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Bate, Andrew M. "Mathematical models in eco-epidemiology." Thesis, University of Bath, 2014. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.616875.
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Diseases have the capacity to not only influence the dynamics of their hosts, but also interacting species like predators, prey and competitors. Likewise, interacting species can influence disease dynamics by altering the host's dynamics. The combination of these two effects is often called eco-epidemiology, the interaction of ecology and epidemiology. In this thesis, we explore this interplay of infectious diseases and predator--prey interactions, where the predator is a specialist. We start with an introductory chapter on modelling eco-epidemiology, with a particular focus on the myriad of different possible assumptions mathematical models in eco-epidemiology can have. In Chapter 2, we consider the effect predator--prey oscillations have on the endemic criteria for an infectious disease. In Chapter 3, we find a great variety of complex dynamics like tristability between endemic and disease-free states, quasi-periodic dynamics and chaos in a predator--prey model with an infectious disease in the predator. In Chapter 4, we consider the impact an infectious disease has on a group defending prey. Here, we find that the disease not only can coexist with a predator, it can actually help the predator survive where it could not in the absence of the disease, in stark contradiction to the principle of competitive exclusion which states that two exploiters should not coexist on a single resource. Lastly, in Chapter 5, we consider a spatial predator--prey model with a disease in the prey and focus on how preytaxis (the movement of predators along prey gradients) can alter various invasion scenarios. Through all these chapters, there is a common focus on the impact (endogenous) oscillations have in eco-epidemiology.
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Booton, Ross D. "Mathematical models of stress and epidemiology." Thesis, University of Sheffield, 2018. http://etheses.whiterose.ac.uk/22549/.
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De, la Harpe Alana. "A comparative analysis of mathematical models for HIV epidemiology." Thesis, Stellenbosch : Stellenbosch University, 2015. http://hdl.handle.net/10019.1/96983.
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Thesis (MSc)--Stellenbosch University, 2015.ENGLISH ABSTRACT: HIV infection is one of the world’s biggest health problems, with millions of people infected worldwide. HIV infects cells in the immune system, where it primarily targets CD4+ T helper cells and without treatment, the disease leads to the collapse of the host immune system and ultimately death. Mathematical models have been used extensively to study the epidemiology of HIV/AIDS. They have proven to be effective tools in studying the transmission dynamics of HIV. These models provide predictions that can help better our understanding of the epidemiological patterns of HIV, especially the mechanism associated with the spread of the disease. In this thesis we made a functional comparison between existing epidemiological models for HIV, with the focus of the comparison on the force of infection (FOI). The spread of infection is a crucial part of any infectious disease, as the dynamics of the disease depends greatly on the rate of transmission from an infectious individual to a susceptible individual. First, a review was done to see what deterministic epidemiological models exist. We found that many manuscripts do not provide the necessary information to recreate the authors’ results and only a small amount of the models could be simulated. The reason for this is mainly due to a lack of information or due to mistakes in the article. The models were divided into four categories for the analysis. On the basis of the FOI, we distinguished between frequency- or density-dependent transmission, and as a second criterion we distinguished models on the sexual activity of the AIDS group. Subsequently, the models were compared in terms of their FOI, within and between these classes. We showed that for larger populations, frequency-dependent transmission should be used. This is the case for HIV, where the disease is mainly spread through sexual contact. Inclusion of AIDS patients in the group of infectious individuals is important for the accuracy of transmission dynamics. More than half of the studies that were selected in the review assumed that AIDS patients are too sick to engage in risky sexual behaviour. We see that including AIDS patients in the infectious individuals class has a significant effect on the FOI when the value for the probability of transmission for an individual with AIDS is bigger than that of the other classes. The analysis shows that the FOI can vary depending on the parameter values and the assumptions made. Many models compress various parameter values into one, most often the transmission probability. Not showing the parameter values separately makes it difficult to understand how the FOI works, since there are unknown factors that have an influence. Improving the accuracy of the FOI can help us to better understand what factors influence it, and also produce more realistic results. Writing the probability of transmission as a function of the viral load can help to make the FOI more accurate and also help in the understanding of the effects that viral dynamics have on the population transmission dynamics.
AFRIKAANSE OPSOMMING: MIV-infeksie is een van die wêreld se grootste gesondheidsprobleme, met miljoene mense wat wêreldwyd geïnfekteer is. MIV infekteer selle in die immuunstelsel, waar dit hoofsaaklik CD4+ T-helperselle teiken. Sonder behandeling lei die siekte tot die ineenstorting van die gasheer se immuunstelsel en uiteindelik sy dood. Wiskundige modelle word breedvoerig gebruik om die epidemiologie van MIV/vigs te bestudeer. Die modelle is doeltreffende instrumente in die studie van die oordrag-dinamika van MIV. Hulle lewer voorspellings wat kan help om ons begrip van epidemiologiese patrone van MIV, veral die meganisme wat verband hou met die verspreiding van die siekte, te verbeter. In hierdie tesis het ons ‘n funksionele vergelyking tussen bestaande epidemiologiese modelle vir MIV gedoen, met die fokus van die vergelyking op die tempo van infeksie (TVI). Die verspreiding van infeksie is ‘n belangrike deel van enige aansteeklike siekte, aangesien die dinamika van die siekte grootliks afhang van die tempo van oordrag van ‘n aansteeklike persoon na ‘n vatbare persoon. ‘n Oorsig is gedoen om te sien watter kompartementele epidemiologiese modelle alreeds bestaan. Ons het gevind dat baie van die manuskripte nie die nodige inligting voorsien wat nodig is om die resultate van die skrywers te repliseer nie, en slegs ‘n klein hoeveelheid van die modelle kon gesimuleer word. Die rede hiervoor is hoofsaaklik as gevolg van ‘n gebrek aan inligting of van foute in die artikel. Die modelle is in vier kategorieë vir die analise verdeel. Op grond van die TVI het ons tussen frekwensie- of digtheidsafhanklike oordrag onderskei, en as ‘n tweede kriterium het ons die modelle op die seksuele aktiwiteit van die vigs-groep onderskei. Daarna is die modelle binne en tussen die klasse vergelyk in terme van hul TVIs. Daar is gewys dat frekwensie-afhanklike oordrag gebruik moet word vir groter bevolkings. Dit is die geval van MIV, waar die siekte hoofsaaklik versprei word deur seksuele kontak. Die insluiting van die vigs-pasiënte in die groep van aansteeklike individue is belangrik vir die akkuraatheid van die oordrag-dinamika van MIV. Meer as helfte van die uitgesoekte studies aanvaar dat vigs-pasiënte te siek is om betrokke te raak by riskante seksuele gedrag. Ons sien dat die insluiting van vigs-pasiënte in die groep van aansteeklike individue ‘n beduidende uitwerking op die TVI het wanneer die waarde van die waarskynlikheid van oordrag van ‘n individu met vigs groter is as dié van die ander klasse. Die analise toon dat die TVI kan wissel afhangende van die parameter waardes en die aannames wat gemaak is. Baie modelle voeg verskeie parameter waardes bymekaar vir die waarskynlikheid van oordrag. Wanneer die parameter waardes nie apart gewys word nie, is dit moeilik om die werking van die TVI te verstaan, want daar is onbekende faktore wat ‘n invloed op die TVI het. Die verbetering van die akkuraatheid van die TVI kan ons help om die faktore wat dit beïnvloed beter te verstaan, en dit kan ook help om meer realistiese resultate te produseer. Om die waarskynlikheid van oordrag as ‘n funksie van die viruslading te skryf kan help om die TVI meer akkuraat te maak en dit kan ook help om die effek wat virale dinamika op die bevolkingsoordrag-dinamika het, beter te verstaan.
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Otieno, Andrew Alex Omondi. "Application of lie group analysis to mathematical models in epidemiology." Thesis, Walter Sisulu University, 2013. http://hdl.handle.net/11260/100.
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Lie group analysis is arguably the most systematic vehicle for finding exact solutions of differential equations. Using this approach one has at one's disposal a variety of algorithms that make the solution process of many differential equations algorithmic. Vital properties of a given differential equation can often be inferred from the symmetries admitted by the equation. However, Lie group analysis has not enjoyed wide-spread application to systems of first-order ordinary differential equations. This is because such systems typically admit an infinite number of Lie point symmetries, and there is no systematic way to find even a single nontrivial one-dimensional Lie symmetry algebra. In the few applications available, the approach has been to circumvent the problem by transforming a given system of first-order ordinary differential equations into one in which at least one of the equations is of order two or greater. It is therefore fair to say that the full power of Lie group analysis has not been sufficiently harnessed in the solution of systems of first-order ordinary differential equations. In this dissertation we review some applications of Lie group analysis to systems of first order ordinary differential equations. We shed light on the integration procedure for first-order systems of ordinary differential equations admitting a solvable Lie algebra. We do this via instructive examples drawn from mathematical epidemiology models. In particular we revisit the work of Nucci and Torrisi [54] and improve the exposition of the Lie-symmetry-inspired solution of a mathematical model which describes a HIV transmission. To aid implementation of the integration strategy for systems of ordinary differential equations, we have developed ad-hoc routines for finding particular types of admitted symmetries and checking if a given symmetry is indeed admitted by a system of ordinary differential equations.
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Lutambi, Angelina Mageni. "Basic properties of models for the spread of HIV/AIDS." Thesis, Stellenbosch : Stellenbosch University, 2007. http://hdl.handle.net/10019.1/19641.
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Thesis (MSc)--University of Stellenbosch, 2007.ENGLISH ABSTRACT: While research and population surveys in HIV/AIDS are well established in developed countries, Sub-Saharan Africa is still experiencing scarce HIV/AIDS information. Hence it depends on results obtained from models. Due to this dependence, it is important to understand the strengths and limitations of these models very well. In this study, a simple mathematical model is formulated and then extended to incorporate various features such as stages of HIV development, time delay in AIDS death occurrence, and risk groups. The analysis is neither purely mathematical nor does it concentrate on data but it is rather an exploratory approach, in which both mathematical methods and numerical simulations are used. It was found that the presence of stages leads to higher prevalence levels in a short term with an implication that the primary stage is the driver of the disease. Furthermore, it was found that time delay changed the mortality curves considerably, but it had less effect on the proportion of infectives. It was also shown that the characteristic behaviour of curves valid for most epidemics, namely that there is an initial increase, then a peak, and then a decrease occurs as a function of time, is possible in HIV only if low risk groups are present. It is concluded that reasonable or quality predictions from mathematical models are expected to require the inclusion of stages, risk groups, time delay, and other related properties with reasonable parameter values.
AFRIKAANSE OPSOMMING: Terwyl navorsing en bevolkingsopnames oor MIV/VIGS in ontwikkelde lande goed gevestig is, is daar in Afrika suid van die Sahara slegs beperkte inligting oor MIV/VIGS beskikbaar. Derhalwe moet daar van modelle gebruik gemaak word. Dit is weens hierdie feit noodsaaklik om die moontlikhede en beperkings van modelle goed te verstaan. In hierdie werk word ´n eenvoudige model voorgelˆe en dit word dan uitgebrei deur insluiting van aspekte soos stadiums van MIV outwikkeling, tydvertraging by VIGS-sterftes en risikogroepe in bevolkings. Die analise is beklemtoon nie die wiskundage vorme nie en ook nie die data nie. Dit is eerder ´n verkennende studie waarin beide wiskundige metodes en numeriese simula˙sie behandel word. Daar is bevind dat insluiting van stadiums op korttermyn tot ho¨er voorkoms vlakke aanleiding gee. Die gevolgtrekking is dat die primˆere stadium die siekte dryf. Verder is gevind dat die insluiting van tydvestraging wel die kurwe van sterfbegevalle sterk be¨ınvloed, maar dit het min invloed op die verhouding van aangestekte persone. Daar word getoon dat die kenmerkende gedrag van die meeste epidemi¨e, naamlik `n aanvanklike styging, `n piek en dan `n afname, in die geval van VIGS slegs voorkom as die bevolking dele bevat met lae risiko. Die algehele gevolgtrekking word gemaak dat vir goeie vooruitskattings met sinvolle parameters, op grond van wiskundige modelle, die insluiting van stadiums, risikogroepe en vertragings benodig word.
