CANadian Network for MODelling infectious Disease / Réseau CANadien de MODélisation des maladies infectieuses
Strengthening the community of people who are making and using infectious disease models to improve public health both inside and outside of Canada.
- CANMOD aims to increase Canada’s capacity for data-driven emerging infectious disease modelling (EIDM) to directly support short, medium, and long-term public health decisions.
- Our network comprises collaborative teams of modellers, statisticians, epidemiologists, public health decision-makers, and those implementing and delivering interventions.
- The questions we tackle will be grounded in public health needs and generated in partnership between research investigators and knowledge users—public health leaders, health administrators and policy-makers.
- This collaborative research will drive data collection, curation and access, such that critical information is available when needed.
- While the network will address questions of immediate relevance in the shorter term, we will take this approach with longer-term challenges in mind, building a trajectory of enhancing modelling expertise and capacity in infectious disease in Canada.]
- We are on this path already, as researchers move from the daily challenges of decision-making during the COVID-19 pandemic to working on longer-term policy questions. CANMOD will build and coordinate national capacity in infectious disease modelling at the forefront of public health.
- This capacity will position public health across Canada for better control of any infectious disease, and will build better preparedness and resilience in case of future pandemics. It will offer extensive experiential training opportunities to postdoctoral fellows (PDFs), graduate and undergraduate students at the intersection of infectious disease modelling, public health policy and decision making.
- CANMOD is committed to increasing equity, diversity, and inclusion in the next generation of infectious disease modellers. Trainees will be well-placed for quantitatively-oriented careers in academia, industry and the public sector.