https://doi.org/10.1140/epjp/s13360-024-05327-4
Regular Article
Assessing the influence of public behavior and governmental action on disease dynamics: a PRCC analysis and optimal control approach
1
Department of Mathematics, Indian Institute of Engineering Science and Technology, Shibpur, 711103, Howrah, India
2
MS2Discovery Interdisciplinary Research Institute, Wilfrid Laurier University, Waterloo, Canada
Received:
18
April
2024
Accepted:
30
May
2024
Published online:
15
June
2024
A compartmental SIRIS epidemiological system containing two separate susceptible compartments (depending on immunity power) has been assessed in the present work involving governmental action, public reaction and social behavioral dynamics. In addition, the impact of environmental perturbations as well as time-dependent control techniques have been investigated. Present study analyzes that a few previously infectious individuals become susceptible to infection again after they have recovered, some infected persons build immunity after infection and some previously diseased populations become contaminated again after having recovered. More particularly, this study demonstrates the significance of social and governmental interventions on disease dynamics, along with the relevance of nonlinear dynamical modeling of epidemiological systems. As indicated by numerical simulation, the activities of government, social behavior act an essential role in preventing a pandemic scenario and if government takes action at incipient phases during an outbreak, the system becomes infection-free much sooner. Sensitivity analysis is used to assess how changes in different parameters of a model affect the spread of a disease. In this case, Latin hypercube sampling is used to perform both uncertainty and sensitivity analyses on input parameters. This sampling method helps to observe how these parameters impact the reproduction number of the disease. After that, Kendall’s tau and Spearman’s rank correlation coefficients are calculated to delve deeper into how these uncertainties affect the dynamics of the disease. Moreover, it is remarkable that random variations might inhibit the propagation of ailment, that can contribute in emergence of beneficial control strategies to govern the dynamics of disease. In this model, the policies implemented by government and pharmaceutical therapy are regarded as most adequate control pair, and it is determined that simultaneous execution of control mechanisms considerably diminishes the ailment burden.
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© The Author(s), under exclusive licence to Società Italiana di Fisica and Springer-Verlag GmbH Germany, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
