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Made available in DSpace on 2016-03-15T19:38:12Z (GMT). No. of bitstreams: 1 Douglas Nunes de Oliveira.pdf: 2639611 bytes, checksum: aa451c77b140c40c8a504474462ded1e (MD5) Previous issue date: 2008-09-17 / Probabilistic cellular automata can be used to model the spreading of contagious diseases in a population composed by susceptible, infected and recovered individuals. At each time step, a susceptible individual can either remain susceptible or contract the disease from infected individuals, where the probability related to the contagion depends on the number of infected individuals in contact with this susceptible individual. At each time step, an infected individual may (probabilistically) either remain infected or recuperate or die by the disease or die by other causes. A recovered individual, at each iteration, can either remain as he/she is or die. When an infected or recovered individual dies, a susceptible one appears in his/her place; thus, the population remains constant. Here, genetic algorithms are employed to identify the probability values concerning the processes of infection, cure and death, from epidemiological data from Arizona (USA) for measles. The goal is to obtain a model based on probabilistic rules of state transitions able of reproducing this time series and to verify the quality of the model prediction. This work reveals that the predictions are strongly influenced by the lattice dimension of the cellular automaton and by limitations imposed to the probability values. / Autômatos celulares probabilistas podem ser usados para modelar a propagação de doenças contagiosas numa população composta por indivíduos suscetíveis, infectados e recuperados da infecção. A cada passo de tempo, um indivíduo suscetível pode ou permanecer suscetível ou contrair a doença de infectados, sendo a probabilidade associada ao contágio dependente do número de infectados em contato com esse suscetível. A cada passo de tempo, um indivíduo infectado pode (probabilisticamente) permanecer infectado, ou se recuperar, ou morrer pela doença ou morrer de outras causas. Um indivíduo recuperado pode, a cada iteração, ou permanecer como está ou morrer. Quando um indivíduo infectado ou recuperado morre, nasce, em seu lugar, um suscetível, de modo que a população permanece constante. Aqui, algoritmos genéticos são empregados para identificar os valores das probabilidades associadas aos processos de infecção, recuperação e morte, a partir de dados epidemiológicos do Arizona (EUA) para catapora. O objetivo é obter um modelo baseado em regras probabilistas de transição de estados capaz de reproduzir essa série temporal e verificar a qualidade da previsão do modelo. Este trabalho revela que as previsões são fortemente influenciadas pelo tamanho do reticulado do autômato celular e por restrições impostas aos valores das probabilidades.

Les technologies modernes permettent d'avoir des renseignements toujours plus précis sur les interactions entre individus. Dans ce contexte, la collaboration SocioPatterns a permis de développer une infrastructure mesurant, avec une très grande résolution temporelle, la proximité face-à-face d'individus volontaires, portant des badges de radio-identification. Cette infrastructure a été déployée dans divers contextes, tels que des conférences scientifiques, un musée, une école ou encore un service hospitalier. La simple analyse de ces données représente un enjeu majeur pour l'étude de la dynamique humaine et soulève des questions aussi fondamentales que la recherche d'outils et de techniques d'analyse adaptés. Cette thèse présente la caractérisation statistique de la dynamique de proximité physique, mise en relation avec le contexte et les autres métadonnées disponibles, telles que l'âge, le sexe des individus, ou bien la structure de leurs réseaux sociaux virtuels. Si la structure des contacts diffère considérablement selon le contexte, les distributions empiriques des durées des interactions et entre interactions sont très similaires. Un modèle individu-centré, présenté dans cette thèse, propose des règles d'interactions microscopiques simples susceptibles de donner lieu à cette structure macroscopique complexe des temps d'interaction. Enfin, la caractérisation de la dynamique des contacts entre individus constitue une étape cruciale pour comprendre les mécanismes de propagation de maladies telles que la grippe dans une population. / Modern technologies allow to access to more and more detailed information on human interactions. In this context, the SocioPatterns collaboration has allowed to develop an infrastructure based on radio-identification devices, that records human proximity patterns at a fine grained resolution, among voluntary individuals. This infrastructure has been deployed in diverse contexts, such as scientific conferences, a museum, a primary school, or a hospital department. The mere analysis of these data represents a high stake for the study of human dynamics and raises fundamental issues such as the need of adequate tools and analysis techniques. This thesis presents the statistical characterization of physical proximity dynamics, put into relation with the context and other available metadata such as the age, the gender of participants or the structure of their virtual social networks. Although contact patterns considerably differ amongst the various contexts, the empirical distributions of interaction durations and of inter-contact times are very similar. An agent-based model, presented in this thesis, suggests simple microscopic interaction rules able to produce the complex macrostructure of interaction durations. In the last place, the characterization of contact dynamics constitutes a determining step for understanding spreading mechanisms of diseases such as the influenza. The human proximity data have allowed to analyze the level of information needed on contact dynamics for the elaboration of epidemiological models of contagion. Such models allow to better estimate the impact of public health strategies, e.g. the closure of school classes and targeted vaccinations.

