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    Modeling Scenario
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    6-045-CholeraTranmission-ModelingScenario
    During the project described here, the students will learn how to solve and address a practical problem such as cholera transmission using various mathematical tools.
    Potential Scenario
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    2016-Lewnard-Townsend-Climatic and evolutionary drivers of phase shifts in the plague epidemics of colonial India
    Our analysis shows that historical datasets can yield powerful insights into the transmission dynamics of reemerging disease agents with which we have limited contemporary experience to guide quantitative modeling and inference.
    Potential Scenario
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    2010-Del-Ciello-EtAl-Modeling Disease
    We model the transmission of a disease through a population. Such modeling is very important to the study of epidemiology and the practice of medicine.
    Potential Scenario
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    2015-Just-Callender-Differential equation models of disease transmission
    The work give full analyses of standard epidemic model and then shows how to do it with differential equations and agent-based modeling. Then it compares the results.
    Potential Scenario
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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.
    Potential Scenario
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    2016-Lofgren-EtAl-Equations of the End Teaching Mathematical Modeling Using the Zombie Apocalypse
    In this article, we explore several uses of zombie epidemics to make mathematical modeling and infectious disease epidemiology more accessible to public health professionals, students, and the general public.
    Potential Scenario
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    2011-Mandal-EtAl-Mathematical models of malaria
    The first aim of this article is to develop, starting from the basic models, a hierarchical structure of a range of deterministic models of different levels of complexity. The second is to elaborate, using some of the representative mathematical...
    Potential Scenario
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    2010-Jungck-EtAl-Mathematical Manipulative Models-In Defense of Beanbag Biology
    This paper offers up samples of projects from the Bio- QUEST Curriculum Consortium’s 24-yr experience of holding faculty development workshops for biology and mathematics educators.
    Potential Scenario
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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
    Potential Scenario
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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.
    Potential Scenario
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    2014-Murillo-EtAl-Vertical Transmission in a Two-Strain Model of Dengue Fever
    The model is used to show that lower transmission rates of DENV-2 Asian are sufficient for displacing DENV-2 American in the presence of vertical transmission.
    Potential Scenario
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    2018-Arden_Baxter-Modeling Public Opinion
    In this paper, we adapt the epidemiological models to model the dynamics of public opinion. Public opinion is any view prevalent among the general public. Our model considers any topic or issue in which the public has two decisive and opposing...
    Potential Scenario
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    2001-Smith-Moore-The SIR Model for Spread of Disease
    A multiple part tour of SIR Models freely available with Maple, Mathematics, and MatLab support files at MAA site.
    Potential Scenario
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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.
    Potential Scenario
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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.
    Potential Scenario
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    2011-Gaff-Lenhart-Use of optimal control models to predict treatment time for managing tick-borne disease
    Tick-borne diseases have been on the rise recently, and correspondingly, there is an increased interest in implementing control measures to decrease the risk. Optimal control provides an ideal tool to identify the best method for reducing risk.
    Potential Scenario
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    2016-Helena_Sofia_Rodrigues-Application of SIR epidemiological model new trends
    In this paper, the basic transmission model is analyzed, as well as simple tools that allows us to extract a great deal of information about possible solutions. A set of applications - traditional and new - is described to show importance of this...
    Potential Scenario
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    2018-Nyanginja-Angwenyi-Musyoka-Orwa - Mathematical modeling of the effects of public health education on tungiasis
    In this paper, we formulate and study a mathematical model for the dynamics of jigger infestation incorporating public health education using systems of ordinary differential equations and computational simulations.
    Modeling Scenario
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    1-160-HeartDeathRate-ModelingScenario
    Students simulate experience from a given data set which represents the heart death rate during the period 2000 - 2010 using several approaches to include exponential decay, difference equation, differential equation, and parameter estimation...
    Article or Presentation
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    2020-TeachingModule-SpreadOfCommonColdSimulation
    This simulation is meant to introduce the idea of a differential equation model and investigate the impact of heightened hygiene and decreased interactions on the spread of an infectious disease. The focus of this simulation is on the common cold.