COVID 19: Forecast of the diffusion by Gurumurthy Kalyanaram
Covid-19 pandemic has devastated economies and societies. Forecasting the diffusion of the virus has been challenging. Over the last four months, several empirical models have been built. We present them here in very abbreviated manner. Then I discuss my own forecasts for the United States. Those forecasts changed substantially over time with new data and assumptions.
Empirical Models SEIR Theory
This is the basic epidemiological theory/framework. Here, the population is described to be in one of four stochastic states: Susceptible, Exposed, Infectious and Recovered (looping back to Susceptible state). Assume S is the fraction of susceptible individuals (those able to contract the disease), E is the fraction of exposed individuals (those who have been infected but are not yet infectious), I is the fraction of infective individuals (those capable of transmitting the disease), and R is the fraction of recovered individuals (those who have become immune). We then have