Master of Science / Department of Grain Science and Industry / Cassandra K. Jones / Animal food manufacturing facilities need to evaluate biological hazards within their facility due to their severity and probability to cause illness or injury in humans or animals. Control of biological hazards, including Salmonella and Porcine Epidemic Diarrhea Virus (PEDV), in animal food manufacturing facilities may require a preventative control to mitigate the risk of the hazard. Thermal processing is an effective point-in-time control, but does not prevent cross-contamination during drying, cooling, and packaging/load-out of animal food. Therefore, it may be appropriate to sanitize surfaces to prevent cross-contamination of animal food during manufacturing. The objective of the first experiment was to evaluate surface decontamination strategies for Porcine Epidemic Diarrhea Virus (PEDV) using chemical disinfectants to reduce viral RNA on various manufacturing surfaces. Concentrated liquid formaldehyde and sodium hypochlorite reduced the quantity of viral PEDV RNA on all tested surfaces. Rubber belting from a bucket elevator retained the most PEDV RNA, while the polyethylene tote bag retained the least. In the second experiment, surface decontamination was evaluated for Salmonella Typhimurium using liquid and dry chemical sanitizers on various manufacturing surfaces. Surfaces treated with concentrated commercial formaldehyde had no detectable Salmonella after treatment, and surfaces treated with medium chain fatty acids (MCFA) had at least a 4-log reduction compared to the control. The dry commercial acidulant, sodium bisulfate, was the most effective dry sanitizer tested, but had limited efficacy depending on surface type. Experiment 3 further tested the application of two chemical sanitizers against Salmonella Enteritidis on residual surface and feed contamination in pilot-scale mixers. Manufacturing sequence, but not treatment impacted feed and surface contamination of Salmonella Enteritidis. Specifically, there was Salmonella-positive residue in the batch of feed manufactured immediately after the positive control batch. However, no Salmonella residue was detected in batches of feed treated with either concentrated commercial essential oil blend or rice hulls treated with 10% MCFA. Low levels of Salmonella residues were observed from feed and surfaces manufactured after Sequence 1, but no residues were observed by Sequence 2. This data suggests that sequencing of feed during manufacturing can reduce Salmonella-positive contamination within animal food and on manufacturing surfaces, particularly after the second batch or with the use of chemical treatments. In summary, liquid sanitizers have been shown to be effective at reducing Salmonella spp. and PEDV contamination on a variety of animal food manufacturing surfaces, but application and practicality may be limited.

Master of Science / Department of Electrical and Computer Engineering / Caterina M. Scoglio / The generalized epidemic modeling framework simulator (GEMFsim) is a tool designed by Dr. Faryad Sahneh, former PhD student in the NetSE group. GEMFsim simulates stochastic spreading process over complex networks. It was first introduced in Dr. Sahneh’s doctoral dissertation "Spreading processes over multilayer and interconnected networks" and implemented in Matlab. As limited by Matlab language, this implementation typically solves only small networks; the slow simulation speed is unable to generate enough results in reasonable time for large networks. As a generalized tool, this framework must be equipped to handle large networks and contain sufficient support to provide adequate performance. The C language, a low-level language that effectively maps a program to machine in- structions with efficient execution, was selected for this study. Following implementation of GEMFsim in C, I packed it into Python and R libraries, allowing users to enjoy the flexibility of these interpreted languages without sacrificing performance. GEMFsim limitations are not limited to language, however. In the original algorithm (Gillespie’s Direct Method), the performance (simulation speed) is inversely proportional to network size, resulting in unacceptable speed for very large networks. Therefore, this study applied the Next Reaction Method, making the performance irrelevant of network size. As long as the network fits into memory, the speed is proportional to the average node degree of the network, which is not very large for most real-world networks. This study also applied parallel computing in order to advantageously utilize multiple cores for repeated simulations. Although single simulation can not be paralleled as a Markov process, multiple simulations with identical network structures were run simultaneously, sharing one network description in memory.

Master of Science / Department of Industrial & Manufacturing Systems Engineering / Todd Easton / History has shown that epidemics can occur at random and without warning — devastating the populations which they impact. As a preventative measure, modern medicine has helped to reduce the number of diseases that can instigate such an event, nevertheless natural and man-made disease mutations place us continuously at risk of such an outbreak. As a second line of defense, extensive research has been conducted to better understand spread patterns and the efficacy of various containment and mitigation strategies. However, these simulation models have primarily focused on minimizing the impact to groups of people either from an economic or societal perspective and little study has been focused on determining the utility maximizing strategy for an individual. Therefore, this work explores the decisions of individuals to determine emergent behaviors and characteristics which lead to increased probability of survival during an epidemic. This is done by leveraging linear program optimization techniques and the concept of Agent Based Simulation, to more accurately capture the complexity inherent in most real-world systems via the interactions of individual entities. This research builds on 5 years of study focused on rural epidemic simulation, resulting in the development of a 4,000-line computer code simulation package. This adaptable simulation can accurately model the interactions of individuals to discern the impact of any general disease type, and can be implemented on the population of any contiguous counties within Kansas. Furthermore, a computational study performed on the 17 counties of northwestern Kansas provides game theoretical based insights as to what decisions increase the likelihood of survival. For example, statistically significant findings suggest that an individual is four times more likely to become infected if they rush stores for supplies after a government issued warning instead of remaining at home. This work serves as a meaningful step in understanding emergent phenomena during an epidemic which, subsequently, provides novel insight to an individual’s utility maximizing strategy. Understanding the main findings of this research could save your life.

