abstract: Extraordinary medical advances have led to significant reductions in the burden of infectious diseases in humans. However, infectious diseases still account for more than 13 million annual deaths. This large burden is partly due to some pathogens having found suitable conditions to emerge and spread in denser and more connected host populations, and others having evolved to escape the pressures imposed by the rampant use of antimicrobials. It is then critical to improve our understanding of how diseases spread in these modern landscapes, characterized by new host population structures and socio-economic environments, as well as containment measures such as the deployment of drugs. Thus, the motivation of this dissertation is two-fold. First, we study, using both data-driven and modeling approaches, the the spread of infectious diseases in urban areas. As a case study, we use confirmed-cases data on sexually transmitted diseases (STDs) in the United States to assess the conduciveness of population size of urban areas and their socio-economic characteristics as predictors of STD incidence. We find that the scaling of STD incidence in cities is superlinear, and that the percent of African-Americans residing in cities largely determines these statistical patterns. Since disparities in access to health care are often exacerbated in urban areas, within this project we also develop two modeling frameworks to study the effect of health care disparities on epidemic outcomes. Discrepant results between the two approaches indicate that knowledge of the shape of the recovery period distribution, not just its mean and variance, is key for assessing the epidemiological impact of inequalities. The second project proposes to study, from a modeling perspective, the spread of drug resistance in human populations featuring vital dynamics, stochasticity and contact structure. We derive effective treatment regimes that minimize both the overall disease burden and the spread of resistance. Additionally, targeted treatment in structured host populations may lead to higher levels of drug resistance, and if drug-resistant strains are compensated, they can spread widely even when the wild-type strain is below its epidemic threshold. / Dissertation/Thesis / Ph.D. Applied Mathematics for the Life and Social Sciences 2014

Este trabalho, ao apresentar os conceitos básicos da Epidemiologia Matemática e da modelagem de populações por classes etárias, tem por objetivo desenvolver e implementar três modelos epidemiológicos de transmissão do dengue, a fim de avaliar teoricamente os efeitos da aplicação de inseticidas em populações de Aedes aegypti, em relação às epidemias de dengue. Uma variedade de métodos têm sido empregados no controle do vetor, sendo o Aedes aegypti a principal espécie envolvida na transmissão do dengue. A· aplicação de inseticidas de ultrabaixo volume (UL V) é uma das técnicas amplamente utilizada, particularmente durante epidemias. Tal técnica tem como objetivo matar os mosquitos adultos (adulticida). Há muita controvérsia em tomo destas aplicações, no que diz respeito ao impacto no controle da transmissão do dengue. Desta forma, através deste trabalho, procuramos observar a influência do uso de inseticida na dinâmica populacional do vetor transmissor e na dinâmica da epidemia, e analisar as circunstâncias em que o inseticida pode ser utilizado a fim de agir eficientemente no controle da transmissão do dengue. O emprego de larvicidas também é abordado, a fim de que se possa observar a influência deste na dinâmica populacional do vetor transmissor e na dinâmica da epidemia. Neste trabalho são detalhadas as hipóteses utilizadas na construção de cada modelo de transmissão do dengue apresentado. Apresentados os modelos, são considerados os aspectos relativos à implementação. Assim, mediante os aspectos teóricos envolvidos na modelagem e implementação, resultados numéricos são obtidos, através das simulações, as quais nos auxiliam a avaliar os efeitos da aplicação de inseticidas em populações de Aedes aegypti no controle da transmissão do dengue. / In this work the basic Mathematical Epidemiology ideas are presented and three models of Dengue Fever transrnission are developed in order to measure the effects of the use o f insecticides on the populations o f the mosquito Aedes aegypti that are related to the dengue epidemics. There is a good variety of control methods on the Aedes aegypti populations. The use of ultra-low volume (UL V) insecticides is widely employed specially during epidemics. The goal of such method is to eliminate a fraction of the adult mosquito population. There is a great deal o f controversy on the effectiveness o f insecticide use during a dengue epidemic. In this way we propose to investigate the impact o f UL V on the mosquito dynarnics and on the epidemics dynarnics as well in order to determine in which circumstances the use o f UL V can truly effective on the course o f a epidemic. On the same line, we also propose a study on the use of larvicides as a control method. In this study we detail the hypotheses that are used to construct the dynarnic models. Once the models are presented we consider the implementation details. The numerical results are obtained after various simulations which provide the data that allow us to measure the impact ofthe control technique on the dengue epidemics.

No description available.

For decades, dengue virus has been a cause of major public health concern in Costa Rica, due to its landscape and climatic conditions that favor the circumstances in which the vector, Aedes aegypti, thrives. The emergence and introduction throughout tropical and subtropical countries of the chikungunya virus, as of 2014, challenged Costa Rican health authorities to provide a correct diagnosis since it is also transmitted by the same vector and infected hosts may share similar symptoms. We study the 2015–2016 dengue and chikungunya outbreaks in Costa Rica while establishing how point estimates of epidemic parameters for both diseases compare to one another. Longitudinal weekly incidence reports of these outbreaks signal likely misdiagnosis of infected individuals: underreporting of chikungunya cases, while overreporting cases of dengue. Our comparative analysis is formulated with a single-outbreak deterministic model that features an undiagnosed class. Additionally, we also used a genetic algorithm in the context of weighted least squares to calculate point estimates of key model parameters and initial conditions, while formally quantifying misdiagnosis.

