SARS-Cov-2 aka Covid-19, the virus behind the current pandemic continues to be a nightmare for everybody - especially for statisticians.
It was bad enough to have the Chinese obfuscating the truth about the original 'Wuhan virus' last year, but now we have a range of mutants (and double-mutants) that seem to be spreading in ways that are difficult to predict. This is is making the work of those who prepare statistical models much more difficult, and this in turn is affecting the quality of decisions being taken by policymakers.
Take for instance, the reproductive-value or R-Value for Covid-19. R is the number of people that one infected person will pass on a virus.
The lowest possible R-Value is R-naught or R0. Also referred to as the Basic Reproduction Number, it is the R-value of a population that is assumed to have zero immunity against a new infection. R0 is the division of the number of new infections by the number of existing infections, or the average number of new infections over an infectious period (R0= new infections/existing infections).
Measles has an R number of 15 in populations without immunity. It means that, on average, every 10 people with Measles will infect 15 other people. For Covid-19, the latest R-value estimate for India, is around 1.30. This number is showing wide variations across states with Uttar Pradesh recording the highest infection value at 1.62, followed by Andhra Pradesh at 1.61.
The problem with the R-Value is that it gives us a picture of the past - by the time you calculate it, the number is already outdated. This is because it is based on data recorded on hospitalisations and death figures to get a sense of how many people have the virus – but the problem with this is that, since the virus’s incubation period is so long, it only gives an accurate picture of a few weeks ago.
Add to this the complications coming from recent mutations of the virus in different parts of the world, each with its own incubation period - the "UK" B.1.1.7; the "South Africa" B.1.351; "Brazil" P1, "India" variants B.1.36 (Bangalore) / B.1.1.7 (Punjab) and B.1.617 which contains two specific mutations - E484Q and L452R which is capable of 'immune escape', and infecting those who have already been vaccinated.
Add to all this other newer emerging variants of concern (VoCs) and we have all ingredients for a statisticians' perfect nightmare.
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LINKS & REFERENCES
* https://www.bbc.com/news/health-52473523
* https://www.weforum.org/agenda/2020/05/covid-19-what-is-the-r-number/
* https://www.statista.com/statistics/1101713/india-covid-19-cases-by-type/
* R0 Explained - https://indianexpress.com/article/explained/coronavirus-r0-reproduction-number-explained-6354339/
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