This webinar will examine how mathematical models have improved our understanding of disease persistence in populations and explore how models of endemicity may be applied to evolving COVID-19.
Stream: Mathematical Modelling
Big Data Basics Infographic
This infographic overviews big data in Public health. It explains basic big data concepts, types of datasets and how public health uses this technology.
PHAC Agent-Based Models on COVID-19
Agent-based models (ABMs) can systematically simulate actions and interactions of independent “agents” that can represent people, places and/or objects within a predefined environment. These models aim to evaluate the success of public health interventions depending upon community structure and population dynamics.
The COVID-19 Public Health Agency of Canada (PHAC) Modelling Group
COVID-19 has spread across the world, and the associated morbidity and mortality, spawning extensive international research to inform both clinical and public health evidence-based actions to mitigate its effects. The Public Health Agency of Canada, as part of its mandate, is monitoring, preparing and responding to the COVID-19 outbreak to ensure minimal impacts to the…
PHAC Gathering Risks Model: On-line Calculator
Simple mathematical modelling approaches to assessing the transmission risk of SARS-CoV-2 at gatherings This paper explores the factors that influence the risk of disease transmission at gatherings and the potential effects of mitigation strategies. This mathematical model is built on general principles and provides a simple and pragmatic application of these principles in order to…
PHAC Age-Stratified SEIR Compartmental Model on COVID-19
Assessing the impact of varying levels of case detection and contact tracing on COVID-19 transmission in Canada during lifting of restrictive closures using a dynamic compartmental model This study (with plain-language summary) underlines the importance of a cautious approach to lifting restrictive closures in this second phase of the epidemic. This approach includes efforts by public…
PHAC SEIR Model on COVID-19
Modelling scenarios of the epidemic of COVID-19 in Canada This paper (with plain-language summary) describes predictive modelling of COVID-19 in general, and efforts within the Public Health Agency of Canada to model the effects of non-pharmaceutical interventions (NPIs) on the transmission of SARS-CoV-2 in the Canadian population to support public health decisions. The article describes…
COVID-19 Vaccine Outlook & Opportunities for Modelling
Immunization by vaccine is one of the most successful public health interventions for the prevention and control of both endemic infectious diseases and emerging pathogens.
Join us and Dr. Joanne Langley who will present an overview of current vaccine development for COVID-19.
Epidemiology of COVID-19 – Evidence from China
Emerging infectious diseases can spread dramatically and lead to large-scale outbreaks, as seen in pandemics of influenza H1N1, MERS, SARS-CoV-1 and, most recently, SARS-CoV-2 (COVID-19).
Join us and Dr. Benjamin Cowling who will overview the natural history of COVID-19 and shares recent findings from his epidemiological research.
Mathematical Modelling in Public Health Planning: Flu Vaccine
In public health, mathematical modelling helps us answer difficult, real-world questions and understand complex relationships between biological, demographic, and environmental factors. Modelling helps answer infectious disease-related questions like “What is the best vaccine to protect an elderly population at increased risk of infection from seasonal influenza?” Modellers interpret the model outcomes and draw conclusions to…
Mathematical Modelling in Public Health: Tuberculosis
In public health, mathematical modelling helps us answer difficult, real-world questions and understand complex relationships between biological, demographic, and environmental factors. Modelling helps answer infectious disease-related questions like “What are the potential effects of three different interventions on a specific disease?” Modellers interpret the model outcomes and draw conclusions to make accurate, evidence-driven and transparent…
An Overview of Mathematical Modeling for Pandemic Control
The emergence of COVID-19 has revealed the need for more effective model-based policies that meet the real-time challenges and surging demands of a pandemic-related emergency.
Join us and Dr. Ashleigh Tuite who will present an overview of mathematical modelling for public health pandemic control (presentation prepared by Dr. Amy Greer).