학술논문

Parameter identifiability and optimal control of an SARS-CoV-2 model early in the pandemic
Document Type
article
Source
Journal of Biological Dynamics, Vol 16, Iss 1, Pp 412-438 (2022)
Subject
Practical and structural identifiability
Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2)
Coronavirus disease 2019 (COVID-19)
outbreak
epidemic model
mass-action incidence
Environmental sciences
GE1-350
Biology (General)
QH301-705.5
Language
English
ISSN
17513758
1751-3766
1751-3758
Abstract
We fit an SARS-CoV-2 model to US data of COVID-19 cases and deaths. We conclude that the model is not structurally identifiable. We make the model identifiable by prefixing some of the parameters from external information. Practical identifiability of the model through Monte Carlo simulations reveals that two of the parameters may not be practically identifiable. With thus identified parameters, we set up an optimal control problem with social distancing and isolation as control variables. We investigate two scenarios: the controls are applied for the entire duration and the controls are applied only for the period of time. Our results show that if the controls are applied early in the epidemic, the reduction in the infected classes is at least an order of magnitude higher compared to when controls are applied with 2-week delay. Further, removing the controls before the pandemic ends leads to rebound of the infected classes.