Characterising pandemic severity and transmissibility from data collected during first few hundred studies

Andrew J Black; Nicholas Geard; James M McCaw; Jodie McVernon; Joshua V Ross

Journal article

Characterising pandemic severity and transmissibility from data collected during first few hundred studies

Andrew J Black, Nicholas Geard, James M McCaw, Jodie McVernon, Joshua V Ross

EPIDEMICS | ELSEVIER SCIENCE BV | Published : 2017

DOI: 10.1016/j.epidem.2017.01.004

University of Melbourne Researchers

James McCaw Author Mathematics and Statistics

Nic Geard Author Computing and Information Systems

Jodie McVernon Author Infectious Diseases

Related Projects (2)

DEVELOPING MATHEMATICAL MODELS OF INFECTION AND TRANSMISSION TO LINK BIOLOGY, EPIDEMIOLOGY AND PUBLIC HEALTH POLICY

Infectious diseases constitute a significant burden on the health of the population. Understanding how best to control them requires a multi..

Simulating social networks to understand how neighbourhood factors influence health

Where you live and who you know has implications for your health. This study will use social network models to understand how social charact..

Grants

Awarded by ARC DECRA

Awarded by ARC Future Fellowship

Awarded by Australian Government NHMRC Career Development Award

Funding Acknowledgements

A.J.B. was supported by an ARC DECRA (DE160100690). J.V.R. was supported by an ARC Future Fellowship (FT130100254). A.J.B. and J.V.R. were also supported by the ARC Centre of Excellence for Mathematical and Statistical Frontiers (CoE ACEMS). N.G. was supported by an ARC DECRA (DE130100660). J.M.M. was supported by an ARC Future Fellowship (FT110100250). J.M. was supported by a Australian Government NHMRC Career Development Award (CDF1061321). A.J.B., N.G., J.M., J.M.M. and J.V.R. were supported by the Australian Government NHMRC Centre for Research Excellencein Policy Relevant Infectious diseases Simulation and Mathematical Modelling (CRE PRISM2).