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Lloyd, Alun Lewis. "Mathematical models for spatial heterogeneity in population dynamics and epidemiology." Thesis, University of Oxford, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.337603.
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McLean, A. R. "Mathematical models of the epidemiology of measles in developing countries." Thesis, Imperial College London, 1987. http://hdl.handle.net/10044/1/47259.
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Tosun, Kursad. "QUALITATIVE AND QUANTITATIVE ANALYSIS OF STOCHASTIC MODELS IN MATHEMATICAL EPIDEMIOLOGY." OpenSIUC, 2013. https://opensiuc.lib.siu.edu/dissertations/732.
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We introduce random fluctuations on contact and recovery rates in three basic deterministic models in mathematical epidemiology and obtain stochastic counterparts. This paper addresses qualitative and quantitative analysis of stochastic SIS model with disease deaths and demographic effects, and stochastic SIR models with/without disease deaths and demographic effects. We prove the global existence of a unique strong solution and discuss stochastic asymptotic stability of disease free and endemic equilibria. We also investigate numerical properties of these models and prove the convergence of the Balanced Implicit Method approximation to the analytic solution. We simulate the models with fairly realistic parameters to visualize our conclusions.
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Thompson, Brett Morinaga. "Development, Implementation, and Analysis of a Contact Model for an Infectious Disease." Thesis, University of North Texas, 2009. https://digital.library.unt.edu/ark:/67531/metadc9824/.
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With a growing concern of an infectious diseases spreading in a population, epidemiology is becoming more important for the future of public health. In the past epidemiologist used existing data of an outbreak to help them determine how an infectious disease might spread in the future. Now with computational models, they able to analysis data produced by these models to help with prevention and intervention plans. This paper looks at the design, implementation, and analysis of a computational model based on the interactions of the population between individuals. The design of the working contact model looks closely at the SEIR model used as the foundation and the two timelines of a disease. The implementation of the contact model is reviewed while looking closely at data structures. The analysis of the experiments provide evidence this contact model can be used to help epidemiologist study the spread of an infectious disease based on the contact rate of individuals.
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Griette, Quentin. "Mathematical and numerical analysis of propagation models arising in evolutionary epidemiology." Thesis, Montpellier, 2017. http://www.theses.fr/2017MONTS051/document.
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Cette thèse porte sur différents modèles de propagation en épidémiologie évolutive. L'objectif est d'en faire une analyse mathématique rigoureuse puis d'en tirer des enseignements biologiques. Dans un premier temps nous envisageons le cas d'une population d'hôtes répartis de manière homogène dans un espace linéaire, dans laquelle se propage un pathogène pouvant muter entre deux phénotypes plus ou moins virulents. Ce phénomène de mutation est à l'origine d'une interaction entre les dynamiques évolutive et épidémiologique du pathogène. Nous étudions la vitesse de propagation de l'épidémie et l'existence de fronts progressifs, ainsi que l'influence sur la vitesse de différents facteurs biologiques, comme des effets stochastiques liés à la taille de la population d'hôtes (explorations numériques). Dans un deuxième temps nous envisageons une hétérogénéité spatiale périodique dans la population d'hôtes, et l'existence de fronts pulsatoires pour le système de réaction-diffusion (non-coopératif) associé. Enfin nous considérons un pathogène pouvant muter vers un grand nombre de phénotypes différents et étudions l'existence de fronts potentiellement singuliers, modélisant ainsi une concentration sur un trait optimalIn this thesis we consider several models of propagation arising in evolutionary epidemiology. We aim at performing a rigorous mathematical analysis leading to new biological insights. At first we investigate the spread of an epidemic in a population of homogeneously distributed hosts on a straight line. An underlying mutation process can shift the virulence of the pathogen between two values, causing an interaction between epidemiology and evolution. We study the propagation speed of the epidemic and the influence of some biologically relevant quantities, like the effects of stochasticity caused by the hosts' finite population size (numerical explorations), on this speed. In a second part we take into account a periodic heterogeneity in the hosts' population and study the propagation speed and the existence of pulsating fronts for the associated (non-cooperative) reaction-diffusion system. Finally, we consider a model in which the pathogen is allowed to shift between a large number of different phenotypes, and construct possibly singular traveling waves for the associated nonlocal equation, thus modelling concentration on an optimal trait
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Penna, Maria Lucia Fernandes. "Dinâmica epidemiológica da tuberculose: um modelo matemático para simulação da efetividade do diagnóstico e tratamento dos casos." Universidade de São Paulo, 1994. http://www.teses.usp.br/teses/disponiveis/6/6132/tde-24012018-143330/.
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O presente trabalho desenvolve um modelo matemático multicompartimental, representado por um sistema de equações diferenciais ordinárias, da dinâmica epidemiológica da tuberculose. Modela-se, além do comportamento natural da doença, o tratamento de casos infectantes, enquanto medida de controle. Este último aspecto da modelagem leva em conta a duração do tratamento e a possibilidade de não adesão. Entre as premissas do modelo, destacam-se a ausência de resistência do bacilo ao esquema terapêutico, a mesma probabilidade de entrada em tratamento de casos já tratados anteriormente e casos novos e a ausência de circulação do HIV. Utilizou-se dados publicados na literatura para a estimativa dos parâmetros. A simulação da introdução da doença em uma população de suscetíveis leva ao equilíbrio, não tendo sido reproduzido o comportamento de queda duradoura da morbidade, observada em várias regiões do mundo. A simulação do tratamento dos casos infectantes produz uma redução acelerada da morbidade nos primeiros anos após o que, dependendo da taxa de entrada em tratamento, pode levar tanto a um novo equilíbrio, como produzir uma queda lenta, porém constante da morbidade tuberculosa, com tendência à extinção. O abandono do tratamento reduz a sua efetividade epidemiológica, mas na maioria das situações simuladas não anula completamente o impacto desta atividade de controle, mesmo no caso de taxas de abandono muito elevadas. É possível produzir soluções em que o abandono do tratamento leve a um prejuízo epidemiológico em relação ao comportamento da doença na ausência de intervenção, alterando-se parâmetros. O modelo proposto é apenas uma etapa na modelagem da dinâmica de transmissão da tuberculose na ausência de intervenção, se prestando, no entanto, enquanto instrumento lógico para simulações da efetividade de programas de controle.This study develops a mathematical model for the dynamics of tuberculosis, as a system of ordinary differential equations, The model includes the treatment of infectious cases as a control measure, allowing for simulation of non compliance, besides the natural behavior of the disease. The most important model\'s assumptions are bacilary sensibility to drugs, absence of HIV circulation, and treatment of new and old cases at the same rate. The parameters were estimated from data published in the medicai literatura. The simulation of the introduction of disease in a susceptible population leads to growing morbidity followed by an equilibrium point. The model did not reproduce the decreasing mortality observed in many countries before drugs were available. The simulation of the infectious cases treatment results in a rapid decrease of morbidity in the first few years, followed by a new steady state ar by a constant decrease at lower rate. The non compliance to the treatment reduce its effectivity as a contrai measure. Depending on certain parameters values, the non compliance may lead to an equilibrium point with higher morbidity than in the absence of any contrai measure, but in most of the simulations there was remaining treatment effectivity even with very high non compliance ratas. This model may be considered only a step in the work of modeling the natural tuberculosis dynamics, but it is already an important tool for the simulation of the effectivity of the control programmes.
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Mercado, Londoño Sergio Luis 1981. "Estimação do número de reprodução basal em modelos compartimentais." [s.n.], 2014. http://repositorio.unicamp.br/jspui/handle/REPOSIP/305840.
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Orientador: Luiz Koodi HottaDissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Matemática Estatística e Computação Científica
Made available in DSpace on 2018-08-24T12:49:57Z (GMT). No. of bitstreams: 1 MercadoLondono_SergioLuis_M.pdf: 1311356 bytes, checksum: 23c15e842c02af3c1dc7de3a2a46a5df (MD5) Previous issue date: 2014
Resumo: Uma das quantidades mais importante definida na epidemiologia é o número de reprodução basal, ou básico, associado com a pandemia e denotado por $R_0$. Ele proporciona uma medida da intensidade das intervenções necessárias para o controle da epidemia. Ao mesmo tempo, os modelos epidemiológicos compartimentais SIR, SEIR, tanto no enfoque enfoque determinístico quanto no estocástico, têm sido de grande ajuda para a compreensão dos mecanismos de transmissão de doenças infecciosas em todo o mundo. Esta dissertação apresenta alguns métodos para estimar esta quantidade através da utilização dos modelos epidemiológicos compartimentais. São considerados os quatro métodos apresentados por Chowell et al. (Mathematical Biosciences, 2007, v. 208, p. 571-589). O primeiro método é baseado na taxa de crescimento (inicial) exponencial da epidemia. Dada a taxa de crescimento exponencial e o modelo subjacente temos uma estimativa de $R_{0}$. No caso dos métodos 2 e 3 o processo de estimação do $R_0$ baseia-se nos modelos compartimentais, modelos SIR e SEIR no método 2, e em um modelo SEIR estendido no método 3. O método 4 utiliza uma abordagem bayesiana do modelo SIR estocástico. O objetivo da dissertação é estudar as propriedades dos estimadores baseados nos métodos 1, 2 e 4. Através de simulações são estimados os vícios, os erros quadráticos médios, as cobertura e as larguras dos intervalos de confiança. Os métodos são estudados quando os verdadeiros processos geradores de dados são os modelos SIR ou SEIR estocásticos. Inicialmente foram estudados os métodos, como apresentados por Chowell et al. (2007), e depois apresentadas modificações para melhorar o desempenho dos estimadores. A dissertação está organizada da seguinte forma: o Capítulo 2 consiste na apresentação dos modelos compartimentais, SIR e SEIR para análise das doenças infecciosas; tanto na abordagem determinística quanto estocástica. Este capítulo apresenta também o número de reprodução basal. O Capítulo 3 apresenta os quatro métodos de estimação apresentados em Chowell et al. (2007) para estimação do número de reprodução basal. O Capítulo 4 apresenta uma comparação de três dos quatro métodos através de simulação, quando o processo gerador de dados é um modelo SIR ou SEIR estocásticos. Neste capítulo também são apresentadas as modificações dos métodos. A conclusão final e as sugestões de trabalhos futuros são apresentadas no Capítulo 5
Abstract: The basic reproduction number, usually denoted by $R_0$, is one of the most important quantities defined in epidemiology and is associated with the potential of an infectious disease to spread through a population. It provides a measure of the intensity needed to control the epidemic interventions. At the same time, the compartmental epidemiological models SIR and SEIR , both in the deterministic and in the stochastic approach, have been very helpful for understanding the mechanisms of infectious diseases transmission. This paper considers the four methods presented by Chowell et al. (Mathematical Biosciences, 2007, v. 208, p. 571-589) to estimate $R_0$. All methods are based on compartmental epidemiological models. The first method is based on the epidemic (initial) exponential growth rate. Given an estimate of the exponential growth rate and an underlying compartmental model we have an estimate of $R_{0}$. The second method is based on fitting SIR or SEIR compartmental models, and the third method in fitting an extended SEIR model. The fourth method uses a Bayesian approach to a stochastic SIR model. The aim of this work is to study the properties of estimators based on methods 1, 2 and 4. The bias, the mean squared errors, the coverage and the widths of the confidence intervals are estimated through simulation. The methods are studied when the true data generating processes are the stochastic SIR or SEIR models. Initially the methods, as presented by Chowell et al. (2007), were studied and then presented modifications to improve the performance of the estimators. The dissertation is organized as follows: Chapter 2 consists of the presentation of compartmental SIR and SEIR models, the deterministic and stochastic approaches for analysis of infectious diseases. This chapter also presents the basic reproduction number. Chapter 3 explains the four estimation methods presented in Chowell et al. (2007) to estimate the basic reproduction number. Chapter 4 discusses and compares three of the four methods by simulation when the data generating process is a SIR or SEIR model. In this chapter the modifications of the methods are also considered. The final conclusion and suggestions for future work are presented in Chapter 5
Mestrado
Estatistica
Mestre em Estatística
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Littunen, Michael. "Mathematical Epidemiology : A study of the COVID-19 pandemic using compartmental models." Thesis, Linköpings universitet, Algebra, geometri och diskret matematik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-177288.