A movimentação de animais em uma rede de fazendas e o espalhamento de algumas doenças animais estão intrinsecamente relacionados. Assim, compreender a dinâmica do espalhamento de doenças infecciosas nestas redes é um instrumento importante no controle dessas doenças. Usando as informações sobre as movimentações de bovinos no estado de Mato Grosso, Brasil, em 2007, reconstruiu-se a rede de trânsito e a rede de proximidade geográfica entre os estabelecimentos desse estado, além de redes hipotéticas seguindo os modelos de rede Molloy-Reed, Kalisky, Método A e Método B, onde simulou-se, usando diferentes configurações do modelo SLIRS, o espalhamento de doenças com parâmetros hipotéticos e reais (brucelose e febre aftosa). Além disso, simulou-se o controle do espalhamento dessas doenças considerando o controle por imunização e por restrição, com e sem rearranjo das movimentações após a restrição, selecionando os estabelecimentos a serem protegidos de forma aleatória, baseando-se no grau de movimentação dos animais e utilizando o conceito do paradoxo da amizade. Dentre os resultados, destacam-se que apesar dos padrões das curvas de prevalência nas redes hipotéticas serem semelhantes aos da rede real, os valores observados foram maiores nas redes hipotéticas, indicando que utilizá-las no planejamento de políticas de controle de doenças no lugar da rede real pode levar a um maior uso de recursos do que seria necessário. Além disso, no controle das doenças tanto com parâmetros hipotéticos quanto com parâmetros reais, nas simulações usando apenas a rede de trânsito dos animais, observou-se uma redução mais efetiva da prevalência ao se selecionar os estabelecimentos com maior grau total do que a da seleção aleatória, enquanto que nas simulações que consideraram a rede de proximidade geográfica dos estabelecimentos, a redução na prevalência das estratégias que selecionaram estabelecimentos específicos foram semelhantes aos da seleção aleatória. Sobre o efeito do rearranjo das movimentações, observou-se que este pode facilitar o espalhamento de doenças na rede, mesmo nas situações em que se aplica alguma estratégia de controle. Espera-se que os resultados das simulações matemáticas possam contribuir para a discussão do impacto relativo entre as estratégias de controle mencionadas e que futuramente possam auxiliar nas atividades dos órgãos responsáveis pela vigilância epidemiológica e no desenvolvimento de políticas de prevenção e controle de doenças em animais. / The animals’ movements in a farms network and the spread of some animal diseases are intrinsically related. Therefore, comprehending the dynamics of the spreading of infectious diseases in these networks is an important tool in controlling these diseases. Using the information about the bovine movements from the State of Mato Grosso, Brazil, in 2007, we rebuilt the network of animal movements and the geographic proximity network between the premises of this state, in addition to hypothetical networks following the network models Molloy-Reed, Kalisky, Method A and Method B, where we simulated, using different configurations of the model SLIRS, the spread of diseases with hypothetical parameters e real ones (brucellosis and foot and mouth disease). Moreover, we simulated the control of these diseases spreading, considering the control by immunization and by restriction, with and without the rearrangement of the movements after the restriction, selecting the premises to be protected randomly, based on the degree of animal’s movements and using the concept of the friendship paradox. Among the results, stands out that although the pattern of the prevalence curves in the hypothetical networks were similar to the ones in the real network, the observed values were higher in the hypothetical networks, indicating that using them in the planning of policies to control diseases in place of the real network might lead to a greater expense of resources than it would be necessary. Furthermore, in the control of the diseases both with hypothetical parameters as well as with real parameters, in the simulations using only the animal’s movements network, it was observed a more effective reduction of the prevalence when selecting the premises with the highest total degree than the random selection, while in the simulations that considered the network of geographic proximity of the premises, the reduction in the prevalence of the strategies that selected specific premises were similar to the random selection. On the effect of rearranging the movements, it was observed that it may facilitate the spread of diseases in the network even in situations where some control strategy is used. We hope that the results of the mathematical simulations may contribute to the discussion of the relative impact of the mentioned control strategies and that in the future they may assist in the activities of agencies responsible for disease surveillance and in the development of policies to prevent and control diseases in animals.

