advance with sufficient accuracy. Such a prognosis can be used as an early warning to enhance evidence-based decision making and effective use of public health resources as well as improved effectiveness of dengue surveillance and control. Simple and clear dengue risk indices improve communications to stakeholders.

In 2014-2015 a large-scale Ebola epidemic occurred in West Africa. The Swedish Civil Contingencies Agency was given the order to conduct the Swedish response. The purpose of this case study was to investigate the impact on project planning of the three factors: the nature of the crisis, political initiative and developing countries. In this case study the crisis was an epidemic, and the project was initiated by the Swedish Government and conducted in two developing countries. The results were intended to contribute to developed understanding and recommendations for future project managers in similar projects. The data collected came from six qualitative interviews, where all respondents were directly involved in the project planning. The project managers suggest that the three external factors had significant effects on project planning. The nature of the crisis led to impaired recruitment processes and personnel safety, and that it was difficult to predict the development of the epidemic, which led to frequent replanning. The political initialization generated pressure on project managers and executives, as well as an increased workload as more reports had to be compiled and presented. Developing countries have a less developed infrastructure, and political and economic aspects, that contributed to a complicated planning process. Many project managers had previous knowledge of the influencing factors but did not have sufficient routines for how to handle them. The study's main conclusion is therefore that project organizations increasingly need to learn from past experiences. / Mellan åren 2014 och 2015 pågick det en storskalig ebolaepidemi i Västafrika. Myndigheten för Samhällsskydd och Beredskap fick uppdraget att genomföra Sveriges respons. Syftet med denna fallstudie var att undersöka hur de tre faktorerna krisens karaktär, politisk initiering och utvecklingsland påverkade planeringsfasen i detta storskaliga krishanteringsprojekt. I det aktuella fallet var krisen en epidemi, projektet initierat av Sveriges regering samt utfört i två utvecklingsländer. Resultaten ämnade bidra med förståelse och rekommendationer för framtida projektledare vid liknande projekt. Den insamlade datan i studien kommer från sex stycken kvalitativa intervjuer, där samtliga respondenter var direkt involverade i fallstudiens projektplanering. Projektledarna upplevde att de valda påverkansfaktorerna hade betydande influenser på projektplaneringen. Krisens karaktär medförde försvårad rekryteringsprocess och personalsäkerhet, samt att det var svårt att förutspå epidemins utveckling vilket ledde till frekvent omplanering. Den politiska initieringen skapade press på projektledare och chefer, samt ökade arbetsbördan då fler rapporter skulle sammanställas, men gav samtidigt bättre samarbetsmöjligheter med övriga aktörer och en ledande roll i dessa relationer. Utvecklingsländer har en mindre utvecklad infrastruktur samt politiska och ekonomiska aspekter vilket bidrog till att planeringen komplicerades. Många av dessa påverkansfaktorer hade projektledarna kunskap om sedan innan men inte tillräckliga rutiner för hur de skulle hanteras. Studiens främsta slutsats är att projektorganisationer i större utsträckning måste ta lärdom av tidigare erfarenheter.

Within this thesis we map the Value-Chains of the Swedish market for Production Music. The reason behind this is that the authors believe this sub-segment of the music industry to be relatively unexplored by business research. Thus increased knowledge should increase transparency for all market actors. We have gathered previous research regarding value chains in the music industry and compare this research to empirical findings on the Production Music Industry.  These findings are primarily gathered from three interviews with individuals in well informed positions within the industry. The three interviews are also backed up by secondary information found through industry websites and other vendors. Analysis indicates that there are two general forms of Value-Chains in the Production Music Industry that are significantly different from each other, and that these are either centered around the Swedish Performing Rights Organization STIM, or the relatively new internet based music library called Epidemic Sound. Specific forms of value delivered back and forth within these value chains consists of everything from education and coaching in production techniques, to monetary compensation and recognition. Analysis also shows that while there is a rather big difference in how the two general value chains are constructed, there seems to be less variation when it comes to how these value chains are governed.

