Canada Spends Logo

Explore our Budget 2026 analysis

Grant: Discovery Grants Program - Individual

York University

$11,000.00

Optimizing Vaccination Strategies within a Population-Pathogen Landscape

FY 2015-16

Summary
Modelling and computational approaches provide powerful tools in the study of disease dynamics at both the individual and population levels. Recent analytical developments, coupled with advances in information and communications technologies, have opened up novel vistas and presented new challenges in mathematical immunology and epidemiology. Mathematical, statistical, and computational modelling has enormous potential to address these challenges, offering integrated frameworks for making assumptions explicit and for best using limited data, highlighting key factors that determine policy needs, providing quantitative projections, and assessing risks, benefits, and trade-offs that are implicit in disease dynamics and control programs. The utility of mathematical and computational modelling is well-documented. An important example is the implementation of model-based recommendations for vaccination strategies and use of antiviral drugs during the 2009 pandemic influenza. By developing and applying these models, this proposal aims to address the following objectives: 1. Evaluate the effect of population demographics on the outcome of vaccination strategies in the presence and/or absence of varying degrees of pre-existing immunity. 2. Determine the impact of individual and population immune profiles on the long-term effects of vaccination strategies. The long-term objective of this research program is to: 3. Develop mathematical and computational methodologies for integrating disease models with biological data to enhance the understanding of complex mechanisms underlying disease emergence and spread.
Program
Discovery Grants Program - Individual
Location
Ontario, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data

As published

Application id
355557-2013
Name nom
Moghadas, Seyed
Department département
Mathematics and Statistics
Organization id
38
Institution établissement
York University
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2015
Competition year année de concours
2013
Award amount
11000
Program id
RGPIN
Program name en
Discovery Grants Program - Individual
Program name fr
Programme de subventions à la découverte - individuelles
Group en
Discovery grants programs
Group fr
Programmes de subventions à la découverte
Committee code
1508
Committee name en
Mathematics and Statistics
Committee name fr
Mathématiques et statistique
Area of application code
405
Area of application group en
Environment
Area of application group fr
Environnement
Area of application en
Modelling and mathematical simulation of natural processes
Area of application fr
Modélisation et simulation mathématique des processus naturels
Research subject code
2960
Research subject group en
Applied mathematics
Research subject group fr
Mathématiques appliquées
Research subject en
Mathematical modelling
Research subject fr
Modélisation mathématique
Partie
3
Nb partie
5
Application title
Optimizing Vaccination Strategies within a Population-Pathogen Landscape
Keyword
NSERC
Application summary
Modelling and computational approaches provide powerful tools in the study of disease dynamics at both the individual and population levels. Recent analytical developments, coupled with advances in information and communications technologies, have opened up novel vistas and presented new challenges in mathematical immunology and epidemiology. Mathematical, statistical, and computational modelling has enormous potential to address these challenges, offering integrated frameworks for making assumptions explicit and for best using limited data, highlighting key factors that determine policy needs, providing quantitative projections, and assessing risks, benefits, and trade-offs that are implicit in disease dynamics and control programs. The utility of mathematical and computational modelling is well-documented. An important example is the implementation of model-based recommendations for vaccination strategies and use of antiviral drugs during the 2009 pandemic influenza. By developing and applying these models, this proposal aims to address the following objectives: 1. Evaluate the effect of population demographics on the outcome of vaccination strategies in the presence and/or absence of varying degrees of pre-existing immunity. 2. Determine the impact of individual and population immune profiles on the long-term effects of vaccination strategies. The long-term objective of this research program is to: 3. Develop mathematical and computational methodologies for integrating disease models with biological data to enhance the understanding of complex mechanisms underlying disease emergence and spread.