SIR Model Parameters Estimation with COVID-19 Data
Nilson C. Roberty *
Nuclear Engineering Program, Coppe, Universidade Federal do Rio de Janeiro, Av. Horocio Macedo, 2030, Bloco G, Sala 206, Centro de Tecnologia, Cidade Universitaria, Ilha do Fund}ao, 21941-914, Rio de Janeiro, RJ, Brasil.
Lucas S. F. de Araujo
Nuclear Engineering Department, Poli, Universidade Federal do Rio de Janeiro, Av. Horocio Macedo, 2030, Bloco G, Sala 206, Centro de Tecnologia, Cidade Universitaria, Ilha do Fund}ao, 21941-914, Rio de Janeiro, RJ, Brasil.
*Author to whom correspondence should be addressed.
Abstract
Based on the SIR model that divides the population into susceptible, infected and removed individuals, data about the evolution of the pandemic compiled by the Johns Hopkins University Center for Systems Science and Engineering (JHUCSSE) are integrated into the numerical system solution. The system parameters Rate of Contact β, Basic Reproduction Number R0 and Removal Rate γ, also named Rate of Decay, are determined according to a ridge regression approach and a mobile statistical scheme with different averages. Data is automatically downloaded from https://raw.githubusercontent.com/CSSEGISandData/COVID-19. The main Python libraries used are Numpy, Pandas, Skit-Learn, Requests and Urllib.
Keywords: COVID-19, Python3, Inverse Problems, Ridge Regression, ODE, Fixed Points