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Agent-based models
Interest
1
#708813
Tags: Agent-based Model, ABM, Agent-based simulation, ABS
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EIDM »
EIDM
EIDM ☜The Emerging Infectious Diseases Modelling Initiative (EIDM) – by the Public Health Agency of Canada and NSERC – aims to establish multi-disciplinary network(s) of specialists across the country in modelling infectious diseases to be applied to public needs associated with emerging infectious diseases and pandemics such as COVID-19. [1]☜F1CEB7
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Research interests »
Research interests
Research interests☜☜9FDEF6
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Agent-based models
Agent-based models☜☜9FDEF6
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Simulation »
Simulation
Simulation☜☜FFFACD
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Advancing agent-based simulation scalability »
Advancing agent-based simulation scalability
Advancing agent-based simulation scalability☜High-fidelity simulation models provide the most accurate representation of the spread of COVID and related diseases but are subject to computational limitations. Agent-based modelling, which treats each individual as a unique agent with objectives/properties/etc., is an example of such a high-fidelity model. The project’s objective is to realize a vastly improved scalability of this type of analysis, using modern techniques in the field of deep learning and AI.☜FFFACD
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Localized Epidemiological Agent-Based Simulation (ABS) »
Localized Epidemiological Agent-Based Simulation (ABS)
Localized Epidemiological Agent-Based Simulation (ABS)☜ This ABS provides information about risk and the effects of both pharmacological and non-pharmacological interventions, as well as detailed control over the rapidly evolving epidemiological characteristics of COVID-19. [1]☜FFFACD
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Cheryl Waldner »
Cheryl Waldner
Cheryl Waldner☜Dr. Cheryl Waldner is a professor of epidemiology from the University of Saskatchewan and the NSERC/Beef Cattle Research Council Senior Industrial Research Chair in One Health and Production Limiting Disease. She is particularly interested in antimicrobial use and resistance as well as the prevention and control of infectious diseases.☜FFFACD
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Nathaniel Osgood »
Nathaniel Osgood
Nathaniel Osgood☜Nathaniel D. Osgood is a Professor in the Department of Computer Science and Associate Faculty in the Department of Community Health & Epidemiology at the University of Saskatchewan.☜FFFACD
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Agent-based »
Agent-based
Agent-based☜☜FFFACD
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04 Robust Agent-Based and Network Infectious Disease Models »
04 Robust Agent-Based and Network Infectious Disease Models
04 Robust Agent-Based and Network Infectious Disease Models☜The “Robust IDM” project will build on the foundations of IDM by developing agent-based and network models. The goal is to develop, expand and refine the agent-based modeling framework, leading to families of models that depart from rigid assumptions like a well-mixed population as adopted in ODE models.☜FFFACD
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pathogen.jl »
pathogen.jl
pathogen.jl☜Simulation, visualization, and inference tools for modelling the spread of infectious diseases with Julia☜FFFACD
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EpiILMCT »
EpiILMCT
EpiILMCT☜The R package EpiILMCT provides tools for simulating from continuous-time individual level models of disease transmission, and carrying out infectious disease data analyses with the same models. The epidemic models considered are distance-based and contact network-based models within Susceptible-Infectious-Removed (SIR) or Susceptible-Infectious-Notified-Removed (SINR) compartmental frameworks. [2]☜FFFACD
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EpiILM »
EpiILM
EpiILM☜The R package EpiILM provides tools for simulating from discrete-time individual level models for infectious disease data analysis. This epidemic model class contains spatial and contact-network based models with two disease types: Susceptible-Infectious (SI) and Susceptible-Infectious-Removed (SIR).☜FFFACD
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Stochastic simulations of classroom-level COVID-19 outbreaks »
Stochastic simulations of classroom-level COVID-19 outbreaks
Stochastic simulations of classroom-level COVID-19 outbreaks☜This repository contains code associated with a preprint exploring COVID-19 outbreaks in classrooms, and how these might be managed with several different protocols: COVID-19s unfortunate events in schools: mitigating classroom clusters in the context of variable transmission. [1]☜FFFACD
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2021/11/02 Joshua Epstein »
2021/11/02 Joshua Epstein
2021/11/02 Joshua Epstein☜Triple Contagion: Toward Cognitive Epidemiology☜FFFACD
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2022/08/02 Compositional methods for health modeling »
2022/08/02 Compositional methods for health modeling
2022/08/02 Compositional methods for health modeling☜The intended audience is mathematical epidemiologists and dynamic modelers for infectious diseases, health and health care seeking to learn about emerging methods and tools, based on applied category theory, for constructing large-scale models efficiently, reliably, and modularly. [1]☜FFFACD
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2021/10/05 Nathaniel Osgood & Cheryl Waldner »
2021/10/05 Nathaniel Osgood & Cheryl Waldner
2021/10/05 Nathaniel Osgood & Cheryl Waldner☜Antimicrobial resistance from farm to fork: first steps in a multi-scale modelling approach.☜FFFACD
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Entered by:-
David Price
NodeID:
#708813
Node type:
Interest
Entry date (GMT):
3/12/2023 12:40:00 AM
Last edit date (GMT):
3/12/2023 12:41:00 AM
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