A dinâmica de movimentação de animais em uma rede de propriedades rurais e o espalhamento de algumas doenças animais estão intrinsecamente relacionados. Assim, compreender a dinâmica do espalhamento de doenças infecciosas nestas redes é um instrumento importante no controle destas. Neste projeto, foram implementados algoritmos para gerar redes de movimentação de animais hipotéticas e reconstruiu-se a rede de movimentações de bovinos do Estado do Mato Grosso, 2007, Brasil. Foram feitas diversas simulações a fim de verificar o espalhamento de doenças agudas e crônicas nessas redes. Diferentes dinâmicas de espalhamento de doenças infecciosas foram observadas em redes com a mesma distribuição de graus e diferentes estruturas topológicas. Espera-se que os resultados das simulações matemáticas possam auxiliar nas atividades dos órgãos responsáveis pela vigilância epidemiológica e incentivar outros Estados a seguirem o exemplo do Estado do Mato Grosso, a construírem bancos de dados que possam ser analisados utilizando a metodologia de redes. / The animals\' movements in a farms network and the spread of some animal diseases are intrinsically related. Therefore, comprehending the dynamics of the spreading of infectious diseases in these networks is an important tool in controlling these diseases. In this project, we have implemented algorithms to generate hypothetical networks of animals\' movements and rebuilt the network of bovine movements from the State of Mato Grosso, 2007, Brazil. We made several simulations in order to check the spreading of acute and chronic disease in these networks. Different dynamics of infectious disease spreading were observed in networks with the same degree distribution and different topological structure. We hope that the results of the mathematical simulations may assist in the activities of agencies responsible for disease surveillance and encourage other States to follow the example of the State of Mato Grosso, to build databases that can be analyzed using the methodology of networks.

A dinâmica de movimentação de animais em uma rede de propriedades rurais e o espalhamento de algumas doenças animais estão intrinsecamente relacionados. Assim, compreender a dinâmica do espalhamento de doenças infecciosas nestas redes é um instrumento importante no controle destas. Neste projeto, foram implementados algoritmos para gerar redes de movimentação de animais hipotéticas e reconstruiu-se a rede de movimentações de bovinos do Estado do Mato Grosso, 2007, Brasil. Foram feitas diversas simulações a fim de verificar o espalhamento de doenças agudas e crônicas nessas redes. Diferentes dinâmicas de espalhamento de doenças infecciosas foram observadas em redes com a mesma distribuição de graus e diferentes estruturas topológicas. Espera-se que os resultados das simulações matemáticas possam auxiliar nas atividades dos órgãos responsáveis pela vigilância epidemiológica e incentivar outros Estados a seguirem o exemplo do Estado do Mato Grosso, a construírem bancos de dados que possam ser analisados utilizando a metodologia de redes. / The animals\' movements in a farms network and the spread of some animal diseases are intrinsically related. Therefore, comprehending the dynamics of the spreading of infectious diseases in these networks is an important tool in controlling these diseases. In this project, we have implemented algorithms to generate hypothetical networks of animals\' movements and rebuilt the network of bovine movements from the State of Mato Grosso, 2007, Brazil. We made several simulations in order to check the spreading of acute and chronic disease in these networks. Different dynamics of infectious disease spreading were observed in networks with the same degree distribution and different topological structure. We hope that the results of the mathematical simulations may assist in the activities of agencies responsible for disease surveillance and encourage other States to follow the example of the State of Mato Grosso, to build databases that can be analyzed using the methodology of networks.

