Visualizing the Covid-19 pandemic with doubling rates

covid by Bosny

As the popularity of coronavirus data visualizations increases, so does the risk of misinterpreting results. We’ve all heard the term flattening the curve. This catch phrase does a good job of summarizing the goal of pandemic mitigation policies: limit the number of people who are simultaneously infected to avoid straining health care systems. However common the phrase may be, it raises the question: What curve are we trying to flatten? And what do these curves tell us about how well we’re doing?

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A long tradition: Discussion meetings at the Royal Statistical Society

RSS discussion meeting

Discussion meetings are the most prestigious of the many types of meetings organised by the Royal Statistical Society (RSS) where researchers can present their work. They have built up a long tradition, and many of the most important ideas in statistics were first presented and discussed at these meetings. Paul A. Smith, the current discussion papers editor, explains.

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Covid-19 through the lens of the peer-reviewed literature: January to May 2020

Tower of books, Prague

As medical students and budding clinical academics, we have been following developments through the current coronavirus pandemic with interest. We are quite bewildered by the vast amount of data being shared via social media as well as more ‘traditional’ routes such as mainstream media and peer-reviewed journals. This surge in information (of highly variable quality) has been described by the World Health Organization (WHO) as an “infodemic” and has necessitated a “myth busters” section on their website to address the spread of misinformation.

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Robust Bayesian modelling for Covid-19 data in Italy

Italy social distancing poster

On 21 February 2020, the first person-to-person transmission of SARS-CoV-2 – the virus responsible for Covid-19 – was reported in Italy. After that, the number of people infected with Covid-19 increased rapidly, first in northern regions and then in all Italian territories.

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