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The sudden occurrence of a global pandemic brought an imbalance to each of our ways of living. Prediction of the COVID-19 progresses is crucial for governments and is deemed essential for the healthcare industry to solve which indicates how mathematical modelling becomes in dire need of use This master thesis aims to use well-established compartmental models like SEIR and modifications of SEIR to simulate scenarios like introducing different restrictions (i.e. isolation of elders, closing schools) by first fitting parameters of the SEIR models to official data. An estimation of the true calculated number of COVID-19 cases in Denmark, Germany, Spain, Sweden and the United Kingdom is made by comparing the number of deceased cases with the number of confirmed cases between the first and second waves of the virus spread. A simulation showing the effect of the British variant B.1.1.7 had on the Swedish third wave is also made. The estimation made from comparing the first and second waves shows that the number of confirmed cases underestimates the true calculated number of cases with a factor between 7.57 and 36.5 depending on the country in consideration. The restriction simulations show that isolating elders decreases the number of elders that contract the disease but no significant change is seen in the total number of infected individuals. When restrictions like closing schools are simulated the total number of infected decreases significantly but the change in decreased cases among elders is not that high. The simulations also show that the British mutation B.1.1.7 with its increased infectiousness is responsible for the third wave of the virus spread. Without the existence of the British mutation, the Swedish third wave of virus spread would have been less severe.
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Corley, Courtney David. "Social Network Simulation and Mining Social Media to Advance Epidemiology." Thesis, University of North Texas, 2009. https://digital.library.unt.edu/ark:/67531/metadc11053/.
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Traditional Public Health decision-support can benefit from the Web and social media revolution. This dissertation presents approaches to mining social media benefiting public health epidemiology. Through discovery and analysis of trends in Influenza related blogs, a correlation to Centers for Disease Control and Prevention (CDC) influenza-like-illness patient reporting at sentinel health-care providers is verified. A second approach considers personal beliefs of vaccination in social media. A vaccine for human papillomavirus (HPV) was approved by the Food and Drug Administration in May 2006. The virus is present in nearly all cervical cancers and implicated in many throat and oral cancers. Results from automatic sentiment classification of HPV vaccination beliefs are presented which will enable more accurate prediction of the vaccine's population-level impact. Two epidemic models are introduced that embody the intimate social networks related to HPV transmission. Ultimately, aggregating these methodologies with epidemic and social network modeling facilitate effective development of strategies for targeted interventions.
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Sfikas, Nikolaos. "Mathematical models for vaccination programs and statistical analysis of infectious diseases of humans." Thesis, University of Strathclyde, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.248340.
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O'Neill, II Martin Joseph. "Computational Epidemiology - Analyzing Exposure Risk: A Deterministic, Agent-Based Approach." Thesis, University of North Texas, 2009. https://digital.library.unt.edu/ark:/67531/metadc11017/.
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Many infectious diseases are spread through interactions between susceptible and infectious individuals. Keeping track of where each exposure to the disease took place, when it took place, and which individuals were involved in the exposure can give public health officials important information that they may use to formulate their interventions. Further, knowing which individuals in the population are at the highest risk of becoming infected with the disease may prove to be a useful tool for public health officials trying to curtail the spread of the disease. Epidemiological models are needed to allow epidemiologists to study the population dynamics of transmission of infectious agents and the potential impact of infectious disease control programs. While many agent-based computational epidemiological models exist in the literature, they focus on the spread of disease rather than exposure risk. These models are designed to simulate very large populations, representing individuals as agents, and using random experiments and probabilities in an attempt to more realistically guide the course of the modeled disease outbreak. The work presented in this thesis focuses on tracking exposure risk to chickenpox in an elementary school setting. This setting is chosen due to the high level of detailed information realistically available to school administrators regarding individuals' schedules and movements. Using an agent-based approach, contacts between individuals are tracked and analyzed with respect to both individuals and locations. The results are then analyzed using a combination of tools from computer science and geographic information science.
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Coburn, Brian John. "Multi-Species Influenza Models with Recombination." Scholarly Repository, 2009. http://scholarlyrepository.miami.edu/oa_dissertations/363.
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Avian influenza strains have been proven to be highly virulent in human populations, killing approximately 70 percent of infected individuals. Although the virus is able to spread across species from birds-to-humans, some strains, such as H5N1, have not been observed to spread from human-to-human. Pigs are capable of infection by both avian and human strains and seem to be likely candidates as intermediate hosts for co-infection of the inter-species strains. A co-infected pig potentially acts as a mixing vessel and could produce a new strain as a result of a recombination process. Humans could be immunologically naive to these new strains, hence making them super-strains. We propose an interacting host system (IHS) for such a process that considers three host species that interact by sharing strains; that is, a primary and secondary host species can both infect an intermediate host. When an intermediate host is co-infected with the strains from both the other hosts, co-infected individuals may become carriers of a super-strain back into the primary host population. The model is formulated as a classical susceptible-infectious-susceptible (SIS) model, where the primary and intermediate host species have a super-infection and co-infection with recombination structure, respectively. The intermediate host is coupled to the other host species at compartments of given infectious subclasses of the primary and secondary hosts. We use the model to give a new perspective for the trade-off hypothesis for disease virulence, by analyzing the behavior of a highly virulent super-strain. We give permanence conditions for a number of the subsystems of the IHS in terms of basic reproductive numbers of independent strains. We also simulate several relevant scenarios showing complicated dynamics and connections with epidemic forecasting.
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Turner, Elizabeth L. "Marginal modelling of capture-recapture data." Thesis, McGill University, 2007. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=103302.
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The central theme of this dissertation is the development of a new approach to conceptualize and quantify dependence structures of capture-recapture data for closed populations, with specific emphasis on epidemiological applications. We introduce a measure of source dependence: the Coefficient of Incremental Dependence (CID). Properties of this and the related Coefficient of Source Dependence (CSD) of Vandal, Walker, and Pearson (2005) are presented, in particular their relationships to the conditional independence structures that can be modelled by hierarchical joint log-linear models (HJLLM). From these measures, we develop a new class of marginal log-linear models (MLLM), which we compare and contrast to HJLLMs.We demonstrate that MLLMs serve to extend the universe of dependence structures of capture-recapture data that can be modelled and easily interpreted. Furthermore, the CIDs and CSDs enable us to meaningfully interpret the parameters of joint log-linear models previously excluded from the analysis of capture-recapture data for reasons of non-interpretability of model parameters.
In order to explore the challenges and features of MLLMs, we show how to produce inference from them under both a maximum likelihood and a Bayesian paradigm. The proposed modelling approach performs well and provides new insight into the fundamental nature of epidemiological capture-recapture data.
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Coleman, Kimberley. "A new capture-recapture model selection criterion /." Thesis, McGill University, 2007. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=101841.
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Capture-recapture methods are used to estimate population size from overlapping, incomplete sources of information. With three or more sources, dependence between sources may be modelled using log-linear models. We propose a Coefficient of Incremental Dependence Criterion (CIDC) for selecting an estimate of population size among all possible estimates that result from hierarchical log-linear models. A penalty for the number of parameters in the model was selected via simulation for the three-source and four-source settings. The performance of the proposed criterion was compared to the Akaike Information Criterion (AIC) through simulation. The CIDC was found to modestly outperform the AIC for data generated from a population size of approximately 100, with AIC performing consistently better for larger population sizes. Modifications to the criterion such as incorporating the estimated population size and the type of source interaction present should be investigated, along with the mathematical properties of the CIDC.
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Vilches, Thomas Nogueira [UNESP]. "Modelos matemáticos e computacionais para descrever a transmissão de dois sorotipos de vírus de dengue." Universidade Estadual Paulista (UNESP), 2015. http://hdl.handle.net/11449/132052.
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000853296.pdf: 525856 bytes, checksum: 95f5500e6558ce1f31d89b02936acd5e (MD5)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
Apresenta-se um modelo de equações diferenciais ordinárias que descreve a transmissão de dengue em uma população humana e de mosquitos quando há circulação de dois sorotipos de vírus. Resultados analíticos e numéricos para os pontos de equilíbrio deste modelo, e o estudo da estabilidade dos mesmos são obtidos. Faz-se uma aproximação de estado quase-estacionário para a população de mosquito, com o objetivo de estudar e comparar a dinâmica da transmissão da dengue em redes de diferentes topologias. O modelo de transmissão através de redes complexas considera diferentes graus de conectividade entre os indivíduos da população e por isso representa melhor as interações sociais. Observa-se que a dinâmica da transmissão da dengue depende fortemente da topologia da rede e do número médio de conexões, portanto medidas de controle da doença devem ter um impacto diferente dada a diversidade das conexões entre os indivíduos de uma população
We present a model of ordinary differential equations to describe the dengue transmission in a human and a mosquito populations when there are two serotypes of circulating virus. Analytic and numeric results to the equilibruim points of this model, and the study of the stability of this points were obtained. We assume the quasi-steady state approach to the mosquito population, in order to study and compare the dynamics of transmission of two serotypes of dengue virus in networks with different topologies. We consider the transmission model through complex networks with different degrees of conectivity among the individuals and, thus, it provides a better representation of the social interations. We observe that the transmission dynamics of dengue depends strongly on the network topology and the mean number of conections, thus the control measures must have a different impact given the diversity of conections among the individuals on the population
FAPESP: 2013/01552-7
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Chitnis, Nakul Rashmin. "Using Mathematical Models in Controlling the Spread of Malaria." Diss., Tucson, Arizona : University of Arizona, 2005. http://etd.library.arizona.edu/etd/GetFileServlet?file=file:///data1/pdf/etd/azu%5Fetd%5F1407%5F1%5Fm.pdf&type=application/pdf.
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Kwok, Kin-on, and 郭健安. "Models of directly transmitted respiratory pathogens in hospitals and households." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2008. http://hub.hku.hk/bib/B40687557.
