Disease Modeling, R Naught, Fallacies
We’re taught that r naught, the value indicating spread potential of a disease. The two variables representing population size and transmissibility, make a general model for spread potential. However, disease modeling is much more complex than this in the real world, and this calculation isn’t complex or robust enough to capture the full picture of a disease. It assumes that the population is equally susceptible, that there is no variability in infectiousness, ignores contextual factors, not account for immunity, and oversimplifies disease dynamics. Moreover, it is a static measurement and does not change in response to the evolving dynamics of an outbreak, such as changes in population behavior, public health interventions, or seasonal effects.
I think it’s a good general introduction to disease modeling, but isn’t robust enough to capture all disease out there and all populations out there. It’s important to keep this into account when using this formula.
The failure of r naught: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3157160/