Cybersecurity risks are evolving rapidly. How can they be more effectively assessed and managed ?
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Articles sur Modelling
Affichage de 21 à 40 de 65 articles
Studying how SARS-CoV-2, the virus that causes COVID-19, travels through indoor air spaces can help reduce transmission risk.
Here’s what we still need to find out before we can know when we’ll be able to return to our pre-coronavirus ways.
To better understand how cancer tumors grow, mathematicians use diffusion models.
We’re on the road again. Getting enough COVID-19 vaccine to where it’s needed in a given time frame is the next logistical hurdle.
The R number fluctuates more as case numbers fall.
Many of the more formal models for predicting the pandemic try to understand why changes happen – but often it can be more accurate to ignore the reasons and simply look at the data.
The UK locked down too late and has been in catch-up mode ever since. But with contact tracing, it can turn things around.
The South African government and some of its advisors want to have the best of both worlds. They want to use incorrect predictions by early models about the COVID-19 pandemic to claim success.
Neuroscientist Karl Friston claims generative modelling techniques produce more valid predictions than conventional models, but the evidence so far is limited.
An easy question, but a difficult answer.
National models on the spread of COVID-19 have helped us through this crisis. But we’ll need local models to get us through the next stage.
The science to policy process that was developed to guide climate mitigation decisions can be applied to the response to the COVID-19 pandemic, without having to be reinvented.
One practical exit strategy from lockdown would be identifying green zones, and progressively joining them together once it is safe to do so.
Policy-makers at various levels of government rely on models and simulations to make predictions about controlling the spread of COVID-19.
Scientific models can help us understand the important features of complex systems, but they need good data.
Study raises hopes that we may be closer to herd immunity than previously thought.
Models can predict the risk and spread of diseases and establish the time and place to implement optimal prevention and control mechanisms.
Predicting how a virus will spread — and its effects — relies on mathematically sound and accurate models that account for factors like weather patterns and human behaviour.
Strict quarantine measures have been shown to be more effective in reducing the spread of COVID-19 than closing schools.
Les contributeurs les plus fréquents
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Lecturer in Probability and Statistics and Senior Research Fellow in Infectious Disease Modelling, University of Oxford
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Professor, Systems and Computer Engineering, Carleton University
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Honorary Enterprise Professor, School of Population and Global Health, and Department of General Practice and Primary Care, The University of Melbourne
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Deputy Director (Programs), Burnet Institute
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Professor, epidemiological modelling of infectious diseases, UNSW Sydney
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Professor of Biostatistics and Epidemiology, University of South Australia
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Professor of Infectious Disease and Epidemiology, James Cook University
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Econometrician, Burnet Institute
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CSIRO Research Group Leader Ecosystem Modelling and Risk Assessment, CSIRO
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Honorary Fellow, Marine and Atmospheric Research, CSIRO
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Associate Professor, Philosophy of Science, The University of Melbourne
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Director and CEO, Burnet Institute
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Associate Principal Research Fellow, Burnet Institute
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Research Fellow in Fisheries, UNSW Sydney
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Enterprise Professor in the School of Engineering, The University of Melbourne
