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by scoot 1511 days ago
That seems more like a truism: If on average one case leads to more than one other (R > 1), the number of cases will grow. The R number therefore appears to be nothing more than a measure of growth or decline. What am I missing?
4 comments

As far as I understand it R is not a rate because it does not include time. Diseases that take on average a few days for you to pass on verses a few months will have different growth rates. For example, an STI might have an R factor of 3, but the rate is completely dependent on how often people have unprotected sex.
Good point, R is often referred to as a rate both in media and academic publications, but "number" or "value" appears to be more correct. Fixed.
R is not a measure of anything (i.e. real world data), it's more of a prediction based on a mathematical modeling procedure. It's not constant for a pathogen like Sars-CoV2, as it depends also on other conditions (environmental factors like temp/humidity, and social factors (norms like handshaking, etc.).

The models used to generate R-numbers have some assumptions which may or may not be valid: (1) rectangular and stationary age distribution, and (2) homogeneous mixing of the population. Thus, the result is a fairly rough estimate.

A major use is in getting a decent estimate of what percentage of a population needs to be vaccinated in order to halt the spread of a viral infection. However, this supposes 'sterilizing vaccination', i.e. vaccinated individuals are not asymptomatic carriers and spreaders of the infection. While this was the case for the smallpox vaccine, it doesn't seem to be the case with all known Covid19 vaccines, where there are many breakthrough cases (even though symptoms are reduced and hospitalization is minimal).

This is essentially what is happening in the percolation case as well.
What I mean is that R varies by disease (or for a given disease, according to interventions, etc).

The size of the total epidemic varies sharply as R is changed in this way.