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Venkatachalam, Sangeeta. "Modeling Infectious Disease Spread Using Global Stochastic Field Simulation." Thesis, University of North Texas, 2006. https://digital.library.unt.edu/ark:/67531/metadc5335/.
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Susceptibles-infectives-removals (SIR) and its derivatives are the classic mathematical models for the study of infectious diseases in epidemiology. In order to model and simulate epidemics of an infectious disease, a global stochastic field simulation paradigm (GSFS) is proposed, which incorporates geographic and demographic based interactions. The interaction measure between regions is a function of population density and geographical distance, and has been extended to include demographic and migratory constraints. The progression of diseases using GSFS is analyzed, and similar behavior to the SIR model is exhibited by GSFS, using the geographic information systems (GIS) gravity model for interactions. The limitations of the SIR and similar models of homogeneous population with uniform mixing are addressed by the GSFS model. The GSFS model is oriented to heterogeneous population, and can incorporate interactions based on geography, demography, environment and migration patterns. The progression of diseases can be modeled at higher levels of fidelity using the GSFS model, and facilitates optimal deployment of public health resources for prevention, control and surveillance of infectious diseases.
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Vilches, Thomas Nogueira. "Modelos matemáticos e computacionais para descrever a transmissão de dois sorotipos de vírus de dengue /." Botucatu, 2015. http://hdl.handle.net/11449/132052.
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Orientador: Cláudia Pio FerreiraBanca: Fernanado Luiz Pio dos Santos
Banca: Suani Tavares Rubim de Pinho
Resumo: Apresenta-se um modelo de equações diferenciais ordinárias que descreve a transmissão de dengue em uma população humana e de mosquitos quando há circulação de dois sorotipos de vírus. Resultados analíticos e numéricos para os pontos de equilíbrio deste modelo, e o estudo da estabilidade dos mesmos são obtidos. Faz-se uma aproximação de estado quase-estacionário para a população de mosquito, com o objetivo de estudar e comparar a dinâmica da transmissão da dengue em redes de diferentes topologias. O modelo de transmissão através de redes complexas considera diferentes graus de conectividade entre os indivíduos da população e por isso representa melhor as interações sociais. Observa-se que a dinâmica da transmissão da dengue depende fortemente da topologia da rede e do número médio de conexões, portanto medidas de controle da doença devem ter um impacto diferente dada a diversidade das conexões entre os indivíduos de uma população
Abstract: We present a model of ordinary differential equations to describe the dengue transmission in a human and a mosquito populations when there are two serotypes of circulating virus. Analytic and numeric results to the equilibruim points of this model, and the study of the stability of this points were obtained. We assume the quasi-steady state approach to the mosquito population, in order to study and compare the dynamics of transmission of two serotypes of dengue virus in networks with different topologies. We consider the transmission model through complex networks with different degrees of conectivity among the individuals and, thus, it provides a better representation of the social interations. We observe that the transmission dynamics of dengue depends strongly on the network topology and the mean number of conections, thus the control measures must have a different impact given the diversity of conections among the individuals on the population
Mestre
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Pereira, da Silva Hélio Doyle. "Aplicación de modelos bayesianos para estimar la prevalencia de enfermedad y la sensibilidad y especificidad de tests de diagnóstico clínico sin gold standard." Doctoral thesis, Universitat de Barcelona, 2016. http://hdl.handle.net/10803/523505.
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Dos objetivos claves de la investigación diagnóstica son estimar con exactitud y precisión la prevalencia de la enfermedad y la sensibilidad y especificidad de tests diagnósticos. Se han desarrollado modelos de clases latentes que tienen en cuenta la correlación entre las medidas de los individuos determinadas con diferentes tests con el fin de diagnosticar enfermedades para las cuales no están disponibles tests gold standard. En algunos estudios clínicos, se hacen varias medidas del mismo individuo con el mismo test en las mismas condiciones y, por tanto, las mediciones replicadas para cada individuo no son independientes. En esta tesis se propone una extensión Bayesiana del modelo de clases latentes de efectos aleatorios de Gauss para ajustar a los datos de tests con resultados binarios y con medidas replicadas por individuo. Se describe una aplicación que utiliza los datos recogidos de personas infectadas por parásitos intestinales Hookworm llevada a cabo en el municipio de Presidente Figueiredo, Estado de Amazonas en Brasil. Además, a través de un estudio de simulación se comparó el desempeño del modelo propuesto con los modelos actuales (el modelo de efectos aleatorios individuo y modelos de dependencia e independencia condicional). Como era de esperar, el modelo propuesto presenta una mayor exactitud y precisión en las estimaciones de prevalencia, sensibilidad y especificidad.
Para un control adecuado de las enfermedades la Organización Mundial de la Salud ha propuesto el diagnóstico y tratamiento de la infección tuberculosa latente (LTBI) en grupos de riesgo de desarrollar la enfermedad, como los niños. No existe un test gold standard para el diagnóstico de la infección latente. Los modelos estadísticos basados en la estimación de clases latentes permiten la evaluación de la prevalencia de la infección y la validez de los tests utilizados en ausencia de un gold standard. Se realizó un estudio transversal con niños de hasta 6 años de edad que habían sido vacunados con la BCG en Manaus, Amazonas-Brasil. El objetivo de dicho estudio fue estimar la prevalencia de la infección latente en los niños pequeños en contacto con un caso indice de tuberculosis en el hogar (TB-HCC) y determinar la validez y la seguridad del test cutáneo de tuberculina (TST) y QuantiFERON-TB Gold-in-tube (QFT), utilizando modelos de clases latentes. Para las estimaciones, en una primera fase se consideró la correlación entre los dos tests, y en la segunda fase se consideró la prevalencia en función de la intensidad y del tiempo de exposición. El cincuenta por ciento de los niños con TB-HCC tenía LTBI, con la prevalencia en función del tiempo y la intensidad de la exposición al caso índice. La sensibilidad y la especificidad de TST fueron del 73 % [intervalo de confianza del 95 % (IC): 53-91] y el 97 % (IC del 95 %: 89-100), respectivamente, frente al 53 % (IC del 95 %: 41-66) y el 81 % (IC del 95 %: 71-90) para QFT. El valor predictivo positivo de TST en niños con TB-HCC fue del 91 % (IC del 95 %: 61-99), y para QFT fue del 74 % (IC del 95 %: 47-95). Este es uno de los primeros estudios que usa modelos de clases latentes para estimar la prevalencia de la infección por M. tuberculosis en niños y los parámetros de sus principales tests diagnósticos. Los resultados sugieren que los niños en contacto con un caso índice tienen un alto riesgo de infección. La validez y los valores predictivos no mostraron diferencias significativas según el test aplicado. El uso combinado de los dos tests en nuestro estudio mostró una sutil mejoría en el diagnóstico de la LTBI.Two key aims of diagnostic research are to accurately and precisely estimate disease prevalence and test sensitivity and specificity. Latent class models have been proposed that consider the correlation between subject measures determined by different tests in order to diagnose diseases for which gold standard tests are not available. In some clinical studies, several measures of the same subject are made with the same test under the same conditions (replicated measurements) and thus, replicated measurements for each subject are not independent. In the present study, we propose an extension of the Bayesian latent class Gaussian random effects model to fit the data with binary outcomes for tests with replicated subject measures. We describe an application using data collected on hookworm infection carried out in the municipality of Presidente Figueiredo, Amazonas State, Brazil. In addition, the performance of the proposed model was compared with that of current models (the subject random effects model and the conditional (in)dependent model) through a simulation study. As expected, the proposed model presented better accuracy and precision in the estimations of prevalence, sensitivity and specificity. For adequate disease control the World Health Organization has proposed the diagnosis and treatment of latent tuberculous infection (LTBI) in groups of risk of developing the disease such as children. There is no gold standard (GS) test for the diagnosis of LTBI. Statistical models based on the estimation of latent class allow evaluation of the prevalence of infection and the accuracy of the tests used in the absence of a GS. We conducted a cross-sectional study with children up to 6 years of age who had been vaccinated with the BCG in Manaus, Amazonas- Brazil. The objective of this study was to estimate the prevalence of LTBI in young children in contact with a household case of tuberculosis (TB-HCC) and determine the accuracy and precision of the Tuberculin Skin Test (TST) and QuantiFERON-TB Gold in-tube (QFT) using the latent class model. Fifty percent of the children with TB-HCC had LTBI, with the pre- valence depending on the intensity and length of exposure to the index case. The sensitivity and specificity of TST were 73 % [95 % confidence interval (CI): 53-91] and 97 % (95 % CI: 89-100), respectively, versus 53 % (95 % CI: 41-66) and 81 % (95 % CI: 71-90) for QFT. The positive predictive value of TST in children with TB-HCC was 91 % (95 % CI: 61-99), and for QFT was 74 % (95 % CI: 47-95). This is one of the first studies to estimate the prevalence of M. tuberculosis infection in children and the parameters of its main diagnostic tests by latent class model. The results suggest that children in contact with an index case have a high risk of infection. The accuracy and the predictive values did not show significant differences according to the test applied. Combined use of the two tests in our study showed scarce improvement in the diagnosis of LTBI.
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Parra, Rojas César. "Intrinsic fluctuations in discrete and continuous time models." Thesis, University of Manchester, 2017. https://www.research.manchester.ac.uk/portal/en/theses/intrinsic-fluctuations-in-discrete-and-continuous-time-models(d7006a2b-1496-44f2-8423-1f2fa72be1a5).html.
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This thesis explores the stochastic features of models of ecological systems in discrete and in continuous time. Our interest lies in models formulated at the microscale, from which a mesoscopic description can be derived. The stochasticity present in the models, constructed in this way, is intrinsic to the systems under consideration and stems from their finite size. We start by exploring a susceptible-infectious-recovered model for epidemic spread on a network. We are interested in the case where the connectivity, or degree, of the individuals is characterised by a very broad, or heterogeneous, distribution, and in the effects of stochasticity on the dynamics, which may depart wildly from that of a homogeneous population. The model at the mesoscale corresponds to a system of stochastic differential equations with a very large number of degrees of freedom which can be reduced to a two-dimensional model in its deterministic limit. We show how this reduction can be carried over to the stochastic case by exploiting a time-scale separation in the deterministic system and carrying out a fast-variable elimination. We use simulations to show that the temporal behaviour of the epidemic obtained from the reduced stochastic model yields reasonably good agreement with the microscopic model under the condition that the maximum allowed degree that individuals can have is not too close to the population size. This is illustrated using time series, phase diagrams and the distribution of epidemic sizes. The general mesoscopic theory used in continuous-time models has only very recently been developed for discrete-time systems in one variable. Here, we explore this one-dimensional theory and find that, in contrast to the continuous-time case, large jumps can occur between successive iterates of the process, and this translates at the mesoscale into the need for specifying `boundary' conditions everywhere outside of the system. We discuss these and how to implement them in the stochastic difference equation in order to obtain results which are consistent with the microscopic model. We then extend the theoretical framework to make it applicable to systems containing an arbitrary number of degrees of freedom. In addition, we extend a number of analytical results from the one-dimensional stochastic difference equation to arbitrary dimension, for the distribution of fluctuations around fixed points, cycles and quasi-periodic attractors of the corresponding deterministic map. We also derive new expressions, describing the autocorrelation functions of the fluctuations, as well as their power spectrum. From the latter, we characterise the appearance of noise-induced oscillations in systems of dimension greater than one, which have been previously observed in continuous-time systems and are known as quasi-cycles. Finally, we explore the ability of intrinsic noise to induce chaotic behaviour in the system for parameter values for which the deterministic map presents a non-chaotic attractor; we find that this is possible for periodic, but not for quasi-periodic, states.