A movimentação de animais em uma rede de fazendas e o espalhamento de algumas doenças animais estão intrinsecamente relacionados. Assim, compreender a dinâmica do espalhamento de doenças infecciosas nestas redes é um instrumento importante no controle dessas doenças. Usando as informações sobre as movimentações de bovinos no estado de Mato Grosso, Brasil, em 2007, reconstruiu-se a rede de trânsito e a rede de proximidade geográfica entre os estabelecimentos desse estado, além de redes hipotéticas seguindo os modelos de rede Molloy-Reed, Kalisky, Método A e Método B, onde simulou-se, usando diferentes configurações do modelo SLIRS, o espalhamento de doenças com parâmetros hipotéticos e reais (brucelose e febre aftosa). Além disso, simulou-se o controle do espalhamento dessas doenças considerando o controle por imunização e por restrição, com e sem rearranjo das movimentações após a restrição, selecionando os estabelecimentos a serem protegidos de forma aleatória, baseando-se no grau de movimentação dos animais e utilizando o conceito do paradoxo da amizade. Dentre os resultados, destacam-se que apesar dos padrões das curvas de prevalência nas redes hipotéticas serem semelhantes aos da rede real, os valores observados foram maiores nas redes hipotéticas, indicando que utilizá-las no planejamento de políticas de controle de doenças no lugar da rede real pode levar a um maior uso de recursos do que seria necessário. Além disso, no controle das doenças tanto com parâmetros hipotéticos quanto com parâmetros reais, nas simulações usando apenas a rede de trânsito dos animais, observou-se uma redução mais efetiva da prevalência ao se selecionar os estabelecimentos com maior grau total do que a da seleção aleatória, enquanto que nas simulações que consideraram a rede de proximidade geográfica dos estabelecimentos, a redução na prevalência das estratégias que selecionaram estabelecimentos específicos foram semelhantes aos da seleção aleatória. Sobre o efeito do rearranjo das movimentações, observou-se que este pode facilitar o espalhamento de doenças na rede, mesmo nas situações em que se aplica alguma estratégia de controle. Espera-se que os resultados das simulações matemáticas possam contribuir para a discussão do impacto relativo entre as estratégias de controle mencionadas e que futuramente possam auxiliar nas atividades dos órgãos responsáveis pela vigilância epidemiológica e no desenvolvimento de políticas de prevenção e controle de doenças em animais. / The animals’ movements in a farms network and the spread of some animal diseases are intrinsically related. Therefore, comprehending the dynamics of the spreading of infectious diseases in these networks is an important tool in controlling these diseases. Using the information about the bovine movements from the State of Mato Grosso, Brazil, in 2007, we rebuilt the network of animal movements and the geographic proximity network between the premises of this state, in addition to hypothetical networks following the network models Molloy-Reed, Kalisky, Method A and Method B, where we simulated, using different configurations of the model SLIRS, the spread of diseases with hypothetical parameters e real ones (brucellosis and foot and mouth disease). Moreover, we simulated the control of these diseases spreading, considering the control by immunization and by restriction, with and without the rearrangement of the movements after the restriction, selecting the premises to be protected randomly, based on the degree of animal’s movements and using the concept of the friendship paradox. Among the results, stands out that although the pattern of the prevalence curves in the hypothetical networks were similar to the ones in the real network, the observed values were higher in the hypothetical networks, indicating that using them in the planning of policies to control diseases in place of the real network might lead to a greater expense of resources than it would be necessary. Furthermore, in the control of the diseases both with hypothetical parameters as well as with real parameters, in the simulations using only the animal’s movements network, it was observed a more effective reduction of the prevalence when selecting the premises with the highest total degree than the random selection, while in the simulations that considered the network of geographic proximity of the premises, the reduction in the prevalence of the strategies that selected specific premises were similar to the random selection. On the effect of rearranging the movements, it was observed that it may facilitate the spread of diseases in the network even in situations where some control strategy is used. We hope that the results of the mathematical simulations may contribute to the discussion of the relative impact of the mentioned control strategies and that in the future they may assist in the activities of agencies responsible for disease surveillance and in the development of policies to prevent and control diseases in animals.

Das Verständnis der komplexen Interaktionen innerhalb des weltweiten Transportnetzes ist ein essentieller Schritt auf dem Weg zur Vorhersage der Krankheitsausbreitung und Entwicklung von effektiven Gegenmaßnahmen. Ungeachtet der weltweiten Vernetzung werden die politischen Entscheidungen oft von nationaler, regionaler und egozentrischen Denkweise geleitet. Die Ebola-Epidemie in 2014 demonstrierte deutlich, dass solche Herangehensweise modernen Epidemien nicht gerecht werden kann. In dieser Dissertation werden mehrere Methoden entwickelt, welche es ermöglichen während einer Epidemie die globalen Teilnehmer entsprechend ihrer Rolle einzustufen und das Risiko des Krankheitsexports zu berechnen. Die Methodik wird analytisch und numerisch ausführlich diskutiert. Darüber hinaus werden Lösungen für hypothetische und reale Epidemien auf dem Flugverkehrsnetz vorgestellt. Im zweiten Teil wird mit Hilfe eines vereinfachten