Since the first cases of HIV/AIDS disease were recognised in the early 1980s, a large number of mathematical models have been proposed. However, the mobility of people among regions, which has an obvious impact on the spread of the disease, has not been much considered in the modelling studies. One of the main reasons is that the models for the spread of the disease in multiple populations are very complex and, as a consequence, they can easily become intractable. In this thesis we provide various new results pertaining to the spread of the disease in mobile populations, including epidemic intervention in multiple populations. We first develop stochastic models for the spread of the disease in a single heterosexual population, considering both constant and varying population sizes. In particular, we consider a class of continuous-time Markov chains (CTMCs). We establish deterministic and Gaussian diffusion analogues of these stochastic processes by applying the theory of density dependent processes. A range of numerical experiments are provided to show how well the deterministic and Gaussian counterparts approximate the dynamic behaviour of the processes. We derive threshold parameters, known as basic reproduction numbers, for both cases above the threshold which the disease is uniformly persistent and below the threshold which disease-free equilibrium is locally attractive. We find that the threshold conditions for both constant and varying population sizes have the same form. In order to take into account the mobility of people among regions, we extend the stochastic models to multiple populations. Various stochastic models for multiple populations are formulated as CTMCs. The deterministic and Gaussian diffusion counterparts of the corresponding stochastic processes for the multiple populations are also established. Threshold parameters for the persistence of the disease in the multiple population models are derived by applying the concept of next generation matrices. The results of this study can serve as a basic framework how to formulate and analyse a more realistic stochastic model for the spread of HIV in mobile heterogeneous populations—classifying all individuals by age, risk, and level of infectivities, and at the same time considering different modes of the disease transmission. Assuming an accurate mathematical model for the spread of HIV/AIDS disease, another question that we address in this thesis is how to control the spread of the disease in a mobile population. Most previous studies for the spread of the disease focus on identifying the most significant parameters in a model. In contrast, we study these problems as optimal epidemic intervention problems. The study is mostly motivated by the fact that more and more local governments allocate budgets over a certain period of time to combat the disease in their areas. The question is how to allocate this limited budget to minimise the number of new HIV cases, say on a country level, over a finite time horizon as people move among regions. The mathematical models developed in the first part of this thesis are used as dynamic constraints of the optimal control problems. In this thesis, we also introduce a novel approach to solve quite general optimal control problems using the Cross-Entropy (CE) method. The effectiveness of the CE method is demonstrated through several illustrative examples in optimal control. The main application is the optimal epidemic intervention problems discussed above. These are highly non-linear and multidimensional problems. Many existing numerical techniques for solving such optimal control problems suffer from the curse of dimensionality. However, we find that the CE technique is very efficient in solving such problems. The numerical results of the optimal epidemic strategies obtained via the CE method suggest that the structure of the optimal trajectories are highly synchronised among patches but the trajectories do not depend much on the structure of the models. Instead, the parameters of the models (such as the time horizon, the amount of available budget, infection rates) much affect the form of the solution.

Since the first cases of HIV/AIDS disease were recognised in the early 1980s, a large number of mathematical models have been proposed. However, the mobility of people among regions, which has an obvious impact on the spread of the disease, has not been much considered in the modelling studies. One of the main reasons is that the models for the spread of the disease in multiple populations are very complex and, as a consequence, they can easily become intractable. In this thesis we provide various new results pertaining to the spread of the disease in mobile populations, including epidemic intervention in multiple populations. We first develop stochastic models for the spread of the disease in a single heterosexual population, considering both constant and varying population sizes. In particular, we consider a class of continuous-time Markov chains (CTMCs). We establish deterministic and Gaussian diffusion analogues of these stochastic processes by applying the theory of density dependent processes. A range of numerical experiments are provided to show how well the deterministic and Gaussian counterparts approximate the dynamic behaviour of the processes. We derive threshold parameters, known as basic reproduction numbers, for both cases above the threshold which the disease is uniformly persistent and below the threshold which disease-free equilibrium is locally attractive. We find that the threshold conditions for both constant and varying population sizes have the same form. In order to take into account the mobility of people among regions, we extend the stochastic models to multiple populations. Various stochastic models for multiple populations are formulated as CTMCs. The deterministic and Gaussian diffusion counterparts of the corresponding stochastic processes for the multiple populations are also established. Threshold parameters for the persistence of the disease in the multiple population models are derived by applying the concept of next generation matrices. The results of this study can serve as a basic framework how to formulate and analyse a more realistic stochastic model for the spread of HIV in mobile heterogeneous populations—classifying all individuals by age, risk, and level of infectivities, and at the same time considering different modes of the disease transmission. Assuming an accurate mathematical model for the spread of HIV/AIDS disease, another question that we address in this thesis is how to control the spread of the disease in a mobile population. Most previous studies for the spread of the disease focus on identifying the most significant parameters in a model. In contrast, we study these problems as optimal epidemic intervention problems. The study is mostly motivated by the fact that more and more local governments allocate budgets over a certain period of time to combat the disease in their areas. The question is how to allocate this limited budget to minimise the number of new HIV cases, say on a country level, over a finite time horizon as people move among regions. The mathematical models developed in the first part of this thesis are used as dynamic constraints of the optimal control problems. In this thesis, we also introduce a novel approach to solve quite general optimal control problems using the Cross-Entropy (CE) method. The effectiveness of the CE method is demonstrated through several illustrative examples in optimal control. The main application is the optimal epidemic intervention problems discussed above. These are highly non-linear and multidimensional problems. Many existing numerical techniques for solving such optimal control problems suffer from the curse of dimensionality. However, we find that the CE technique is very efficient in solving such problems. The numerical results of the optimal epidemic strategies obtained via the CE method suggest that the structure of the optimal trajectories are highly synchronised among patches but the trajectories do not depend much on the structure of the models. Instead, the parameters of the models (such as the time horizon, the amount of available budget, infection rates) much affect the form of the solution.

