James McCaw

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Professor of Mathematical Biology

University of Melbourne

Australia

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About

James McCaw is a Professor of Mathematical Biology at The University of Melbourne, Australia. His research focuses on mathematical modeling of infectious diseases, particularly in the context of COVID-19 and influenza. Recent articles include studies on public health policy, stochastic modeling of epidemic dynamics, and the impact of immune dynamics on multi-season epidemics.

Recent Grants

Grant: Close

The dynamics of interacting infections

Open Date: 2021-01-01

Close Date: 2024-01-01

Articles (18)

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2025

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2022

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2022

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2021

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2020

Collaborators (12)

Michael Lydeamore

Lecturer

MONASH UNIVERSITY

AUSTRALIA

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Peter Taylor

Professor

University of Melbourne

AUSTRALIA

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Oliver Eales

University of Melbourne

AUSTRALIA

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Michael J. Plank

University of Canterbury

NEW ZEALAND

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Nick Golding

Telethon Kids Institute

AUSTRALIA

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Nicholas Geard

Associate Professor

University of Melbourne

AUSTRALIA

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Freya M. Shearer

University of Melbourne

AUSTRALIA

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James Osborne

Professor at School of Mathematics and Statistics

University of Melbourne

AUSTRALIA

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Mick Roberts

Massey University

NEW ZEALAND

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Gerard Ryan

Children's Cancer Institute Australia

AUSTRALIA

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Cameron Zachreson

University of Melbourne

AUSTRALIA

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Jodie McVernon

University of Melbourne

AUSTRALIA

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James McCaw

Research Interests

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About

Recent Grants

Articles (18)

Accounting for the geometry of the respiratory tract in viral infections

Should public health policy exempt cases with low viral load from isolation during an epidemic?: a modelling study

Stochastic modelling of early-stage COVID-19 epidemic dynamics in rural communities in the United States

A modular approach to forecasting COVID-19 hospital bed occupancy

Inferring temporal trends of multiple pathogens, variants, subtypes or serotypes from routine surveillance data

How immune dynamics shape multi-season epidemics: a continuous-discrete model in one dimensional antigenic space

Spatial information allows inference of the prevalence of direct cell–to–cell viral infection

Challenges in the case-based surveillance of infectious diseases

Biases in Routine Influenza Surveillance Indicators Used to Monitor Infection Incidence and Recommendations for Improvement

Choice of spatial discretisation influences the progression of viral infection within multicellular tissues

A modelling approach to estimate the transmissibility of SARS-CoV-2 during periods of high, low, and zero case incidence

Improving estimates of waning immunity rates in stochastic SIRS models with a hierarchical framework

How effective were Australian Quarantine Stations in mitigating transmission aboard ships during the influenza pandemic of 1918-19?

COVID-19 in low-tolerance border quarantine systems: Impact of the Delta variant of SARS-CoV-2

Stochastic Modeling of Within-Host Dynamics of Plasmodium Falciparum

THE ROLE OF THE MATHEMATICAL SCIENCES IN SUPPORTING THE COVID-19 RESPONSE IN AUSTRALIA AND NEW ZEALAND

Modelling the Effect of MUC1 on Influenza Virus Infection Kinetics and Macrophage Dynamics

Infectious disease pandemic planning and response: Incorporating decision analysis

Collaborators (12)

Michael Lydeamore

Peter Taylor

Oliver Eales

Michael J. Plank

Nick Golding

Nicholas Geard

Freya M. Shearer

James Osborne

Mick Roberts

Gerard Ryan

Cameron Zachreson

Jodie McVernon

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