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Reyes, Silveyra Jorge A. "Modeling Epidemics on Structured Populations: Effects of Socio-demographic Characteristics and Immune Response Quality." Thesis, University of North Texas, 2014. https://digital.library.unt.edu/ark:/67531/metadc700011/.
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Epidemiologists engage in the study of the distribution and determinants of health-related states or events in human populations. Eventually, they will apply that study to prevent and control problems and contingencies associated with the health of the population. Due to the spread of new pathogens and the emergence of new bio-terrorism threats, it has become imperative to develop new and expand existing techniques to equip public health providers with robust tools to predict and control health-related crises. In this dissertation, I explore the effects caused in the disease dynamics by the differences in individuals’ physiology and social/behavioral characteristics. Multiple computational and mathematical models were developed to quantify the effect of those factors on spatial and temporal variations of the disease epidemics. I developed statistical methods to measure the effects caused in the outbreak dynamics by the incorporation of heterogeneous demographics and social interactions to the individuals of the population. Specifically, I studied the relationship between demographics and the physiological characteristics of an individual when preparing for an infectious disease epidemic.
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Mitchell, Kate Margaret. "Analysis of the dynamics of protective immune responses in human populations with endemic schistosome infection." Thesis, University of Edinburgh, 2011. http://hdl.handle.net/1842/5273.
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Urinary schistosomiasis, which is caused by the blood fluke Schistosoma haematobium, is a tropical disease infecting over 100 million people in sub-Saharan Africa. Infection typically involves repeated re-infection with long-lived parasites, and field studies have demonstrated that protective immunity takes many years to develop in humans. In communities with endemic schistosomiasis, distinctive patterns of infection and schistosome-specific antibody responses are seen, including a peaked age-infection curve, a highly aggregated distribution of infection intensities among individuals, and an age-related switch in the subclasses of antibody produced. The antibody switch, which occurs naturally in older children, is also seen in younger children following treatment with the antihelminthic drug praziquantel, which kills adult worms. This study aimed to identify the important mechanisms underlying the slow development of protective immunity, using a mathematical modelling approach. Deterministic population-level and stochastic individual-based models were developed that describe how levels of infection and antibody change with age for individuals living in endemic communities. These models were used to explore different hypotheses for the slow development of protective immunity: (1) that schistosome parasites actively suppress protective immune responses; (2) that dying worms provide the main antigenic stimulus for protective immunity and (3) that a threshold level of antigen must be experienced before a protective immune response is initiated. Models were assessed for their ability to simultaneously reproduce different robust patterns of infection and antibody responses identified in cross-sectional and post-treatment field data from Zimbabwe. It was found that significant immunosuppression by schistosomes was not consistent with population-level patterns of infection intensity, including the peaked age-infection curve. In order to explain both age-related and post-treatment changes in infection intensity and antibody responses, including the antibody switch, protective antibody responses had to be stimulated by antigens from dying worms. Additionally, it was shown that these protective responses reduced worm fecundity rather than reducing rates of re-infection. An antigen threshold was found to be consistent with observed field patterns, but was not necessary to explain them. From a large number of possible models that were considered, a single model structure and a subset of parameter combinations were identified that were consistent with field data. This model was used to predict the longer-term impact of mass-treatment programmes upon the development of protective immunity, and the consequent effects on infection levels.
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Abbas, Kaja Moinudeen. "Bayesian Probabilistic Reasoning Applied to Mathematical Epidemiology for Predictive Spatiotemporal Analysis of Infectious Diseases." Thesis, University of North Texas, 2006. https://digital.library.unt.edu/ark:/67531/metadc5302/.
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Abstract Probabilistic reasoning under uncertainty suits well to analysis of disease dynamics. The stochastic nature of disease progression is modeled by applying the principles of Bayesian learning. Bayesian learning predicts the disease progression, including prevalence and incidence, for a geographic region and demographic composition. Public health resources, prioritized by the order of risk levels of the population, will efficiently minimize the disease spread and curtail the epidemic at the earliest. A Bayesian network representing the outbreak of influenza and pneumonia in a geographic region is ported to a newer region with different demographic composition. Upon analysis for the newer region, the corresponding prevalence of influenza and pneumonia among the different demographic subgroups is inferred for the newer region. Bayesian reasoning coupled with disease timeline is used to reverse engineer an influenza outbreak for a given geographic and demographic setting. The temporal flow of the epidemic among the different sections of the population is analyzed to identify the corresponding risk levels. In comparison to spread vaccination, prioritizing the limited vaccination resources to the higher risk groups results in relatively lower influenza prevalence. HIV incidence in Texas from 1989-2002 is analyzed using demographic based epidemic curves. Dynamic Bayesian networks are integrated with probability distributions of HIV surveillance data coupled with the census population data to estimate the proportion of HIV incidence among the different demographic subgroups. Demographic based risk analysis lends to observation of varied spectrum of HIV risk among the different demographic subgroups. A methodology using hidden Markov models is introduced that enables to investigate the impact of social behavioral interactions in the incidence and prevalence of infectious diseases. The methodology is presented in the context of simulated disease outbreak data for influenza. Probabilistic reasoning analysis enhances the understanding of disease progression in order to identify the critical points of surveillance, control and prevention. Public health resources, prioritized by the order of risk levels of the population, will efficiently minimize the disease spread and curtail the epidemic at the earliest.
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Meesumrarn, Thiraphat. "Simulation of Dengue Outbreak in Thailand." Thesis, University of North Texas, 2018. https://digital.library.unt.edu/ark:/67531/metadc1248484/.
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The dengue virus has become widespread worldwide in recent decades. It has no specific treatment and affects more than 40% of the entire population in the world. In Thailand, dengue has been a health concern for more than half a century. The highest number of cases in one year was 174,285 in 1987, leading to 1,007 deaths. In the present day, dengue is distributed throughout the entire country. Therefore, dengue has become a major challenge for public health in terms of both prevention and control of outbreaks. Different methodologies and ways of dealing with dengue outbreaks have been put forward by researchers. Computational models and simulations play an important role, as they have the ability to help researchers and officers in public health gain a greater understanding of the virus's epidemic activities.
In this context, this dissertation presents a new framework, Modified Agent-Based Modeling (mABM), a hybrid platform between a mathematical model and a computational model, to simulate a dengue outbreak in human and mosquito populations. This framework improves on the realism of former models by utilizing the reported data from several Thai government organizations, such as the Thai Ministry of Public Health (MoPH), the National Statistical Office, and others. Additionally, its implementation takes into account the geography of Thailand, as well as synthetic mosquito and synthetic human populations. mABM can be used to represent human behavior in a large population across variant distances by specifying demographic factors and assigning mobility patterns for weekdays, weekends, and holidays for the synthetic human population. The mosquito dynamic population model (MDP), which is a component of the mABM framework, is used for representing the synthetic mosquito population dynamic and their ecology by integrating the regional model to capture the effect of dengue outbreak. The two synthetic populations can be linked to each other for the purpose of presenting their interactions, and the Local Stochastic Contact Model for Dengue (LSCM-DEN) is utilized. For validation, the number of cases from the experiment is compared to reported cases from the Thailand Vector Borne Disease Bureau for the selected years.
This framework facilitates model configuration for sensitivity analysis by changing parameters, such as travel routes and seasonal temperatures. The effects of these parameters were studied and analyzed for an improved understanding of dengue outbreak dynamics.
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Gao, Zhanhai School of Mathematics UNSW. "Modelling Human Immunodeficiency Virus and Hepatitis C Virus Epidemics in Australia." Awarded by:University of New South Wales. School of Mathematics, 2001. http://handle.unsw.edu.au/1959.4/18187.
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This thesis is concerned with the mathematical modelling for human immunodeficiency virus (HIV) and hepatitis C virus (HCV) epidemics in Australia. There are two parts to this thesis. Part I is aimed at modelling the transmission of HIV and HCV via needle sharing among injecting drug users (IDUs). The dynamical model of an epidemic through needle sharing among IDUs is derived. This model reveals the correlation between needle sharing and the epidemic prevalence among IDUs. The simulations of HIV and HCV prevalence and incidence among IDUs in Australia are made with this model. The comparison of simulated results with literature estimates shows that the modelled results are consistent with the literature estimates. The effects of needle sharing and cleaning on HIV and HCV prevalence and incidence among IDUs in Australia are evaluated. Part II is devoted to modelling the spread of HIV in the general community in Australia. A mathematical model is formulated to assess the epidemiological consequences of injecting drug use and sexual transmission in Australia. The effects of highly active antiretroviral therapies (HAART) on the HIV epidemic are included. The modelled results are in broad agreement with the literature estimates and observed data. The long-term effects of HAART are also discussed.
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Macufa, Marta Maria Mucacho. "Modelos epidemiológicos alternativos da malária." [s.n.], 2011. http://repositorio.unicamp.br/jspui/handle/REPOSIP/306459.
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Orientador: Rodney Carlos BassaneziDissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Matemática, Estatística e Computação Científica
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Resumo: Neste trabalho apresentamos um estudo de modelos matemáticos epidemiológicos determinísticos da malária. Em seguida propomos um modelo alternativo da malária, supostamente menos complexo com o intuito de utilizar modelos associados que contemplam a subjetividade em seus elementos. Para o modelo alternativo determinístico fizemos uma análise qualitativa e simulações com dados reais dos casos confirmados de malária no Brasil, de modo particular na região Amazônica onde se concentra cerca de 90% dos casos. Dado que os modelos clássicos têm como característica a precisão dos dados e, muitas vezes, as soluções clássicas podem não traduzir a realidade devido às imprecisões dos dados. Fizemos uma abordagem da teoria dos conjuntos fuzzy, apresentando algumas de suas características: valor esperado, base de regras para sistemas p-fuzzy e o princípio de extensão de Zadeh, com a finalidade de incluir subjetividade no modelo alternativo proposto, o qual traduziria possivelmente uma situação mais próxima a realidade
Abstract: In this work we present a study of mathematic deterministic epidemiological models of malaria. We then propose an alternative model of malaria, supposedly less complex, with the intention of using associate models that contemplate the subjectivity in their elements. For the alternative deterministic model we made a quantitative analysis and simulations with real data of confirmed cases of malaria in Brazil, more specifically in the Amazon region, where about 90 % of cases occur. The characteristic of classic models is the precision of the data and, many times, classic solutions may not translate the reality due to data imprecision. For that reason, we made an approach of the theory of logic fuzzy, presenting some of its characteristics: expected value, base of rules for p-fuzzy system and principle of extension of Zadeh, with the purpose of including subjectivity in the proposed alternative model, which would possibly reflect a situation closer to reality
Mestrado
Biomatematica
Mestre em Matemática Aplicada
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Wang, Jinjun. "Sensitivity and uncertainty analyses of contaminant fate and transport in a field-scale subsurface system." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/22562.
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Thesis (Ph. D.)--Civil and Environmental Engineering, Georgia Institute of Technology, 2008.Committee Chair: Aral, Mustafa; Committee Member: Guan, Jiabao; Committee Member: Kim, Seong Hee; Committee Member: Luo, Jian; Committee Member: Uzer, Turgay.
