Parameter estimation of tuberculosis transmission model using Ensemble Kalman filter across Indian states and union territories

A Heterogeneous Ensemble Forecasting Model for Disease Prediction

“…The simulations were performed for tracking the spatio-temporal patterns of emerging epidemics. The parameter estimation of TB, a prime cause of mortality across the globe, is undertaken by authors in [ 24 ]. Here, the authors employed the EnKF (ensemble Kalman filter) approach to estimate the smear-positive cases in India for the period 2006–2011.…”

Short-term forecasts of the COVID-19 pandemic: a study case of Cameroon

“…Thus, the COVID-19 transmission rates β h and β v are the unknown parameters in model system (3) . As in Refs [29] , [54] ., the unknown parameters can be written into a simple state space model following a Markov process as where β t is the uncertainty at time t given by a Gaussian white noise in with standard deviations T t . One can interpret η t as the behavior change that makes contacts grow or fall beyond a certain limit 0 and 1.…”

“…Finally, we simulate the model system (3) using the Runge Kutta method. Since each variable of (3) follows a Markov process [28] , [29] , we use the following discrete model: where w t is the incertitude at time t of the discretization (error) that is assumed to be a white noise process with the covariance matrix Q t that appreciates the estimation of the exact value of the state variables x ( t ) at time t [28] , f ( x t , β t ) is the approximated value of given by the discrete model obtained by discretizing (3) using the Runge Kutta method.…”

“…With the complexity of many phenomena, estimating of both states and parameters for dynamical systems are of high interest. EnKf has dealt with this interrogation [28] , [29] .…”

Optimal control problem for a tuberculosis model with multiple infectious compartments and time delays

“…Using a basic SEI model with saturated incidence rate, Baba et al [34] studied the effect of optimal controller and awareness. It is noted that a considerable number of studies that deal with TB modelling use the basic SEI or SEIR model with only a single compartment of infectious people (see [35][36][37][38][39][40][41]). However, considering a single infectious compartment is no longer convenient, as it fails to take into account that some infected individuals can be detected and treated whereas others remain undetected and untreated.…”