Open AccessA Nonlinear Observer to Estimate the Effective Reproduction Number of Infectious Diseases
Author(s) -
Agus Hasan
Publication year - 2021
Publication title -
communication in biomathematical sciences
Language(s) - English
Resource type - Journals
ISSN - 2549-2896
DOI - 10.5614/cbms.2021.4.1.4
Subject(s) - observer (physics) , control theory (sociology) , nonlinear system , covid-19 , extended kalman filter , kalman filter , pandemic , linear matrix inequality , mathematics , alpha beta filter , computer science , statistics , medicine , mathematical optimization , infectious disease (medical specialty) , artificial intelligence , moving horizon estimation , physics , control (management) , disease , quantum mechanics
In this paper, we design a Nonlinear Observer (NLO) to estimate the effective reproduction number (Rt) of infectious diseases. The NLO is designed from a discrete-time augmented Susceptible-Infectious-Removed (SIR) model. The observer gain is obtained by solving a Linear Matrix Inequality (LMI). The method is used to estimate Rt in Jakarta using epidemiological data during COVID-19 pandemic. If the observer gain is tuned properly, this approach produces similar result compared to existing approach such as Extended Kalman filter (EKF).