Infected cases forecast model:
SIR (Susceptible-Infective-Recovered) model is used to forecast the number of infected cases, and the peak time.
A model of reactive social distancing in epidemics is proposed, in which the infection rate changes with the number infected. The final-size equation for the total number that the epidemic will infect can be derived analytically, as can the peak infection proportion. This model could assist planners during for example the COVID-19 pandemic.
The following graphs illustrate the infection case numbers are given in proportions to populations. Please note the days are from the day after the confirmed 100th case. They show the best possible forecasts and the average as well as the estimated peak date and the maximum infection proportion.
We updated forecasts for New York and for all US other than New York. The peak day shows for New York as mid April and for the other places are expected to be lagging 2-3 weeks. Latest forecasts are below; please note that these are not total numbers that we expect to see when the epidemic is over. We expect to have total confirmed cases is about 4.760.000 and total fatality is about 95.600. These numbers are close to recently published White House projections.
We use ideas from adsabs.harvard.edu, check them out: here