https://doi.org/10.1140/epjs/s11734-021-00335-2
Regular Article
A revisit to the past plague epidemic (India) versus the present COVID-19 pandemic: fractional-order chaotic models and fuzzy logic control
1
Department of Electrical Engineering, Tezpur University, 784028, Tezpur, India
2
Department of Electrical Engineering, NIT Silchar, 788010, Silchar, India
3
Division of Dynamics, Lodz University of Technology, Stefanowskiego 1/15, 90-924, Lodz, Poland
4
Center for Nonlinear Systems, Chennai Institute of Technology, Chennai, India
5
Laboratory of Nonlinear Systems-Circuits and Complexity, Physics Department, Aristotle University of Thessaloniki, 54124, Thessaloniki, Greece
Received:
30
June
2021
Accepted:
30
October
2021
Published online:
12
December
2021
India is one of the worst hit regions by the second wave of COVID-19 pandemic and ‘Black fungus’ epidemic. This paper revisits the Bombay Plague epidemic of India and presents six fractional-order models (FOMs) of the epidemic based on observational data. The models reveal chaotic dispersion and interactive coupling between multiple species of rodents. Suitable controllers based on fuzzy logic concept are designed to stabilise chaos to an infection-free equilibrium as well as to synchronise a chaotic trajectory with a regular non-chaotic one so that the unpredictability dies out. An FOM of COVID-19 is also proposed that displays chaotic propagation similar to the plague models. The index of memory and heredity that characterise FOMs are found to be crucial parameters in understanding the progression of the epidemics, capture the behaviour of transmission more accurately and reveal enriched complex dynamics of periodic to chaotic evolution, which otherwise remain unobserved in the integral models. The theoretical analyses successfully validated by numerical simulations signify that the results of the past Plague epidemic can be a pathway to identify infected regions with the closest scenarios for the present second wave of Covid-19, forecast the course of the outbreak, and adopt necessary control measures to eliminate chaotic transmission of the pandemic.
© The Author(s), under exclusive licence to EDP Sciences, Springer-Verlag GmbH Germany, part of Springer Nature 2021