Doctor of Philosophy / Department of Animal Sciences and Industry / Cassandra K. Jones / Porcine epidemic diarrhea virus (PEDV) is a heat-sensitive virus that devastated the United States swine industry. Because of its heat sensitivity, it was hypothesized that a pellet mill mimicking commercial thermal processing may mitigate PEDV infectivity. From the results, it was determined that a conditioning time of 30 sec or greater and temperatures above 54.4°C were effective point-in-time kill steps to inactive PEDV in a research setting. However, this does not prevent subsequent recontamination after pelleting as it is a point-in-time mitigation step. To further explore this, various mitigation additives were evaluated to prevent or mitigate PEDV post-pellet contamination in swine feed and ingredients. Various additives were examined across 3 experiments and included mitigation additives of medium chain fatty acids (MCFA), organic acids (OA), essential oils (OA), formaldehyde based products, and sodium bisulfate. From Exp. 1, formaldehyde, medium chain fatty acids (MCFA), essential oils (EO), and organic acid (OA) each decreased detectable PEDV RNA compared to the control (P<0.05). Additionally, PEDV stability over time was influenced by matrix as the meat and bone meal and spray-dried animal plasma resulted in a greater (P<0.05) quantity of detectable PEDV RNA over 42 days compared to that of the swine diet and blood meal. In Exp. 2, the 1% MCFA inclusion was equally effective at mitigating PEDV as a commercially available formaldehyde product in the complete swine diet. To further explore the effects of MCFA against PEDV, Exp. 3 was conducted to evaluate lower inclusion levels of MCFA and fat sources containing MCFA. It was noted that formaldehyde, 1% MCFA (1:1:1: of caproic, caprylic, and capric acids), 0.66% caproic, 0.66% caprylic, and 0.66% capric acids enhance the RNA degradation of PEDV in swine feed as determined by a bioassay. The MCFA were also evaluated against Salmonella Typhimurium, Generic Escherichia coli, Enterotoxigenic Escherichia coli, and Campylobacter coli. It was noted that the efficacy of the MCFA varied between each bacteria species with caproic and caprylic being the most effective. Commercial developmental products were also tested and determined that Product A and B provided the lowest MIC values across Salmonella Typhimurium, Generic Escherichia coli, and Enterotoxigenic Escherichia coli (P < 0.05). Product A and B were further tested in an animal disease trial utilizing a strain of enterotoxigenic Escherichia. coli O149:K91: K88. From d 7 to 14, chlortetracycline, 1:1:1 blend, and Product B, all improved G:F compared to the control (P<0.05). This also led to chlortetracycline and Product B having an improvement (P<0.05) over the control diet from d 0 to 14. A treatment × day interaction for the enterotoxigenic E. coli plate scores was observed (P < 0.05), which occurred because of the decrease (P<0.05) in plate scores for Product B from d 1 to d 14 and an increase (P<0.05) in chlortetracycline from d 7 to 14. A decrease (P<0.05) in plasma urea nitrogen and haptoglobin was observed as time increased from d -2 to 14. In summary MCFA have shown to be an effect interventional mitigation strategy against PEDV and various bacteria.

