Epidemiologists assured us S-shaped curves would be the case for COVID-19, but many countries had decreases of infection numbers "social distancing" and a linear rise of infection curves after the first peak.
A new paper offers an explanation for the linear growth of the infection curve.
Traditional epidemiological models required so much fine-tuning of parameters that they became scientifically meaningless. Linear growth, with an R number at 1, in the epidemiology models that were being used would have to mean reducing contacts by the same exact and constant percentage. That was never going to happen outside the world of statistical hope.