Cybersecurity risks evolve rapidly, and are everywhere.
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Cybersecurity risks are evolving rapidly. How can they be more effectively assessed and managed ?
The risk of transmitting COVID-19 is much higher indoors due to proximity to other people and building ventilation systems.
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Studying how SARS-CoV-2, the virus that causes COVID-19, travels through indoor air spaces can help reduce transmission risk.
Sandra Lindsay, a nurse at Long Island Jewish Medical Center, is given the COVID-19 vaccine – she is one of the first in the US to receive it.
EPA/Mark Lennihan
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.
A melanoma, a malignant tumor of the pigmentary system of the skin, magnified 40 times.
J Wisell
To better understand how cancer tumors grow, mathematicians use diffusion models.
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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.
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The R number fluctuates more as case numbers fall.
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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.
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The UK locked down too late and has been in catch-up mode ever since. But with contact tracing, it can turn things around.
President Ramaphosa’s government is easing the lockdown because of unsustainable economic costs.
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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.
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Neuroscientist Karl Friston claims generative modelling techniques produce more valid predictions than conventional models, but the evidence so far is limited.
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An easy question, but a difficult answer.
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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.
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May 7, 2020
Robert (Bob) Scholes , University of the Witwatersrand ; Albertus J. Smit , University of the Western Cape ; Francois Alwyn Engelbrecht , University of the Witwatersrand ; Guy Franklin Midgley , Stellenbosch University ; Jennifer Fitchett , University of the Witwatersrand ; Neville Sweijd , Applied Centre for Climate and Earth Systems Science ; Pedro M.S. Monteiro , Council for Scientific and Industrial Research , and Pravesh Debba , Council for Scientific and Industrial Research
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.
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One practical exit strategy from lockdown would be identifying green zones, and progressively joining them together once it is safe to do so.
Chief Public Health Officer Theresa Tam and Deputy Chief Public Health Officer Howard Njoo are reflected in a computer screen showing data on Canada’s COVID-19 situation during a news conference in Ottawa, on April 13, 2020.
THE CANADIAN PRESS/Adrian Wyld
Policy-makers at various levels of government rely on models and simulations to make predictions about controlling the spread of COVID-19.
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Scientific models can help us understand the important features of complex systems, but they need good data.
Have most of us already had it?
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Study raises hopes that we may be closer to herd immunity than previously thought.
Staff members of Local NGO Shining Hope for Communities (SHOFCO) in the Kibera slum, Nairobi, on March 20, 2020.
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Models can predict the risk and spread of diseases and establish the time and place to implement optimal prevention and control mechanisms.
Mitigating the effects of future pandemics will require sound and efficient predictions.
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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.
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Strict quarantine measures have been shown to be more effective in reducing the spread of COVID-19 than closing schools.