Stochastic method to control Mycobacterium tuberculosis epidemic. (August 2020) - Mandal, Saurav; Singh, Shakti Nath; Malik, Md. Zubbair; Singh, R.K. Brojen
Graphical abstract: Highlights: We propose that any TB epidemic may have high chance of periodic recurrence and can be controlled by optimizing parameters. We studied SNP distributions of experimentally identified drug resistance genes. We try to study sequence evolution of these genes. We found emergence of random clusters driven by demographic stochasticity. We observe development of time reversal oscillation after threshold value of stress signal. Multifractal analysis indicate that TB epidemic is caused by contact communication. Abstract: We study the origin of TB (tuberculosis) epidemic and complex distributions of various populations of TB infection within the stochastic framework. The stochastic nature of this disease infection could be linked to the stochastic behaviour at genome level which is exhibited in SNP (single nucleotide polymorphism) distributions of experimentally identified hotspot driver genes. Our results show the emergence of random clusters, and well-defined discrete domains of the respective species populations in the model driven by demographic stochasticity and intrinsic complex species interaction. The multifractal analysis of the time series of the species populations indicate that TB epidemic could be mainly caused by contact communication and is directional. We propose that any TB epidemic may have high chance of approximately periodic recurrence and can be controlled by optimizing some of the parameters involved in the system modelling.