Modelling: Understanding pandemics and how to control them

Epidemics

Valerie Isham¹  Daniel Villela²  Liza Hadley³  Pieter Trapman⁴  Francesca Scarabel⁵  Glenn Marion⁶  Lorenzo Pellis⁷  Ben Swallow⁸  Jasmina Panovska-Griffiths⁹  Denis Mollison^1,10  Gianpaolo Scalia Tomba^1,11 

[1] Correspondence to: Biomathematics and Statistics Scotland, James Clerk Maxwell Building, The King's Buildings, Peter Guthrie Tait Road, Edinburgh, EH9 3FD, UK.;Joint UNIversities Pandemic and Epidemiological Research, UK;Scottish COVID-19 Response Consortium, UK;The Alan Turing Institute, London, UK;The Queen's College, Oxford University, UK;Biomathematics and Statistics Scotland, Edinburgh, UK;Department of Actuarial Mathematics and Statistics, Heriot-Watt University, UK;Department of Mathematics, University of Manchester, UK;Department of Statistical Science, University College London, UK;Disease Dynamics Unit, Department of Veterinary Medicine, University of Cambridge, UK;The Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK;

关键词: Infectious disease models;    Behaviour and multi-scale transmission dynamics;    Within, host dynamics;    Pathogen dynamics;    Value of information studies;   

DOI  :  

来源: DOAJ

【 摘 要 】

New disease challenges, societal demands and better or novel types of data, drive innovations in the structure, formulation and analysis of epidemic models. Innovations in modelling can lead to new insights into epidemic processes and better use of available data, yielding improved disease control and stimulating collection of better data and new data types. Here we identify key challenges for the structure, formulation, analysis and use of mathematical models of pathogen transmission relevant to current and future pandemics.

【 授权许可】

Unknown