spieltheoretischen Modells der Prozess der Ressourcenverteilung zur Epidemieeindämmung untersucht. Dabei erfolgt die Verteilung der Ressourcen von den Knoten und kann in egozentrischer oder altruistischer Weise erfolgen. Im Rahmen der Modells liegen die Optima für das altruistische und egozentrische System eng beieinander, solange der ausbruch räumlich konzentriert ist. In diesem Fall ist es optimal alle Ressourcen in den Ausbruchsknoten zu investieren. Bei lokal getrennten Ausbrüchen streben die Systeme verschiedene Gleichgewichte an. In allen Aspekten der Arbeit wird netzwerkbasierte Repräsentation des Systems verwendet, so dass die Orte durch Knoten innerhalb eines Transportnetzwerkes abgebildet werden. Die vorliegende Arbeit vereint mehrere Vorteileder etablierten Methoden: während der Schwerpunkt auf der Topologie des Netzwerkes liegt, berücksichtigt die vorgestellte Methodik den Ursprungsort der Epidemie. / The growing complexity of the global mobility is a key challenge for the understanding of the worldwide spread of emergent infectious diseases and the design of effective containment strategies. Despite global connectivity, containment policies are often based on national, regional and ’egocentric’ assessments of outbreak situations that are no longer effective or meaningful, as recently demonstrated by 2014 Ebola outbreak in West Africa, where months passed before a concerted, international effort followed. Despite the importance of the matter, optimal strategies in highly connected non-local settings are poorly understood. In the work at hand we propose a set of methods for more informed decision making during and prior to a pandemic. All of the studied systems are represented by networks in analogz the traffic networks, which play a dominant role during the global disease spreading. We introduce methods to calculate the risk of disease importation in a specific location and to determine the role of a node during an outbreak. Using the world aviation network, we demonstrate how the methods can be applied on real and hypothetical pandemics. We show that the airports can be divided into two distinct groups according to the role they take on in distributing the disease. Further, investigate the allocation of resources as a game theoretic dilemma. We embrace a bottom-up approach to this question, allowing the nodes of the network to distribute the resourses. We investigate egocentric and altruistic strategies and conclude that the optimal state of both systems are very similar if the outbreak is spacially confined. In this case allocation of resources ti the affected nodes is the optimal strategy. When there are multiple independent outbreaks, the optima diverge substantially. To foster the benefits of multiple approaches, the work at hand combines the information on the network topology but also regard some specifics of the outbreak at hand outbreak.

L’épizootie de fièvre aphteuse de 2001 telle qu’elle s’est déroulée en Grande-Bretagne a montré les limites de certains des systèmes de surveillance, d’intervention, d’anticipation et d’aide à la décision actuellement en place. Parallèlement, l’assouplissement des modalités d’utilisation de la vaccination a enrichi la palette des outils utilisables par le gestionnaire de risque. Une réévaluation pour la France a semblé ainsi opportune. Pour cela, le projet de recherche s’est proposé tout d’abord d’étudier l’organisation des différentes filières d’animaux de rente en France. L’analyse du réseau d’élevages français par la méthode d’analyse des réseaux sociaux a permis de caractériser les relations entre établissements et d’estimer une vulnérabilité structurale constante face à la diffusion de maladies apportées essentiellement par le réseau d’échanges bovins.Dans une deuxième partie, la diffusion de la maladie dans ce réseau d’élevages a été étudiée en s’appuyant sur des simulations générées par un modèle spécifiquement construit. L’efficacité et les coûts de différentes stratégies de lutte envisageables (combinaisons d’abattage sanitaire, abattage préventif et vaccination) ont été ensuite comparés. Les résultats obtenus ont montré l’absence d’une stratégie unique optimale à la fois sur le plan épidémiologique et économique et la nécessité de s’adapter au contexte local. En effet, la nature de la stratégie optimale varie selon la région concernée et l’acteur considéré. Ces travaux ont permis de créer un outil de réflexion pour aider à la décision, mais également un outil d’entraînement et de formation collective pour se préparer à une telle gestion de crise. / The 2001 Foot-and-mouth disease epizootic in the United Kingdom has illustrated limits in some established surveillance, control, anticipation and decision-making systems. At the same time, the relaxation of vaccination procedures has enhanced the set of usable tools by risk managers. A reassessment in France seemed needed.For this purpose, the research project firstly proposed to study the organization of the different livestock industries in France. The analysis of French holding network by using the method of social network analysis has led to characterize the relationships between holdings and to determine a constant structural vulnerability to diseases spread especially due to bovine trade network.Secondly, the disease spread in the holding network has been studied with simulations generated by a specifically built model. The cost-effectiveness of different control strategies (combining infected herd depopulation, pre-emptive culling and vaccination) were then compared. Results showed that no single epidemiological and economical optimal strategy existed and local context must be taken into account. Indeed, the cost-effective strategy changed according to the concerned area and the considered players.This research work allowed creating a thinking tool for decision-making but also a training tool for crisis management preparation.