## Understanding Pandemic Statistics

Real examples help to better understand how to interpret the statistics.

False Positive Paradox: A particular medical test for a disease is 96% accurate. If one has the disease, the test comes back ‘Yes’ 96% of the time, and if one does not have the disease, the test comes back ‘Yes’ 4% of the time.

If  100  of 10000 tested patients have the disease, what is the probability that the person with the diagnosis ‘Yes’ has the disease?

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Effective Average Infection Ratio: R is the effective average infection ratio for a disease, also known as the reproduction number. It is the average number of secondary infections caused by one person. (Infections caused by the secondary infections – which would be tertiary infections – are not counted). Consider 50 infected people. Suppose 49 spread the infection to nobody, but one person spreads the infection to 60 people.

What is the R-value?

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Leslie Green asks: How would you propose to deal with the COVID-19 pandemic, given information current at the time of writing (11 October 2020).

A. Severe lockdown for 4 weeks

B. Ignore it and carry on as normal

C. Partial lockdown and wait for a vaccine

D. Some other idea

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The Pfizer COVID-19 vaccine-candidate interim results from 8 Nov 2020 showed 38,955 participants in a placebo controlled double-blind trial.
94 participants  became “evaluable”, which we presume to mean they showed COVID-19 symptoms. The analysis presented was that the vaccine efficacy rate was above 90%. What is the maximum number of (genuinely) vaccinated people who showed COVID-19 symptoms?

Variability Analysis on COVID-19 Interim Trial Data by Leslie Green

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Is there any rational justification for being wary of vaccines?