Segundo a OMS as gastroenterites agudas são a segunda maior causa de morte de crianças no mundo. Este cenário é mais grave em países em desenvolvimento. Presume-se que a grande maioria das hospitalizações e mortes por gastroenterites agudas são causadas pela rotavirose. No ano de 2009 a OMS recomendou a vacinação internacional de crianças de 0-5 anos devido ao sucesso das campanhas de vacinação em países que adotaram esta política pública. Atualmente há uma variedade de vacinas para o rotavírus, tornando a avaliação do custobenefício destas vacinas desejável. O objetivo deste trabalho é adaptar um modelo da dinâmica da transmissão que possa contribuir com estas avaliações de custo-benefício. Para tanto foi adotada a abordagem ampla com ênfase na análise quantitativa da dinâmica da doença. O método consistiu em adaptar um modelo compartimental de referência da literatura internacional sobre modelagem de doenças com protocolo de vacinação. Este modelo de referência foi estudado e simulado para diferentes valores para posteriormente se imputar os parâmetros do modelo com os valores estimados para a rotavirose no Estado de São Paulo. Os resultados foram comparados com os valores obtidos dos dados do Datasus. Como resultado foram estimados alguns parâmetros da infecção e de seu comportamento dinâmico com informações da literatura. Conclui-se que são necessários mais estudos que possam caracterizar melhor a infecção no Estado de São Paulo, para que com isto se possa estimar melhor a infecção / According to WHO, acute gastroenteritis is the second leading cause of death for children in the world. This scenario is more serious in developing countries. It is assumed that the vast majority of hospitalizations and deaths from acute gastroenteritis are caused by rotavirus. In 2009, WHO recommended the international vaccination of children aged 0-5 due to the success of vaccination campaigns in countries that adopted this public policy. Currently, there are a variety of rotavirus vaccines, making the cost-benefit assessment of these vaccines desirable. The purpose of this paper is to contribute to these cost-benefit assessments. For that, a broad approach was adopted with emphasis on the quantitative analysis of the dynamics of the disease. The method consisted of adopting a compartmental model of the international literature on disease modelling. This reference model was studied, simulated for different values to later assign the parameters of the model to the estimated values for rotavirus in the State of São Paulo. The results were compared with the data obtained from Datasus. As a result of this work, some parameters of the infection have been estimated and it was studied the dynamic behaviour of the disease using the information available in the literature. It is concluded that further studies are needed to better characterize the infection in the State of São Paulo so that it is possible to better estimate the infection

Charles University in Prague, Faculty of Science Department of Genetics and Microbiology Ph.D. study program: Molecular and Cellular Biology, Genetics and Virology Genetic basis of multidrug resistance in Acinetobacter baumannii Lenka Křížová Supervisor: Doc. RNDr. Alexandr Nemec, Ph.D. Supervisor-consultant: RNDr. Lubomír Janda, Ph.D. Prague 2014 SUMMARY Acinetobacter baumannii has emerged as a significant bacterial pathogen pre-eminently associated with hospital-acquired infections. Strains of this species may currently exhibit resistance to nearly all or even all clinically relevant drugs. The vast majority of epidemic and multidrug-resistant A. baumannii strains belong to a few globally spread lineages, in particular to the so-called European (EU) clones I, II, and III. Complex resistance patterns displayed by these strains result from their marked capacity to develop, acquire, and combine secondary resistance mechanisms against originally effective agents. The aim of this thesis was to broaden our knowledge on the genetic basis and epidemiology of multidrug resistance in A. baumannii. The obtained results have been published in the form of six studies which are part of this thesis. In the first study, we analysed the epidemiology of carbapenem resistance among hospital strains of Acinetobacter in the...