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Thein, Hla-Hla Public Health & Community Medicine Faculty of Medicine UNSW. "Measuring the health burden of hepatitis C at an individual and population level in Australia." Awarded by:University of New South Wales. School of Public Health and Community Medicine, 2006. http://handle.unsw.edu.au/1959.4/24967.
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This thesis examines the effect of hepatitis C virus infection (HCV) on health-related quality of life (HRQOL) to define burden of disease at individual and population levels. A systematic review of HCV HRQOL studies was undertaken with translation of Short Form-36 (SF-36) Health Survey data into community-weighted health state utilities using three different methods. Derived estimates of health utilities were 0.87 for HCV treatment-induced sustained virological response (SVR); 0.81 for pre-cirrhosis; 0.76 for compensated cirrhosis; 0.69 for decompensated cirrhosis; 0.67 for hepatocellular carcinoma (HCC); and 0.77 for liver transplant. The HCV health state utilities varied considerably from expert estimates, with relatively lower estimates for early liver disease and higher estimates for advanced liver disease, but were comparable to direct patient-elicited utilities. A study utilising data from population-based health surveys incorporating HCV screening among prisoners at Australian correctional centres in 1996 and 2001 showed no measurable effect of HCV on HRQOL, including that attributable to HCV viraemia. Compared to uninfected Australian norms, prisoners had lower HRQOL irrespective of HCV status. Several non-HCV factors such as age, co-morbidity, severity of depressive symptoms, and medical care utilization influenced HRQOL. A prospective study of health outcomes among HCV monoinfected and HIV/HCV coinfected individuals conducted at Sydney tertiary level hepatitis clinics between 2003 and 2005 found similar cognitive function, mood, and HRQOL patterns in these two HCV groups in the context of pegylated interferon (PEG-IFN) alfa-2a and ribavirin therapy. The HCV groups had similar levels of pre-treatment HRQOL impairment, further on-treatment deterioration, and posttreatment improvements. SVR was associated with significant HRQOL improvements, but mental HRQOL improvement was also seen in individuals not achieving an SVR. The impact of HCV treatment uptake on HCV-related burden of disease at a population level in Australia was examined using a mathematical model. The model estimated that in 2004, there were ~181,500 cases of chronic HCV infection, 7,020 with HCV-related cirrhosis, and annual incidence of 238 cases of HCV-related liver failure and 70 cases of HCV-related HCC. Compared to no treatment, current treatment levels (~1% of HCV-infected individuals per annum) would reduce projected HCV-related cirrhosis and advanced liver disease numbers by ~30% at 2020 and a gain of ~122,200 Quality-Adjusted Life Years (QALYs). Even with a five-fold increase from current treatment levels, advanced liver disease numbers will continue to increase through 2020 but will be reduced by ~55% and a gain of ~483,200 QALYs.
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Ni, Lihong, and 倪莉紅. "Modeling vaccination for pandemic influenza: implication of the race between pandemic dynamics and vaccineproduction." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2007. http://hub.hku.hk/bib/B40687430.
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Sabino, Marcio Rodrigues. "Efeitos da vacinação e do tratamento na dinâmica da transmissão da tuberculose." [s.n.], 2011. http://repositorio.unicamp.br/jspui/handle/REPOSIP/307215.
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Orientadores: Hyun Mo Yang, Silvia Martorano RaimundoDissertação (mestrado) - Universidade Estadual de Campinas, Insituto de Matemática, Estatística e Computação Científica
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Resumo: O interesse em modelar a dinâmica de transmissão da Tuberculose (TB) é principalmente pelo fato de que a TB representa um grande problema de Saúde Pública em todo o mundo. Segundo a Organização Mundial de Saúde, a TB é a principal causa de mortalidade por doenças infecciosas, sendo responsável por mais de 2 milhões de óbitos a cada ano (WHO, 2007). Outro motivo, muito importante desse estudo é o fato da descoberta da "vacina gênica (ou vacina de DNA)" pelo grupo de pesquisas do pesquisador Célio Lopes Silva, coordenador do Laboratório de Vacinas Gênicas da Faculdade de Medicina de Ribeirão Preto da USP. A vacina, ainda em fase de experimento e padronização pode se tornar a maior promessa de combate a doenças infecciosas para as quais até hoje não existe prevenção segura, como é o caso da TB. Neste trabalho apresentam-se estudos epidemiológicos da TB, as principais características da ação da vacina na epidemiologia da doença e, posteriormente, a formulação de um modelo matemático para descrever a dinâmica da transmissão da TB usando a vacina gênica como estratégia de controle da doença. A suposição básica do modelo é que a vacinação é adotada não somente como proteção para os indivíduos suscetíveis, mas também como tratamento para os indivíduos infectados e infecciosos. Apresenta-se uma análise do modelo geral determinando-se os pontos de equilíbrio do sistema e as condições de estabilidades destes pontos: analiticamente para o equilíbrio trivial, e numericamente, para o equilíbrio não trivial. Através de uma simplificação do modelo geral, foi também possível mostrar analiticamente a estabilidade global dos pontos de equilíbrio trivial e não trivial através da função de Lyapunov. Foram estimados alguns parâmetros do modelo, utilizando-se os dados que descrevem o cenário da TB no Brasil entre 1980 e 2007. Por fim, através deste ajuste, determinou-se os valores críticos de vacinação para o controle da doença
Abstract: The interest in modeling the transmission dynamics of the Tuberculosis(TB) is mainly due to the fact that TB is a major public health problem worldwide. According to World Health Organisation, TB is the leading cause of mortality from infectious diseases, accounting for more than 2 million deaths each year (WHO, 2007). Another reason, very important to this study is the discovery of "genetic vaccines" (or "DNA vaccine") by the research group of the researcher Celio Lopes Silva, coordinator of the Laboratory of genetic vaccines of the Faculty of Medicine of Ribeirao Preto, USP. The vaccine, still under experimentation and standardization, is a great promise for combating infectious diseases for which today there is no safe prevention, such as TB. This work presents epidemiological studies of TB, the main characteristics of the action of the vaccine on the epidemiology of the disease and then, a mathematical model formulation to describe the dynamics of TB transmission by using the genetic vaccine as a strategy for disease control. The basic assumption of the model is that vaccination is adopted not only as protection for susceptible individuals, but also as a treatment for infected and infectious individuals. An analysis of the general model is presented, by determining the equilibrium points of the system and the conditions of stability of these points: analytically for the trivial equilibrium point, and numerically for the endemic equilibrium point. By simplifying the general model, it was also possible to show analytically the global stability of the trivial and nontrivial equilibrium points with Lyapunov functions. Were estimated parameters of the model, using the data describing the scenario of TB in Brazil between 1980 and 2007. Finally, with these settings, critical values of vaccination for disease control were determined
Mestrado
Matematica Aplicada
Mestre em Matemática Aplicada
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Campanella, Gianluca. "Estimation of infection rate in epidemic models with multiple populations." Master's thesis, Faculdade de Ciências e Tecnologia, 2011. http://hdl.handle.net/10362/6118.
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Dissertação para obtenção do Grau de Mestre em Matemática e Aplicações Especialização em Actuariado, Estatística e Investigação OperacionalThe e ect of infectious diseases on human development throughout history is well established, and investigation on the causes of infectious epidemics { and plagues in particular { dates back at least to Hippocrates,the father of Western medicine. The mechanisms by which diseases spread, however, could not be fully understood until the late nineteenth century, with the discovery of microorganisms and the understanding of their role as infectious agents. Eventually, at the turn of the twentieth century, the foundations of the mathematical epidemiology of infectious diseases were laid by the seminal work of En'ko, Ross, and Kermack and McKendrick. More recently, the application of graph theory to epidemiology has given rise to models that consider the spread of diseases not only at the level of individuals belonging to a single population (population models), but also in systems with multiple populations linked by a transportation network(meta-population models). The aim of meta-populations models is to understand how movement of individuals between populations generates the geographical spread of diseases, a challenging goal whose importance is all the greater now that long-range displacements are facilitated by inexpensive air travel possibilities. A problem of particular interest in all epidemic models is the estimation of parameters from sparse and inaccurate real-world data, especially the socalled infection rate, whose estimation cannot be carried out directly through clinical observation. Focusing on meta-population models, in this thesis we introduce a new estimation method for this crucial parameter that is able to accurately infer it from the arrival times of the rst infective individual in each population. Moreover, we test our method and its accuracy by means of computer simulations.
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Njagarah, Hatson John Boscoh. "Modelling water-borne infections : the impact of hygiene, metapopulation movements and the biological control of cholera." Thesis, Stellenbosch : Stellenbosch University, 2014. http://hdl.handle.net/10019.1/95972.
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Thesis (PhD)--Stellenbosch University, 2014.ENGLISH ABSTRACT: Water-borne infections have been a menace in many countries around the globe, claiming millions of lives. Cholera in particular has spread to all continents and now on its seventh epidemic. Although control measures have been continually developed through sanitation, vaccination and rehydration, the infection still devastates populations whenever there is an outbreak. In this research work, mathematical models for cholera transmission dynamics with focus on the impact of sanitation and hygiene, metapopulation spread, optimal control and biological control using a bacteriophage specific for pathogenic Vibrio cholerae are constructed and analysed. Vital analyses for the models are precisely given as well as numerical results depicting long term behaviour and the evolution of populations over time. The results of our analysis indicate that; improved sanitation and hand-hygiene are vital in reducing cholera infections; the spread of disease across metapopulations characterised by exchange of individuals and no cross community infection is associated with synchronous fluctuation of populations in both adjacent communities; during control of cholera, the control measures/efforts ought to be optimal especially at the beginning of the epidemic where the outbreak is often explosive in nature; and biological control if well implemented would avert many potential infections by lowering the concentration of pathogenic vibrios in the aquatic environment to values lower than the infectious dose.
AFRIKAANSE OPSOMMING: Water-infeksies is ’n bedreiging in baie lande regoor die wêreld en eis miljoene lewens. Cholera in die besonder, het op sy sewende epidemie na alle kontinente versprei. Hoewel beheermaatreëls voortdurend ontwikkel word deur middel van higiëne, inentings en rehidrasie, vernietig die infeksie steeds bevolkings wanneer daar ’n uitbraak voorkom. In hierdie navorsingswerk, word wiskundige modelle vir cholera-oordrag dinamika met die fokus op die impak van higiëne, metabevolking verspreiding, optimale beheer en biologiese beheer met behulp van ’n bakteriofaag spesifiek vir patogene Vibrio cholerae gebou en ontleed. Noodsaaklike ontledings vir die modelle is gegee sowel as numeriese resultate wat die langtermyn gedrag uitbeeld en die ontwikkeling van die bevolking oor tyd. Die resultate van ons ontleding dui daarop dat; verbeterde higiëne is noodsaaklik in die vermindering van cholera infeksies; die verspreiding van die siekte oor metapopulaties gekenmerk deur die uitruil van individue en geen kruis gemeenskap infeksie wat verband houmet sinchrone skommeling van bevolkings in beide aangrensende gemeenskappe; tydens die beheer van cholera,behoort die beheermaatreëls/pogings optimaal te wees veral aan die begin van die epidemie waar die uitbreking dikwels plofbaar in die natuur is; en biologiese beheer, indien dit goed geïmplementeer word, kan baie potensiële infeksies voorkom deur ’n vermindering in die konsentrasie van patogene vibrio in die water tot waardes laer as die aansteeklike dosis.
