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23/11/16 Madeline Ward Document1 #715385 Bayesian epidemic models with dynamic adherence to protective behaviour adoption.

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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 »NetworksNetworks☜Learn more about the five EIDM networks: CANMOD, MfPH, OMNI, OSN, and SMMEID.☜79B9B9

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CANMOD »CANMOD CANMOD ☜CANadian Network for MODelling infectious Disease / Réseau CANadien de MODélisation des maladies infectieuses☜79B9B9

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CANMOD – Training »CANMOD – TrainingCANMOD – Training☜We are building expertise amongst the next generation of infectious disease modellers, and preparing them for careers in academia, industry, and the public sector.☜AECCD8

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23/11/12 CANMOD: Progress and Next Steps »23/11/12 CANMOD: Progress and Next Steps23/11/12 CANMOD: Progress and Next Steps☜The Banff International Research Station will host the The Canadian Network for Modelling Infectious Diseases: Progress and Next Steps workshop in Banff from November 12 to November 17, 2023. Organizers: David Earn (McMaster University), Caroline Colijn (Simon Fraser University), Irena Papst (Public Health Agency of Canada).☜E883B6

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23/11/16 Madeline Ward23/11/16 Madeline Ward☜Bayesian epidemic models with dynamic adherence to protective behaviour adoption.☜B5ACA0

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Madeline Ward »Madeline WardMadeline Ward☜Madeline A. Ward is a PHD student in Biostatistics in the Department of Mathematics and Statistics at the University of Calgary.☜FFFACD

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Behaviour »BehaviourBehaviour☜In infectious disease outbreaks we often see the population reacting to outbreak severity, changing the transmission dynamics over time. For example, the COVID-19 pandemic has led to voluntary and government-mandated physical distancing across the world, which slows spread. Further, we see these behaviours relax when case counts are low and increase when high.☜FFFACD

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Mathematical modelling of human response behaviour during pandemics »Mathematical modelling of human response behaviour during pandemicsMathematical modelling of human response behaviour during pandemics☜Mathematical modelling of human response behaviour, opinion dynamics, and social influence during pandemics. COVID-19 showed that understanding human response to intervention is essential in mitigating disease spread and forming policy. We are particularly interested in understanding how opinion influence affects vaccine and NPI hesitancy. This project aims to incorporate a broader understanding of intervention and control, which embodies the entire theme.☜FFFACD

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Entered by:- David Price
NodeID: #715385
Node type: Document
Entry date (GMT): 11/16/2023 10:14:00 PM
Last edit date (GMT): 11/16/2023 11:19:00 PM
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