TY - JOUR
T1 - Calibrating COVID-19 susceptible-exposed-infected-removed models with time-varying effective contact rates
AU - Gleeson, James P.
AU - Brendan Murphy, Thomas
AU - O'Brien, Joseph D.
AU - Friel, Nial
AU - Bargary, Norma
AU - O'Sullivan, David J.P.
N1 - Publisher Copyright:
© 2021 The Authors.
PY - 2022
Y1 - 2022
N2 - We describe the population-based susceptible-exposed-infected-removed (SEIR) model developed by the Irish Epidemiological Modelling Advisory Group (IEMAG), which advises the Irish government on COVID-19 responses. The model assumes a time-varying effective contact rate (equivalently, a time-varying reproduction number) to model the effect of non-pharmaceutical interventions. A crucial technical challenge in applying such models is their accurate calibration to observed data, e.g. to the daily number of confirmed new cases, as the history of the disease strongly affects predictions of future scenarios. We demonstrate an approach based on inversion of the SEIR equations in conjunction with statistical modelling and spline-fitting of the data to produce a robust methodology for calibration of a wide class of models of this type. This article is part of the theme issue 'Data science approaches to infectious disease surveillance'.
AB - We describe the population-based susceptible-exposed-infected-removed (SEIR) model developed by the Irish Epidemiological Modelling Advisory Group (IEMAG), which advises the Irish government on COVID-19 responses. The model assumes a time-varying effective contact rate (equivalently, a time-varying reproduction number) to model the effect of non-pharmaceutical interventions. A crucial technical challenge in applying such models is their accurate calibration to observed data, e.g. to the daily number of confirmed new cases, as the history of the disease strongly affects predictions of future scenarios. We demonstrate an approach based on inversion of the SEIR equations in conjunction with statistical modelling and spline-fitting of the data to produce a robust methodology for calibration of a wide class of models of this type. This article is part of the theme issue 'Data science approaches to infectious disease surveillance'.
KW - calibration
KW - differential equations
KW - epidemic modelling
KW - generalized additive model
KW - thin-plate splines
UR - http://www.scopus.com/inward/record.url?scp=85122312827&partnerID=8YFLogxK
U2 - 10.1098/rsta.2021.0120
DO - 10.1098/rsta.2021.0120
M3 - Article
AN - SCOPUS:85122312827
SN - 1364-503X
VL - 380
JO - Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
JF - Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
IS - 2214
M1 - 20210120
ER -