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23/11/13 Junling Ma Document1 #715359 Evaluating the effectiveness of contact tracing in Toronto during the early stage of the COVID-19 pandemic.

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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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23/11/13 Junling Ma23/11/13 Junling Ma☜Evaluating the effectiveness of contact tracing in Toronto during the early stage of the COVID-19 pandemic.☜B5ACA0

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Junling Ma »Junling MaJunling Ma☜I am an associate professor in Department of Mathematics and Statistics, University of Victoria. I received B.Sc. in Applied Mathematics in 1994, and M.Sc in Applied Mathematics in 1997, from Xian Jiaotong University, China. I received Ph.D. in Applied Mathematics from Princeton University in 2003.☜FFFACD

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Contact tracing »Contact tracingContact tracing☜☜FFFACD

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Entered by:- David Price
NodeID: #715359
Node type: Document
Entry date (GMT): 11/16/2023 5:24:00 PM
Last edit date (GMT): 11/16/2023 5:24:00 PM
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