Canadian Medical Association Journal (CMAJ) Article CMAJ Article – Projected effects of nonpharmaceutical public health interventions to prevent resurgence of SARS-CoV-2 transmission in Canada This paper describes the results of predictive modelling of several nonpharmaceutical measures used to prevent further transmission of COVID-19. A Public Health Agency of Canada research team used an aged-structured agent-based…
Canada Communicable Disease Report (CCDR) Publication Summary CCDR Article – Modelling Scenarios of the Epidemic of COVID-19 in Canada The article 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…
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.
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.
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…
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…
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).
Join the National Collaborating Centre for Infectious Diseases (NCCID) for a new, interdisciplinary webinar series! The Synergies Series harnesses the knowledge of experts from several disciplines and nations. Collaborators share research evidence, context-based insights, information on data availability, and practical tools to develop better infectious disease models and evidence-based public health policies for the control…
Canada’s response to Covid-19 is being guided by data and mathematical modelling. The Public Health Agency of Canada (PHAC) has shared information with Canadians from their COVID-19 modelling work. The results from the data indicate that it is critical and essential to physically distance, detect and isolate cases of COVID-19, identify and quarantine close contacts, and prevent international infection…
Mathematical modelling is a research method that can inform public health planning and infectious disease control. Through complex simulations of real-world possibilities, mathematical modelling provides a cost-effective and efficient method to assess optimal public health interventions. NCCID supports an expanding area of knowledge translation and exchange related to mathematical modelling for public health. This has…
Mathematical modelling can provide timely evidence to guide decision-making. As public health planners strive to prepare for potential outbreaks of COVID-19, this quantification can help identify the type and intensity of control measures required to mitigate infection spread.
Case study on the application of mathematical modelling to assess the impact of a newly-designed intervention on the burden of syphilis in Winnipeg, Manitoba.
Their story illustrates how mathematical modelling can provide timely evidence to guide decision-making by public health planners and practitioners throughout the implementation of a new intervention.
The lessons they share may help to demystify modelling and reveal the benefits of collaborations between modellers and public health personnel.