Associamos independentemente a cada vértice v de un grafo infinito G um raio de infecção aleatório R_v e definimos um modelo de percolação sujeito às seguintes regras: (1) no tempo zero só a raiz é declarada infectada, (2) um vértice é declarado infectado em um instante t, t>0, se está a uma distância no maximo R_v de algum vértice v previamente infectado, e (3) vértices infectados permanecem infectados para sempre. Dizemos que há sobrevivência em uma realização particular do modelo se o número final de vértices infectados é infinito. Neste trabalho damos condições suficientes sobre o grafo G para a transição de fase deste modelo, estabelecendo limitantes não triviais para o parâmetro crítico quando os raios R_v têm distribuição geometrica de parâmetro 1-p. Além disto, restringindo nosso estudo para o caso das árvores esfericamente simétricas, obtemos um melhor limitante superior para este parâmetro. Finalmente, concluímos que o parâmetro crítico para o modelo nas árvores homogêneas de grau d+1 se comporta assintoticamente como 1/(2d). / We assign independently to each vertex v of an infinite graph G, a random radius of infection R_v and define a percolation model subject to the following rules: (1) at time zero, only the root is declared infected, (2) a vertex is declared infected at time t, t>0, if it is at distance at most R_v of some vertex v previously infected, and (3) infected vertices stay infected forever. We say that there is survival in a particular realization of the model if the final number of infected vertices is infinite. In this work, we give sufficient conditions on the graph G for the phase transition of this model, by stating non-trivial bounds for the critical parameter when the radii have geometrical distribution with parameter 1-p. In addition, restricting our study to the case of the spherically symmetric trees, we obtain an improved upper bound for this critical parameter. Finally, we conclude that the critical parameter for the model on homogeneous trees of degree (d+1) behaves asymptotically as 1/(2d).

Estudamos um sistema de partículas a tempo discreto cuja dinâmica é a seguinte. Considere que no instante inicial sobre cada inteiro não negativo há uma partícula, inicialmente inativa. A partícula da origem é ativada e instantaneamente ativa um conjunto aleatório contíguo de partículas que estão a sua direita. Como regra, no instante seguinte ao que foi ativada, cada partícula ativa realiza esta mesma dinâmica de modo independente de todo o resto. Dizemos que o processo sobrevive se em qualquer momento sempre há ao menos uma partícula ativa. Chamamos este processo de Firework, associando a dinâmica de ativação de uma partícula inativa a uma infecção ou explosão. Nosso interesse é estabelecer se o processo tem probabilidade positiva de sobrevivência e apresentar limites para esta probabilidade. Isto deve ser feito em função da distribuição da variável aleatória que define o raio de ação de uma partícula. Associando o processo de ativação a uma infecção, podemos pensar este modelo como um modelo epidêmico. Consideramos também algumas variações dessa dinâmica. Dentre elas, variantes com partículas distribuídas sobre a semirreta dos reais positivos (nesta vertente, existem condições para as distâncias entre partículas consecutivas) e também com as partículas distribuídas sobre vértices de árvores. Estudamos também para esses casos a transição de fase e probabilidade de sobrevivência. Nesta variante os resultados obtidos são funções da sequência de distribuições dos alcances das explosões e da estrutura dos lugares onde se localizam as partículas. Consideramos também variações do modelo onde cada partícula ao ser ativada, permanece ativa durante um tempo aleatório e nesse período emite explosões que ocorrem em instantes aleatórios. / We studied a discrete time particle system whose dynamic is as follows. Consider that at time zero, on each non-negative integer, there is a particle, initially inactive. A particle which is placed at origin is activated and instantly activates a contiguous random set of particles that is on its right. As a rule, the next moment to what it has been activated, each active particle carries the same behavior independently of the rest. We say that the process survives if the amount of particles activated along the process is infinite. We call this the Firework process, associating the activation dynamic of a particle to an infection or explosion process. Our interest is to establish whether the process has positive probability of survival and to present limits to this probability. This is done according to the distribution random variable that defines the radius of infection of each active particle, Associating the activation process to an infection, we think this model as a model epidemic. We also consider some variations of this dynamic. Among them, variants with particles distributed over the half line (there are conditions for the distances between consecutive particles) and also with particles distributed over the vertices of a tree. We studied phase transitions and the correspondent survival probability. In this variant the results depend on the sequence of probability distributions for the range of the explosions and on the particles displacement. We also consider a variation where each particle after activated, remains active during a random time period emitting explosions that occur in random moments.

