TY - GEN
T1 - Estimating SIR model parameters from data using differential evolution
T2 - 2020 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2020
AU - Rica, Sergio
AU - Ruz, Gonzalo A.
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/10/27
Y1 - 2020/10/27
N2 - The problem of fitting parameters of a dynamical system appears to be relevant in many areas of knowledge, like weather forecasting, system biology, epidemiology, and financial markets. In this paper, we analyze the Susceptible-Infected-Recovered (SIR) epidemiological model. We first derive an alternative representation of the SIR model, reducing it to one differential equation that models the cumulative number of infected cases in function of time. Then we present a differential evolution approach to estimate the parameters of this dynamical model from data. We illustrate the proposed approach with COVID-19 data from Santiago, Chile. The goodness of fit, obtained by the differential evolution algorithm outperformed ten times the results obtained by a random search strategy used in previous works.
AB - The problem of fitting parameters of a dynamical system appears to be relevant in many areas of knowledge, like weather forecasting, system biology, epidemiology, and financial markets. In this paper, we analyze the Susceptible-Infected-Recovered (SIR) epidemiological model. We first derive an alternative representation of the SIR model, reducing it to one differential equation that models the cumulative number of infected cases in function of time. Then we present a differential evolution approach to estimate the parameters of this dynamical model from data. We illustrate the proposed approach with COVID-19 data from Santiago, Chile. The goodness of fit, obtained by the differential evolution algorithm outperformed ten times the results obtained by a random search strategy used in previous works.
KW - COVID-19 data
KW - Differential Evolution
KW - Dynamical System
KW - SIR model
UR - http://www.scopus.com/inward/record.url?scp=85099069707&partnerID=8YFLogxK
U2 - 10.1109/CIBCB48159.2020.9277708
DO - 10.1109/CIBCB48159.2020.9277708
M3 - Conference contribution
AN - SCOPUS:85099069707
T3 - 2020 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2020
BT - 2020 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2020
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 27 October 2020 through 29 October 2020
ER -