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Denholm, Scott J. "Mathematical models for investigating the long-term impact of Gyrodactylus salaris infections on Atlantic salmon populations." Thesis, University of Stirling, 2013. http://hdl.handle.net/1893/17021.
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Gyrodactylus salaris Malmberg, 1957, is a notifiable freshwater ecto-parasite that infects both wild and farmed populations of Atlantic salmon (Salmo salar, L.). It has caused catastrophic damage to wild salmon stocks in Norway since its accidental introduction in 1975, reducing salmon density in some rivers by 98% over a period of five years. It is estimated that G. salaris has cost the Norwegian salmon industry more than 500 million EUR. Currently the UK has G. salaris free status under EU law, however, it is believed that if G. salaris emerged in the UK the impact would be similar to that witnessed in Norway. The aim of this thesis is to develop mathematical models that describe the salmon-G. salaris system in order to gain a greater understanding of the possible long-term impact the parasite may have on wild populations of Atlantic salmon in G. salaris-free territories such as the UK. Mathematical models, including deterministic, Leslie matrix and individual based models, were used to investigate the impact of G. salaris on Atlantic salmon at the individual and population level. It is known that the Atlantic strain of Atlantic salmon, examples of which occur naturally in Norway and the UK, does not have any resistance to G. salaris infections and the parasite population is able to quickly grow to epidemic levels. In contrast, the Baltic strain of Atlantic salmon, examples of which occur naturally in Sweden and Russia, exhibits some form of resistance and the parasite is unable to persist. Thus, baseline models were extended to include immunity to infection, a trade-off on salmon reproductive rate, and finally, to consider interactions between populations of G. salaris and multiple strains of salmon exhibiting varying levels of immunity from fully susceptible to resistant. The models proposed predict that in the absence of host resistance or an immune response infections by G. salaris will result in an epidemic followed by the extinction of the salmon host population. Models also predict that if salmon are able to increase their resistance to G. salaris infections through mutations, salmon population recovery after the epidemic is indeed possible within 10-15 years post introduction with low level parasite coexistence. Finally, models also highlight areas where additional information is needed in order to improve predictions and enable the estimation of important parameter values. Model predictions will ultimately be used to assist in future contingency planning against G. salaris outbreaks in the UK and possibly as a basis for future models describing other fish/ecto-parasite systems.
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Ximenes, Raphael. "Risco de dengue para turistas no Brasil na Copa do Mundo da FIFA 2014 e nos Jogos Olímpicos Rio 2016, utilizando modelagem matemática." Universidade de São Paulo, 2017. http://www.teses.usp.br/teses/disponiveis/5/5144/tde-31072017-114959/.
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A Organização Mundial da Saúde estima que 3.9 bilhões de pessoas, em 128 países, vivem atualmente em áreas de risco para contrair dengue em todo o mundo, e que anualmente, 390 (284-528) milhões de infecções ocorrem, sendo apenas 96 (67-136) milhões de casos com manifestações clínicas. Estima-se que 500.000 casos de dengue hemorrágica aconteçam por ano, muitos deles em crianças, causando milhares de mortes (Bhatt et al., 2013; WHO, 2015a). A urbanização, a superpopulação, aglomeração, a pobreza, a infra-estrutura de saúde pública enfraquecida, além das mudanças demográficas globais, são fatores que interferem na incidência da dengue e contribuem para a perpetuação e o crescente número de casos da doença (Farmer, 1996; Guzmán and Kouri, 2002). Além destes fatores, as viagens internacionais também implicam no aumento da incidência da dengue, porque o viajante ajuda a introduzir novas estirpes de diferentes partes do mundo ao chegar doente em seu destino, ou ao voltar para casa portando a doença (Wilder-Smith and Schwartz, 2005). O Brasil sediou em 2014 a Copa do Mundo da FIFA e, em 2016, recebeu os Jogos Olímpicos de Verão, no Rio de Janeiro, dois dos maiores eventos esportivos da atualidade, e por isso esperava receber centenas de milhares de turistas em cada um dos eventos. Embora exista uma vacina contra a dengue, sua eficácia não é suficiente para a prevenção ampla, e a curto prazo, da população suscetível e, por estas razões, este trabalho pretende, através da modelagem matemática, estimar o risco de contágio de dengue para turistas não imunes no Brasil no período da Copa do Mundo da FIFA 2014, em cada uma das 12 cidades-sede do evento e também estimar o risco de contágio de dengue para turistas não imunes no Brasil no período dos Jogos Olímpicos Rio 2016. Para a Copa do Mundo da FIFA, o risco obtido variou de 3,61x10-6 no melhor cenário a 8,33x10-4, no pior. Já para os Jogos Olímpicos, o pior risco individual obtido foi igual a 5.84x10-5 (IC 95%: 5.21x10-5 - 6.47x10-5)The World Health Organization estimates that 3,9 billion people in 128 countries currently live in areas at risk of dengue worldwide, and that 390 (284-528) million infections occur annually, of which 96 (67 -136) million cases with clinical manifestations. It is estimated that 500,000 cases of dengue hemorrhagic occur annually, many of them in children, causing thousands of deaths (Bhatt et al., 2013; WHO, 2015a). Urbanization, overpopulation, agglomeration, poverty, weakened public health infrastructure, and global demographic changes are factors that interfere with the incidence of dengue and contribute to the perpetuation and increasing number of cases of the disease (Farmer, 1996; Guzmán and Kouri, 2002). In addition to these factors, international travel also increase in the incidence of dengue, because an infected traveller may introduce new strains from different parts of the world when they arrive at their destination, or when they return home with the disease (Wilder-Smith and Schwartz, 2005). Brazil hosted the 2014 FIFA World Cup and hosted the 2016 Summer Olympics in Rio de Janeiro, two of the biggest modern sporting events, and it was predicted that each event would receive hundreds of thousands of tourists in each of events. Although a vaccine against dengue exists, its efficacy is not sufficient for the broad and short-term prevention of the susceptible population. As a result, this work intends, through mathematical modelling, to estimate the risk of contagion of dengue for non-immune tourists in Brazil during the period of 2014 FIFA World Cup in each of the 12 host cities of the event and also estimate the risk of contagion of dengue for non-immune tourists in Brazil during the period of Rio 2016 Olympic Games. During the FIFA World Cup, the risk obtained ranged from 3,61x10-6 in the best scenario up to 8,33x10-4 in the worst case scenario. For the Olympic Games, the worst individual risk was 5.84x10-5 (IC 95%: 5.21x10-5 - 6.47x10-5)
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Chartree, Jedsada. "Monitoring Dengue Outbreaks Using Online Data." Thesis, University of North Texas, 2014. https://digital.library.unt.edu/ark:/67531/metadc500167/.
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Internet technology has affected humans' lives in many disciplines. The search engine is one of the most important Internet tools in that it allows people to search for what they want. Search queries entered in a web search engine can be used to predict dengue incidence. This vector borne disease causes severe illness and kills a large number of people every year. This dissertation utilizes the capabilities of search queries related to dengue and climate to forecast the number of dengue cases. Several machine learning techniques are applied for data analysis, including Multiple Linear Regression, Artificial Neural Networks, and the Seasonal Autoregressive Integrated Moving Average. Predictive models produced from these machine learning methods are measured for their performance to find which technique generates the best model for dengue prediction. The results of experiments presented in this dissertation indicate that search query data related to dengue and climate can be used to forecast the number of dengue cases. The performance measurement of predictive models shows that Artificial Neural Networks outperform the others. These results will help public health officials in planning to deal with the outbreaks.
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Orwa, Titus Okello. "Modelling the dynamics of alcohol and methamphetamine co-abuse in the Western Cape Province of South Africa." Thesis, Stellenbosch : Stellenbosch University, 2014. http://hdl.handle.net/10019.1/95982.
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Thesis (MSc)--Stellenbosch University, 2014.ENGLISH ABSTRACT: Clinical results have indicated that abuse of multiple drugs/substances has devastating health and social consequences. The combined abuse of alcohol and the highly addictive methamphetamine has worsened the drug epidemic in South Africa, especially in the Western Cape Province. Using non-linear ordinary differential equations, we formulate a deterministic mathematical model for alcohol-methamphetamine coabuse epidemic. We prove that the growth of the co-abuse epidemic is dependent on the threshold parameters of the individual substances of abuse. The substance with the maximum reproduction number dominates the epidemic. We also prove that the equilibria points of the co-abuse sub-models are locally and globally asymptotically stable when the sub-model threshold parameters are less than unity. Using parameters values derived from the sub-model fittings to data, a population estimate of co-users of alcohol and methamphetamine under treatment is estimated with a prevalence of about 1%. Although the results show of a small proportion of co-users of alcohol and methamphetamine in the province, the prevalence curve is indicative of a persistent problem. Numerical simulation results reveal that co-abuse epidemic would persists when both reproduction numbers are greater than one. Results from sensitivity analysis shows that the individual substance transmission rates between users of methamphetamine and/or alcohol and the general susceptible population are the most vital parameters in the co-abuse epidemic. This suggests the need to emphasise on preventive measures through educational campaigns and social programs that ensure minimal recruitment into alcohol or methamphetamine abuse. Model analysis using the time-dependent controls (policies) emphasizes the need to allocate even more resources on educational campaigns against substance abuse and on effective treatment services that minimizes or eliminates rampant cases of relapse into substance abuse.
AFRIKAANSE OPSOMMING: Kliniese resultate toon dat die misbruik van meer as een dwelmmiddel verwoestende gesondheids-en sosiale gevolge het. Die gekombineerde misbruik van alkohol en die hoogsverslawende methamphetamine het die dwelm-epidemie in Suid-Afrika vererger, veral in die Wes-Kaapse provinsie. Deur van nie-lineere gewone diffensiaalvergelykings gebruik te maak, formuleer ons ’n deterministiese wiskundige model vir epidemie van die gesamentlike misbruik van alkohol en methamphetamine. Ons toon aan dat die groei van die sogenaamde mede-misbruik epidemie afhanklik is van die drumpelparameters van die individuele middels wat misbruik word. Die middels met die grootste voortbringende syfer domineer die epidemie. Ons bewys ook dat die ekwilibriumpunte van die mede-misbruik submodelle plaaslik en globaal asimptoties stabiel is wanneer die sub-model drumpelparameters kleiner as een is. Deur die submodelle op werklike data te pas word waardes vir die drumpelparameters afgelei en word daar beraam dat daar ongeveer 1% van die populasie mede-misbruikers van alkohol en methamphetamine onder behandeling is. Alhoewel die data ’n klein persentasie van mede-misbruikers van alkohol en methamphetamine in die provinsie toon, dui die voorkomskurwe op ’n groeiende endemie en voortdurende probleem. Resultate uit numeriese simulasie toon dat die mede-misbruik epidemie sal voortduur indien beide reproduserende syfers groter as een sal wees. Resultate van sensitiwiteitsanalise toon dat die individuele middeloordragkoerse tussen gebruikers van methamphetamine en/of alkohol en die gewone vatbare populasie die mees noodsaaklike parameters in die mede-misbruik epidemie is. Dit stel voor dat daar meer klem gelê moet word op voorkomingsmaatreëls deur opvoedkundige veldtogte en sosiale programme om te verseker dat minder alkohol en/of methamphetamine misbruik sal word. Model-analise wat gebruik maak van tyd-afhanklike kontroles (beleide) lê verder klem op die feit dat selfs meer hulpbronne aan opvoedkundige veldtogte teen dwelmmisbruik toegewy moet word, asook die effektiewe behandeling wat gevalle van terugval in dwelmmisbruik sal minimeer of elimineer.