The theme of my thesis is the issue of the new strain of influenza A (H1N1 Pandemic 2009) and the associated awareness of vaccination amongst the elderly. The work is divided into two parts, a theoretical and practical part. In the theoretical part, I tried to comprehensively process the available knowledge on the origins, epidemiology and prevention of influenza with particular emphasis on vaccination, oriented towards the elderly. The practical part is focused on mapping the awareness of the elderly of the issue of vaccination against influenza and analysis of results from a research exploratory investigation. The data acquisition method I used was quantitatively oriented research using anonymus questionnaires. Altogether, I distribued 350 questionnaires; the final number for data processing was 191 questionnaires. In connection with the work I set four hypotheses: 1) More than a third of respondents were vaccinated against the new strain of influenza A (H1N1 Pandemic 2009), 2) The most common reason for not being vaccinated was a lack of information. 3) The size of the place of residence significantly contributes statistically to a sense of awareness of respondents on this issue, 4) More than half of respondents would like to obtain more information on the issue of the new strain of influenza type A (Pandemic H1N1 2009). I confirmed or refuted the formulated the hypotheses based on survey evaluation. The results of the survey showed that most respondents do not feel that they are sufficiently informed about the issue of the new strain of influenza, and therefore discard the use of vaccinations. With this work I would like to stress the importance of information, which can help people consider the risks of influenza and motivate them to be vaccinated. Vaccination is an important means of protection against influenza viruses particulary for high-risk groups including the elderly. For this reason I consider the dissemination of information as very important and I hope that my thesis also serves this purpose.

Pesquisas sobre a propagação de epidemias são uma constante devido a sua relevância para a contenção de doenças. Porém, devido aos diversos tipos de doenças existentes, a observação de um comportamento genérico e aproximado torna-se impraticável. Neste âmbito, a elaboração de modelos matemáticos epidêmicos auxiliam no fornecimento de informações que podem ser usadas por orgãos públicos para o combate de surtos epidêmicos reais. Em paralelo, por causa do grande volume de dados que são processados na execução da simulação desses modelos, o constante aumento dos recursos computacionais desenvolvidos vem em auxílio desta tarefa. O objetivo desta dissertação é estudar o comportamento da disseminação de uma epidemia simulada computacionalmente através do modelo epidêmico SIR em reticulados quadrados considerando duas propriedades: a existência de vértices vazios e a movimentação aleatória dos agentes. Essas propriedades são conhecidas por taxas de diluição e mobilidade, respectivamente. Para alcançar esse objetivo, algumas técnicas físico-estatística, tais como a análise das transições de fase e fenômenos críticos, foram aplicadas. Através destas técnicas, é possível observar a passagem do sistema da fase em que ocorre um surto epidêmico para a fase em que a epidemia é contida, bem como estudar a dinâmica do modelo quando ele está na criticidade, ou seja, no ponto de mudança de fase, conhecido por ponto crítico. Foi constatado que a taxa de diluição influencia a disseminação das epidemias porque desloca a transição de fase negativamente, reduzindo o valor crítico da imunização. Por sua vez, a taxa da movimentação dos agentes favorece o espalhamento da doença, pois a transição de fase é positivamente deslocada e seu ponto crítico, aumentado. Além disso foi observado que, apesar desse incremento, ele não é completamente restaurado devido às restrições de mobilidade dos agentes e ao alto grau de desconectividade da rede causado pelas altas taxas de diluição. Neste trabalho nós mostramos as razões deste comportamento. / Research on the spreading of epidemics are frequent because of their relevance for the containment of diseases. However, due to the variety of existing illnesses, the observation of an approximated generic behavior becomes impractical. In this context, the development of mathematical models of epidemics assists in providing information that can be used to make strategic decisions for the combat of real epidemic outbreaks. In parallel, because of the large volume of data which has to be processed in the simulation of these models, the increase of computational performance helps with this task. The objective of this thesis is to study the behavior of the spreading of an epidemic, by computationally simulating an SIR epidemic model on square lattices, considering two properties: the existence of empty vertices and random movement of agents. These properties are known as dilution rate and mobility rate, respectively. To achieve this goal, techniques of statistical physics, such as the analysis of phase transition and power laws, were applied. With these techniques, it is possible to observe the transition of the system from the phase in which an outbreak occurs to the phase where the epidemic is contained. Additionally, we studied the dynamics of the model when it is in criticality, that is, at the point of phase transition, known as the critical point. It was found that a higher dilution rate reduces the spreading of epidemics because it shifts the phase transition negatively, reducing the value of its critical point. On the other hand, increasing the rate of movement of the agents favors the spreading of the disease, because the phase transition is shifted positively and its critical point is increased. It was noticed that, despite of this increasing, this point is not completely restored due to restricted mobility of agents and the high degree of the network disconectivity caused by the high dilution rates. In this work we show the reasons for this behavior.