<p>Infectious diseases spreading in a human population can occasionally exhibit sudden transitions in their qualitative dynamics. Previous work has been very successful in predicting such transitions in New York City's measles incidence rates using the standard SIR model (susceptible, infected, recovered). This work relied on a dataset spanning 45 years, which we have extended to 93 years (1891-1984). We continue previous research in transition analysis on this larger dataset, and compare resonant and transient periods predicted to exist in NYC's measles incidence rates with those observed through a continuous wavelet transform of the data. We find good agreement between SIR predictions and observation, and in particular note the likely existence of previously unobserved hysteresis early in our new time-series.</p> / Master of Science (MSc)

Ce travail de thèse traite de la modélisation et du contrôle des maladies infectieuses à l’aide des automates cellulaires. Nous nous sommes d’abord focalisés sur l’étude d’un modèle de type SEIR. Nous avons pu monter d’une part qu’un voisinage fixe pouvait entrainer une sous-évaluation de l’incidence et de la prévalence et d’autre part que sa structure a un impact direct sur la structure de la distribution de la maladie. Nous nous sommes intéressés également la propagation des maladies vectorielles à travers un modèle de type SIRS-SI multi-hôtes dans un environnement hétérogène.Les hôtes y étaient caractérisés par leur niveau de compétence et l’environnement par la variation du taux de reproduction et de mortalité. Son application à la maladie de Chagas, nous a permis de montrer que l’hétérogénéité de l’habitat et la diversité des hôtes contribuaient à faire baisser l’infection. Cependant l’un des principaux résultats de notre travail à été la formulation du nombre de reproduction spatiale grâce à deux matrices qui représentent les coefficients d’interactions entre les différentes cellules du réseau. / This PhD thesis considers the general problem of epidemiological modelling and control using cellular automata approach.We first focused on the study of the SEIR model. On the one hand, we have shown that the traditionnal neighborhood contribute to underestimate the incidence and prevalence of infection disease. On the other hand, it appeared that the spatial distribution of the cells in the lattice have a real impact on the disease spreading. The second study concerns the transmission of the vector-borne disease in heterogeneous landscape with host community. We considered a SIRS-SI with various level of competence at witch the environnment heterogeneity has been characterized by the variation of the birth flow and the death rate. We simulated the Chagas disease spreading and shown that the heterogeneity of habitat and host diversity contribute to decrease the infection. One of the most important results of our work, was the proposition of the spatial reproduction number expression based on two matrices that represent the interaction factors between the cells in the lattice.

<div>Wildlife diseases are an increasingly growing concern for public health managers, conservation biologists, and society at large. These diseases may be zoonotic -- infective wildlife are able to spread pathogens to human populations. Animal or plant species of conservation concern may also be threatened with extinction or extirpation due to the spread of novel pathogens into their native ranges. In this thesis, I develop some mathematical methods for understanding the dynamics of vector-borne diseases in wildlife populations which include several elements of host and vector biology. </div><div><br></div><div>We consider systems where a vector-borne pathogen is transmitted to a host population wherein individuals either die to disease or recover, remaining chronically infective. Both ordinary differential equations (ODE) and individual based (IBM) models of such systems are formulated then applied to a specific system of wildlife disease: avian malaria in Hawaiian honeycreeper populations -- where some species endure disease-induced mortality rates exceeding 90\%. The ODE model predicts that conventional management methods cannot fully stop pathogen transmission.</div><div><br></div><div>Vector dispersal and reproductive biology may also play a large role in the transmission of vector-borne diseases in forested environments. Using an IBM which models dispersal and mosquito reproductive biology, we predict that reducing larval habitat at low elevations is much more effective than at higher elevations. The ODE model is extended to include distinct populations of sensitive and tolerant hosts. We find that the form which interaction between the hosts takes has a significant impact on model predictions.</div>

In mathematical epidemiology, disease transmission is commonly assumed to behave in accordance with the law of mass action; however, other disease incidence terms also exist in the literature. A homogeneous Susceptible-Infectious-Removed (SIR) model with a generalized incidence term is presented along with analytic and numerical results concerning effects of the generalization on the global disease dynamics. The spatial heterogeneity of the metapopulation with nonrandom directed movement between populations is incorporated into a heterogeneous SIR model with nonlinear incidence. The analysis of the combined effects of the spatial heterogeneity and nonlinear incidence on the disease dynamics of our model is presented along with supporting simulations. New global stability results are established for the heterogeneous model utilizing a graph-theoretic approach and Lyapunov functions. Numerical simulations confirm nonlinear incidence gives raise to rich dynamics such as synchronization and phase-lock oscillations.