A emergência de fenômenos coletivos e correlações de longo alcance impossibilitam a inferência de propriedades de sistemas como um todo a partir de suas partes componentes. A modelagem destes sistemas frequentemente ocorre mediante emprego de operadores de spin localizados em grafos com topologias não-triviais. Aqui, mostramos que o operador de momento angular de muitos corpos une o estudo de diversos sistemas complexos, desde a sistemas epidêmicos até cadeias magnéticas de spin. Para o modelo epidêmico SIS, determinamos a matriz de transição do processo estocástico correspondente e mostramos suas soluções para grafos regulares e aleatórios, por meio de técnicas geralmente empregadas em sistemas fortemente correlacionados. Já no modelo de Dicke, identificamos o vínculo que explica a relevância e o efeito finito de operadores anti-girantes para duas espécies atômicas confinadas numa cavidade óptica que interagem com radiação eletromagnética. Por fim, o papel do momento angular também é identificado para duas cadeias quânticas de spin 1/2 acopladas, as quais modelam nanoestruturas magnéticas heterogêneas. A estrutura de bandas é calculada, enquanto efeitos espúrios de superfície são removidos pela introdução de quasipartículas dotadas de grau de liberdade de spin adicional / The emergence of collective phenomena and long range correlations makes it impossible to infer the properties of whole systems from their components. Their modeling often occurs through the use of localized spin operators, taking place within graphs with non-trivial topologies. Here, we show that the many-body angular momentum operator connects the study of several complex systems, ranging from epidemic systems to magnetic spinchains. For the SIS epidemic model, we calculate the transition matrix of the corresponding stochastic process and show the corresponding solutions for regular and random graphs, using techniques generally employed in strongly correlated systems. For the Dicke model we identify the constraint that explains the relevance and finite size effect of anti-rotating operators, for two atomic species, confined within an optical cavity, and interacting with electromagnetic radiation. Finally, the role of angular momentum is also identified for two coupled quantum spinchains 1/2 which model heterogeneous magnetic nanostructures. The band structure is calculated, while spurious surface effects are removed due to the introduction of quasiparticles with an additional spin degree of freedom.

Thesis advisor: Susan A. Michalczyk / Malaria is a curable, preventable disease which has been around for millennia. Unfortunately, in this time of unprecedented growth and resources, the world has yet to prevent malaria from continuing its vicious cycle, taking the life of a child every thirty seconds. This project is an interdisciplinary creative writing exploration of the underlying biological, sociological, and theological reasons for this failure to eradicate an avoidable illness. Aside from the biological difficulties involved in creating vaccines for the complex strains of the malaria parasite, the deeper cause of malaria's persistence within the bloodstream of humanity is the narcissism to which all people are prone, especially when self-interest is upheld as the highest virtue of Western capitalistic society. Literature, sociology, and theology, among other fields, each point to the answer of humility and love as solutions to the global problem caused by the fact that, ultimately, there is something far worse than malaria plaguing everyone from within. / Thesis (BA) — Boston College, 2007. / Submitted to: Boston College. College of Arts and Sciences. / Discipline: College Honors Program.

Estudamos, através de modelagem matemática, aspectos estacionários, espaciais e temporais relacionados à propagação e controle de doenças infecciosas de transmissão direta por contato pessoa-a-pessoa. Elaboramos modelos matemáticos determinísticos fundamentados no princípio de ação de massas em Epidemiologia, levando em consideração a simetria no número de contatos entre suscetíveis e infectados, o que nos permitiu estimar a taxa per capita de contatos potencialmente infectantes e, por conseguinte, a força de infecção e os possíveis efeitos de diferentes programas de vacinação. O desenvolvimento do modelo de estado estacionário foi feito com base em dados sorológicos de rubéola (Azevedo Neto 1992) para uma população que ainda não havia sido imunizada por meio de vacinação. Analisamos, então, o efeito de três diferentes esquemas de vacinação para a rubéola, nos seguintes intervalos de idade: de 1 a 2 anos, de 7 a 8 anos e de 14 a 15 anos. A incerteza estatística na idade média de infecção foi estimada com o auxílio do método de Monte Carlo e tal metodologia foi aplicada a dados de varicela e hepatite A. Estudamos também o aspecto espacial, com a inclusão da variável distância na formulação de um modelo SIR e análise da influência do alcance de interação entre indivíduos. E, através do estudo da força de infecção em função da idade e do tempo, pudemos analisar, de modo qualitativo, diferentes cenários na evolução temporal de uma doença infecciosa. / We have studied, based on mathematical modelling, stationary, spatial and temporal features related to the propagation and control of directly transmitted infectious diseases through person-to-person contact. We have developed deterministic mathematical models founded on the mass-action principle of Epidemiology, taking into account the symmetry of contacts among susceptible and infectious individuals. Such symmetry enabled us to estimate the potentially infective per capita contact rate and, therefore, the force of infection and the possible effects of different vaccination programmes. The steady state modelling has been based on rubella serological data of a non-immunized population (Azevedo Neto 1992) and we have analysed three different vaccination schemes against rubella in the following age intervals: from 1 to 2 years of age, from 7 to 8 years of age, and from 14 to 15 years of age. The serological data variability has been considered in the estimation of the statistical uncertainty of the average age at infection by means of the Monte Carlo method and we have applied this methodology to varicella and hepatitis A data. The spatial feature in a SIR model has been studied with the analysis of the influence of the interaction range among individuals. We have also studied the force of infection as a function of age and time and we have analysed, in a qualitative way, different situations in the time evolution of an infectious disease.