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Almeida, Priscila Roque de. "Modelos epidêmicos SIR, contínuos e discretos, e estratégias de vacinação." Universidade Federal de Viçosa, 2014. http://locus.ufv.br/handle/123456789/4933.
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Previous issue date: 2014-02-21Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
The main Objective Of this Work is to study and discretize the epidemic SIR model (Susceptible-Infected-Recovered) developed by Kermack and MCKendrick in 1927 [11], between its Consider the simple models With Vital dynamics and Constant and Vaccination strategies pulses, as a method Of epidemic ControL The study of the stability of Continuous-time models With pulse Vaccination is done by means of the Floquet theory. Already the rnethod Of ñnite difference appro- Ximation is used to forward discretize Continuous systems and the analysis On the stability of the new systems found is displayed The theoretical results are Conñrmed by numerical simulations.
O Objetivo principal desde trabalho é estudar e discretizar os modelos epidêmi- COS SIR (Suscetíveis-Infectados-Recuperados) desenvolvidos por MCKendrick e Kermack em 1927, [11], entre eles Consideramos os modelos simples Com dinâmica Vital e Com estratégias de Vacinação Constante e em pulsos, Como método de Con- trole epidêmico. O estudo da estabilidade dos modelos em tempo Contínuos Com Vacinação em pulsos é feito por meio, da Teoria de Floquet. Já 0 rnétodo de aproximação de diferenças ñnitas para frente é utilizado para discretizar os siste- mas Contínuos e é apresentada a análise sobre a estabilidade dos novos sistemas encontrados. Os resultados teóricos são Conñrmados por simulações numéricas.
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Amara, Pavan Kumar. "Towards a Unilateral Sensing System for Detecting Person-to-Person Contacts." Thesis, University of North Texas, 2018. https://digital.library.unt.edu/ark:/67531/metadc1703441/.
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The contact patterns among individuals can significantly affect the progress of an infectious outbreak within a population. Gathering data about these interaction and mixing patterns is essential to assess computational modeling of infectious diseases. Various self-report approaches have been designed in different studies to collect data about contact rates and patterns. Recent advances in sensing technology provide researchers with a bilateral automated data collection devices to facilitate contact gathering overcoming the disadvantages of previous approaches. In this study, a novel unilateral wearable sensing architecture has been proposed that overcome the limitations of the bi-lateral sensing. Our unilateral wearable sensing system gather contact data using hybrid sensor arrays embedded in wearable shirt. A smartphone application has been used to transfer the collected sensors data to the cloud and apply deep learning model to estimate the number of human contacts and the results are stored in the cloud database. The deep learning model has been developed on the hand labelled data over multiple experiments. This model has been tested and evaluated, and these results were reported in the study. Sensitivity analysis has been performed to choose the most suitable image resolution and format for the model to estimate contacts and to analyze the model's consumption of computer resources.
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Corley, Courtney D. "Modeling the Impact and Intervention of a Sexually Transmitted Disease: Human Papilloma Virus." Thesis, University of North Texas, 2006. https://digital.library.unt.edu/ark:/67531/metadc5289/.
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Many human papilloma virus (HPV) types are sexually transmitted and HPV DNA types 16, 18, 31, and 45 account for more than 75% if all cervical dysplasia. Candidate vaccines are successfully completing US Federal Drug Agency (FDA) phase III testing and several drug companies are in licensing arbitration. Once this vaccine become available it is unlikely that 100% vaccination coverage will be probable; hence, the need for vaccination strategies that will have the greatest reduction on the endemic prevalence of HPV. This thesis introduces two discrete-time models for evaluating the effect of demographic-biased vaccination strategies: one model incorporates temporal demographics (i.e., age) in population compartments; the other non-temporal demographics (i.e., race, ethnicity). Also presented is an intuitive Web-based interface that was developed to allow the user to evaluate the effects on prevalence of a demographic-biased intervention by tailoring the model parameters to specific demographics and geographical region.
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Schramm, Harrison C. "An analytic framework for the War of Ideas." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2006. http://library.nps.navy.mil/uhtbin/hyperion/06Sep%5FSchramm.pdf.
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Thesis (M.S. in Operations Research)--Naval Postgraduate School, September 2006.Thesis Advisor(s): Moshe Kress, Roberto Szechtman. "September 2006." Includes bibliographical references (p. 57-59). Also available in print.
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McBryde, Emma Sue. "Mathematical and statistical modelling of infectious diseases in hospitals." Queensland University of Technology, 2006. http://eprints.qut.edu.au/16330/.
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Antibiotic resistant pathogens, such as methicillin-resistant Staphylococcus aureus (MRSA), and vancomycin-resistant enterococci (VRE), are an increasing burden on healthcare systems. Hospital acquired infections with these organisms leads to higher morbidity and mortality compared with the sensitive strains of the same species and both VRE and MRSA are on the rise worldwide including in Australian hospitals. Emerging community infectious diseases are also having an impact on hospitals. The Severe Acute Respiratory Syndrome virus (SARS Co-V) was noted for its propensity to spread throughout hospitals, and was contained largely through social distancing interventions including hospital isolation. A detailed understanding of the transmission of these and other emerging pathogens is crucial for their containment. The statistical inference and mathematical models used in this thesis aim to improve understanding of pathogen transmission by estimating the transmission rates of contagions and predicting the impact of interventions. Datasets used for these studies come from the Princess Alexandra Hospital in Brisbane, Australia and Shanxi province, mainland China. Epidemiological data on infection outbreaks are challenging to analyse due to the censored nature of infection transmission events. Most datasets record the time on symptom onset, but the transmission time is not observable. There are many ways of managing censored data, in this study we use Bayesian inference, with transmission times incorporated into the augmented dataset as latent variables. Hospital infection surveillance data is often much less detailed that data collected for epidemiological studies, often consisting of serial incidence or prevalence of patient colonisation with a resistant pathogen without individual patient event histories. Despite the lack of detailed data, transmission characteristics can be inferred from such a dataset using structured HiddenMarkovModels (HMMs). Each new transmission in an epidemic increases the infection pressure on those remaining susceptible, hence infection outbreak data are serially dependent. Statistical methods that assume independence of infection events are misleading and prone to over-estimating the impact of infection control interventions. Structured mathematical models that include transmission pressure are essential. Mathematical models can also give insights into the potential impact of interventions. The complex interaction of different infection control strategies, and their likely impact on transmission can be predicted using mathematical models. This dissertation uses modified or novel mathematical models that are specific to the pathogen and dataset being analysed. The first study estimates MRSA transmission in an Intensive Care Unit, using a structured four compartment model, Bayesian inference and a piecewise hazard methods. The model predicts the impact of interventions, such as changes to staff/patient ratios, ward size and decolonisation. A comparison of results of the stochastic and deterministic model is made and reason for differences given. The second study constructs a Hidden Markov Model to describe longitudinal data on weekly VRE prevalence. Transmission is assumed to be either from patient to patient cross-transmission or sporadic (independent of cross-transmission) and parameters for each mode of acquisition are estimated from the data. The third study develops a new model with a compartment representing an environmental reservoir. Parameters for the model are gathered from literature sources and the implications of the environmental reservoir are explored. The fourth study uses a modified Susceptible-Exposed-Infectious-Removed (SEIR) model to analyse data from a SARS outbreak in Shanxi province, China. Infectivity is determined before and after interventions as well as separately for hospitalised and community symptomatic SARS cases. Model diagnostics including sensitivity analysis, model comparison and bootstrapping are implemented.
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Fournié, Guillaume. "The potential for silent circulation of highly pathogenic avian influenza viruses subtype H5N1 to be sustained in live bird markets : a survey of markets in northern Viet Nam and Cambodia and mathematical models of transmission." Thesis, Royal Veterinary College (University of London), 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.559027.
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Amara, Pavan Kumar. "Towards a Unilateral Sensor Architecture for Detecting Person-to-Person Contacts." Thesis, University of North Texas, 2012. https://digital.library.unt.edu/ark:/67531/metadc1703441/.
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The contact patterns among individuals can significantly affect the progress of an infectious outbreak within a population. Gathering data about these interaction and mixing patterns is essential to assess computational modeling of infectious diseases. Various self-report approaches have been designed in different studies to collect data about contact rates and patterns. Recent advances in sensing technology provide researchers with a bilateral automated data collection devices to facilitate contact gathering overcoming the disadvantages of previous approaches. In this study, a novel unilateral wearable sensing architecture has been proposed that overcome the limitations of the bi-lateral sensing. Our unilateral wearable sensing system gather contact data using hybrid sensor arrays embedded in wearable shirt. A smartphone application has been used to transfer the collected sensors data to the cloud and apply deep learning model to estimate the number of human contacts and the results are stored in the cloud database. The deep learning model has been developed on the hand labelled data over multiple experiments. This model has been tested and evaluated, and these results were reported in the study. Sensitivity analysis has been performed to choose the most suitable image resolution and format for the model to estimate contacts and to analyze the model's consumption of computer resources.
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Wyse, Ana Paula Pintado. "Optimal control for malaria vector for a seasonal mathematical model." Laboratório Nacional de Computação Científica, 2007. http://www.lncc.br/tdmc/tde_busca/arquivo.php?codArquivo=140.
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In the Amazonian region occurs a variation in the malaria incidence, which is related to the pluviometric variation annual. The mathematical model proposed here considers this seasonality and different treatment intensities accessible to the infected people. The numerical evidence the seasonal fluctuation and the relationship between the environment temperature and treatment efficiency, showing that the temperature increase strongly affects the extrinsic latent period,reducing the healthy care efficiency. Because malaria treatment already exists it should be import. For another hand, even the investment in treatment is an efficient form to block the epidemy, it is not always sufficient, because the protozoan has been more resistent to the medicine; then scientists are creating transgenic mosquitoes refractory to malaria to couple with wild one, generating descending transgenic. To avaliate this situation, we consider here a mathematical model that describes the relatioship between these populations. Then, we formulate and solve an optimal control problem indicating how the transgenic mosquitoes should be introduced in the environment. The numerical simulations show the effectiveness of the control.Na Amazônia ocorre uma variação na incidência de malária que está intimamente relacionada à variação pluviométrica ao longo do ano. O modelo matemático aqui proposto considera esta sazonalidade e diferentes intensidades de tratamento acessíveis às pessoas infectadas. Experimentos numéricos descrevem a flutuação sazonal e evidenciam uma relação inversa entre a temperatura e eficiência do tratamento, mostrando que um aumento na temperatura afeta fortemente o período latente extrínseco, reduzindo a eficiência do investimento em saúde. Como o tratamento para os infectados existe, é importante concentrar esforços nesse sentido para obter sucesso no controle da malária. Por outro lado, embora o investimento em tratamento seja uma forma eficaz de impedir a epidemia, isso nem sempre é suficiente, pois é fato que o protozoário tem se mostrado cada vez mais resistente aos medicamentos; por esse motivo, cientistas estão criando mosquitos transgênicos refratários à malária que devem acasalar com os mosquitos selvagens, gerando descendência transgência. Para avaliar esta situação, consideramos neste trabalho um modelo matemático que descreve de maneira simplificada a relação entre estas duas populações. A partir desse modelo, formulamos e resolvemos um problema de controle ótimo indicando uma forma adequada de introduzir esses mosquitos transgênicos. Experimentos numéricos mostram a eficácia do controle adotado.