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MfPH – Projects
Project
1
#701038
CONTEXT
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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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Networks »
Networks
Networks☜Learn more about the five EIDM networks: CANMOD, MfPH, OMNI, OSN, and SMMEID.☜79B9B9
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MfPH »
MfPH
MfPH☜Mathematics for Public Health (MfPH), led by Dr. V. Kumar Murty, Director of the Fields Institute and Professor at the University of Toronto, will aim to bridge the gap between mathematical research and real public health issues. The team will seek to produce models that are effective, practical and reliable for applications to public health issues for COVID-19 as well as boost Canada’s future pandemic preparedness. [1]☜79B9B9
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MfPH – Projects
MfPH – Projects☜☜70BEA3
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01 Contact Mixing and Optimal Decision Making »
01 Contact Mixing and Optimal Decision Making
01 Contact Mixing and Optimal Decision Making☜The project aims to develop a comprehensive modelling approach that integrates key heterogeneities by age, setting, immunization status, geographical locations and a generalized intervention package accounting for evolving pharmaceutical treatment and vaccination, non-pharmaceutical interventions, diagnostic testing, contact tracing, and case isolation.☜70BEA3
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02 Integrative Modelling »
02 Integrative Modelling
02 Integrative Modelling☜This project aims to develop an integrative framework that explores the impact of public health interventions across a broad spectrum of societal and economic issues, through ‘stitching together’ the various individual models to determine the total effect of the virus on society.☜70BEA3
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03 Risk Evaluation and Early Detection »
03 Risk Evaluation and Early Detection
03 Risk Evaluation and Early Detection☜Risk Evaluation and Early Detection of Emerging Infectious Disease Outbreaks in Canada.☜70BEA3
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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.☜70BEA3
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05 Mobility Network and Patch Models »
05 Mobility Network and Patch Models
05 Mobility Network and Patch Models☜The spatio-temporal spread of infectious diseases involves a succession of transport and importation events, so to better model global spread, we will develop models of both processes, in isolation and together.☜70BEA3
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06 Infection Control during Mass Gathering Events »
06 Infection Control during Mass Gathering Events
06 Infection Control during Mass Gathering Events☜Mass gatherings (MG) have the potential to facilitate global spread of infectious pathogens. Individuals from disease-free areas may acquire the pathogen while at the mass gathering site, which in turn could lead to its translocation in the originally disease-free zones when individuals return home.☜70BEA3
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07 Antimicrobial Resistance »
07 Antimicrobial Resistance
07 Antimicrobial Resistance☜By the inclusion of an evolutionary framework into population models of AMR, we will aim to take advantage of linking genetic and epidemiological data, and investigate the effect of various exogenous factors on the secular trend.☜70BEA3
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08 Contact tracing »
08 Contact tracing
08 Contact tracing☜This project aims to develop models and analyses that incorporates the processes of diagnosis of symptomatic individuals and contact tracing to address important issues relevant to outbreak control: tracing delays; tracing resource allocation among regions with different prevalence or growth rate; adherence of individuals to isolation and to disclosure of contacts; vaccine coverage levels.☜70BEA3
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09 Joint Estimation of Parameters in Outbreak Models »
09 Joint Estimation of Parameters in Outbreak Models
09 Joint Estimation of Parameters in Outbreak Models☜This project aims to address various issues relevant to joint estimation of parameters in epidemic models.☜70BEA3
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10 Dynamic Bifurcation and Scenario Analyses »
10 Dynamic Bifurcation and Scenario Analyses
10 Dynamic Bifurcation and Scenario Analyses☜This project aims to deliver a MfPH Library of important model frameworks (discrete vs continuous, deterministic vs stochastic, homogeneous vs heterogeneous and structured); examine their respective strengths and limitations in association with those issues addressed in other MfPH projects; link the bifurcation phenomena to observed patterns of COVID-19 pandemic in Canada and globally; and distinguish finite-time behaviour optimisation from asymptotic behaviour (infinite time horizon).☜70BEA3
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11 Immune response, immune memory and cross-immunity »
11 Immune response, immune memory and cross-immunity
11 Immune response, immune memory and cross-immunity☜This project aims to develop and analyze a suite of models of an immune response to an emergent infectious pathogen incorporating immune memory generated by prior infection by related pathogens.☜70BEA3
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12 Pathogen Contamination and Spread Control during Food-Processing »
12 Pathogen Contamination and Spread Control during Food-Processing
12 Pathogen Contamination and Spread Control during Food-Processing ☜We will develop and analyze novel deterministic and stochastic simulation models to investigate necessary conditions under which an infectious disease has emerged from food or wastewater to humans and investigate its initial and transient dynamics to inform policy makers in public health to make necessary interventions.☜70BEA3
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13 Phylodynamic Modelling of Infectious Diseases »
13 Phylodynamic Modelling of Infectious Diseases
13 Phylodynamic Modelling of Infectious Diseases☜In this project, we aim to develop phylodynamic and phylogeographic models to a) characterize the early spread of the epidemic that include insights into the origin, transmission potential, transmission routes, and genetic diversity of the pathogen; b) understand pathogen spread across spatiotemporal scales within and between geographical locations, and determine the factors that have driven pathogen spread. ☜70BEA3
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CIHR Variants of Concern Study »
CIHR Variants of Concern Study
CIHR Variants of Concern Study☜MfPH network, led by the Fields Institute and leveraging the multidisciplinary membership of the Modelling Consensus and Science Tables, and beyond, aims to develop innovative mathematical models to understand disease transmission dynamics in the context of SARS-CoV-2 and its variants, and to connect mathematicians with other experts in the diverse aspects of disease modelling to accelerate the introduction of new mathematical tools, methods, analyses and perspectives for effective response.☜70BEA3
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EOC Modeling Simulations and Exercises »
EOC Modeling Simulations and Exercises
EOC Modeling Simulations and Exercises☜MfPH will utilize the Advanced Disaster, Emergency and Rapid Simulation Facility (ADERSIM) facility housed at York University to develop Emergency Operations Center (EOC) modeling, simulation and exercises.☜70BEA3
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Entered by:-
David Price
NodeID:
#701038
Node type:
Project
Entry date (GMT):
9/16/2022 4:19:00 PM
Last edit date (GMT):
9/16/2022 4:20:00 PM
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