Ce document est dédié à la modélisation dynamique des interactions hôtes-parasites. Il porte sur deux modèles biologiques très différents, mais étudiés à l’aide de modèles épidémiologiques standards construits à partir de systèmes dynamiques à compartiments. La première contribution est l’implémentation d’un modèle ‘micro-parasites’ pour étudier la transmission du parasite protozoaire Trypanosoma cruzi, agent étiologique de la trypanosomiase américaine (ou ‘maladie de Chagas’), au sein d’une communauté d’hôtes synanthropiques et domestiques. L’analyse du modèle mathématique montre pour la première fois dans ce système biologique un effet de dilution associé aux hôtes aviaires, ainsi que la possibilité de réduire la transmission à l’homme par modification de la composition de la communauté d’hôtes domestiques. La seconde contribution porte sur la dynamique des ‘parasites génomiques’ que sont les éléments transposables. En utilisant les analogies entre concepts de génomique et d’écologie proposées par l’approche d’ « Écologie du génome », il a été possible d’adapter des modèles développés pour les ‘macro-parasites’ à la dynamique d’éléments transposables de classe 1, les retro-transposons. L’analyse de cesmodèles permet de formuler des hypothèses sur l’importance relative de la démographie des hôtes, de la distribution du nombre de copies entre les individus et des mécanismes moléculaires de silencing de ces éléments, sur leurpersistance au sein de population d’hôtes se reproduisant de façon asexuée. / This document is dedicated to the dynamic modeling of host-parasite interactions. It is about two distant biological models, who are studied using standard epidemiological models built from dynamic compartmental models. The first contribution is the implementation of a 'micro-parasites' model to study the transmission of the protozoan parasite Trypanosoma cruzi, the etiological agent of American trypanosomiasis (or 'Chagas' disease), within a host community of synanthropic and domestic animals. The analysis of the mathematical model shows for the first time in this biological system a dilution effect associated with avian hosts, as well as the possibility of reducing the transmission to humans by modifying the composition of the domestic host communities. The second contribution deals with the dynamics of the "genomic parasites" that are the transposable elements. Using the analogies between genomics and ecology concepts proposed by the "Genome Ecology" approach, it was possible to adapt models developed for 'macro-parasites' to the dynamics of transposable elements of class 1, retro-transposons. The analysis of these models makes it possible toformulate hypotheses on the relative importance of the host demography, the distribution of the number of copies between individuals and the molecular mechanisms of silencing of these elements, on their persistence within the population of hosts reproducing asexually.

Em epidemiologia matemática, muitos modelos de propagação de doenças infecciosas em populações têm sido analisados matematicamente e aplicados para doenças específicas. Neste trabalho um modelo de propagação de dengue é analisado considerando-se diferentes hipóteses sobre o tamanho da população humana. Mais precisamente, estamos interessados em verificar o impacto das variações populacionais a longo prazo no cálculo do parâmetro Ro e no equilíbrio endêmico. Vamos discutir algumas ideias que nortearam o processo de definição do parâmetro Ro a partir da construção do Operador de Próxima Geração. Através de um estudo qualitativo do modelo matemático, obtivemos que o equilíbrio livre de doença é globalmente assintoticamente estável se Ro é menor ou igual a 1 e instável se Ro>1. Para Ro>1, a estabilidade global do equilíbrio endêmico é provada usando um critério geral para estabilidade orbital de órbitas periódicas associadas a sistemas autônomos não lineares de altas ordens e resultados da teoria de sistemas competitivos para equações diferenciais ordinárias. Também foi desenvolvida uma análise de sensibilidade do Ro e do equilíbrio endêmico com relação aos parâmetros do modelo de propagação. Diversos cenários foram simulados a partir dos índices de sensibilidade obtidos nesta análise. Os resultados demonstram que, de forma geral, o parâmetro Ro e o equilíbrio endêmico apresentam considerável sensibilidade a taxa de picadas do vetor e a taxa de mortalidade do vetor. / In mathematical epidemiology many models of spread of infectious diseases in populations have been analyzed mathematically and applied to specific diseases. In this work a dengue propagation model is analyzed considering different assumptions about the size of the human population. More precisely, we are interested to verify the impact of population long-term variations in the calculation of the parameter Ro and endemic equilibrium. We will discuss some ideas that guided the parameter setting process Ro from the construction of the Next Generation Operator. Through a qualitative study of the mathematical model, we found that the disease-free equilibrium is globally asymptotically stable if Ro is less or equal than 1 and unstable if Ro> 1. For Ro> 1 the global stability of the endemic equilibrium is proved using a general criterion for orbital stability of periodic orbits associated with nonlinear autonomous systems of higher orders and results of the theory of competitive systems for ordinary differential equations. Also a sensitivity analysis of the Ro and the endemic equilibrium with respect to the parameters of the propagation model was developed. Several scenarios were simulated from the sensitivity index obtained in this analysis. The results demonstrate that in general the parameter Ro and the endemic equilibrium are the most sensitive to the vector biting rate and the vector mortality rate.