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    Potential Scenario
    142

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    68

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    2017-Allali-EtAl-Mathematical Modeling of the Adaptive Immune Responses in the Early Stage of the HBV Infection
    The aim of this paper is to study the early stage of HBV infection and impact delay in the infection process on the adaptive immune response, which includes cytotoxic T-lymphocytes and antibodies.
    logisticHBV infectionadaptive immunie responseT-lymphocytes
    Potential Scenario
    177

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    69

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    2002-Nelson-Perelson-Mathematical analysis of delay differential equations models of HIV-1 infection
    We develop and analyze a set of models that include intracellular delays, combination antiretroviral therapy, and the dynamics of both infected and uninfected T cells.
    infectionHIVT cells
    Potential Scenario
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    40

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    2008-Yang-EtAl-Differential Equation Model of HIV Infection of CD T-Cells with Delay 
    Abstract: An epidemic model of HIV infection of CD4+ T-cells with cure rate and delay is studied. We include a baseline ODE version of the model, and a differential-delay model with a discrete time delay.
    virusT cellsHopf bifurcationendemic equilibrium
    Potential Scenario
    153

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    104

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    2017-Fred_Adler-Mathematically Modeling Asthma
    Our Asthma models have examined how a viral infection can tip the immune system into a different state, with the potential to predispose an individual to future asthma
    infectionasthmaimmune responserhinovirus
    Potential Scenario
    149

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    52

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    2006-Loyd-Wodarz-Drug Resistance in Acute Viral Infections-Rhinovirus as a Case Study
    We develop an epidemiological model that can be used to address the spread of resistance at the population level, and a virus dynamics model that can be used to study the dynamics of virus over the time course of an individual’s infection.
    stabilityresistancevirusdrugepidemic competitionimmune responserhinovirus
    Article or Presentation
    133

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    33

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    2002-Patrick_Nelson-Alan_Perelson-Mathematical_analysis_of_delay_differential _equation_models_of_HIV-1_infection
    Models of HIV-1 infection that include intracellular delays are more accurate representations of the biology and change the estimated values of kinetic parameters when compared to models without delays.
    delayHIV-1T cellscombination antiviral therapy
    Potential Scenario
    256

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    67

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    2018-Van_Kinh Nguyen-Esteban_Hernandez-Vargas-Parameter estimation in mathematical models of viral infections using R
    Mathematical modeling has played a central role to understand mechanisms in different viral infectious diseases. In this approach, biological-based hypotheses are expressed via mathematical relations and then tested based on empirical data.
    simulationdiseasevirusviral infection
    Potential Scenario
    155

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    54

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    2009-Noakes-Sleigh-Mathematical models for assessing the role of airflow on the risk of airborne infection in hospital wards
    Understanding the risk of airborne transmission can provide important information for designing safe healthcare environments with an appropriate level of environmental control for mitigating risks.
    infectioncompartmenthospitalventilationairbornesthochasticWells–Riley
    Potential Scenario
    154

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    83

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    2002-Dietz-Heesterbeek-Daniel Bernoulli-epidemiological model revisited
    The seminal paper by Daniel Bernoulli published in 1766 is put into a new perspective. After a short account of smallpox inoculation and of Bernoulli’s life, the motivation for that paper and its impact are described.
    life tableepidemicsmallpoxDaniel Bernoullicompeting riskinoculation
    Potential Scenario
    130

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    45

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    2020-Chen_Et_Al-MathModel_Simulation_Phase-Based_Transmissability_Corona_Virus
    In this study, we developed a Bats-Hosts-Reservoir-People transmission network model for simulating the potential transmission from the infection source (probably be bats) to the human infection.
    basic reproduction numbercoronavirusnext generation matrixtransmissibilitynovel coronavirus
    Potential Scenario
    170

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    71

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    2011-Yanyu_Xiao-Study of Malaria Transmission Dynamics by Mathematical Models
    The novelty lies in the fact that different distribution functions are used to describe the variance of individual latencies. The theoretical results of this project indicate that latencies reduce the basic reproduction number.
    infectious diseaseinfectionmalarialatencyspatial dispersalmulti-species
    Modeling Scenario
    382

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    665

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    6-007-FunctionsAndDerivativesInSIRModels-ModelingScenario
    Given a system of differential equations, how do the solution graphs compare with the graphs of the differential equations? Students tackle this question using SIR models for well-known infectious diseases.
    epidemiologyspecies interactionsderivativesvisualizationinfectionSIR modelsLaw of Mass Action
    Potential Scenario
    157

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    51

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    2012-Tweedle-Smith-Mathematical model of Bieber Fever-The most infectious disease of our time
    We develop a mathematical model to describe the spread of Bieber Fever, whereby individuals can be susceptible, Bieber-infected or bored of Bieber.
    infectious diseasediseaseinfectionmediaJustin BieberBieber feversymptomsboredreproductive ratio
    Modeling Scenario
    551

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    279

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    0

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    1-104A-T-InfectionRisk-ModelingScenario
    This project is designed to examine differences between the exponential and logistic growth models in biology and how to apply these models in solving epidemic questions and comparing to actual disease data sets.
    regressioninfectionCOVID19carrying capacitylogistic equationexponential model
    Potential Scenario
    169

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    94

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    2014-Rogert_Smith-Mathematical Modeling of Zombies
    Here, we use diffusion to model the zombie population shuffling randomly over a one-dimensional domain.
    kineticsZombiezombificationinteraction times
    Modeling Scenario
    316

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    140

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    1-104-InfectionRisk-ModelingScenario
    This project is designed to examine differences between the exponential and logistic growth models in biology and how to apply these models in solving epidemic questions.
    infectionlogisticexponentialcovidcarrying capacity
    Modeling Scenario
    324

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    506

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    0

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    6-016-PandemicModeling-ModelingScenario
    The recent coronavirus outbreak has infected millions of people worldwide and spread to over 200 countries. How can we use differential equations to study the spread of coronavirus?
    population dynamicsinfectious diseasediseaseEbolaeSIR modelsCOVID19pandemicepidemicreproduction number
    Potential Scenario
    253

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    62

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    2011-Cruz-Aponte-Herrera-Valdez-Mitigating effects of vaccination on influenza outbreaks given constraints in stockpile size and daily administrati
    We present a SIR-like model that explicitly takes into account vaccine supply and the number of vaccines administered per day and places data-informed limits on these parameters.
    vaccinationinfectionSIRepidemic
    Potential Scenario
    185

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    80

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    2011-Nakul-Chitnis-Introduction to Mathematical Epidemiology - Deterministic Compartmental Model
    Deterministic compartmental models form the simplest models in the mathematical study of infectious disease dynamics. They assume that a population is homogenous (all people are the same) and the only distinction is in their disease state.
    sensitivitydiseaseinfectionthresholdcompartmentbifrucation
    Potential Scenario
    151

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    46

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    2006-Ousmane_Mousa_Tessa-Mathematical model for control of measles by vaccination
    In this article, we use a compartmental mathematical model of the dynamics of measles spread within a population with variable size to provide this framework.
    vaccinationcompartmentherd immunitymeaslesoptimal strategy