Unravelling the web of tuberculosis: Mathematical models to decode and defeat tuberculosis transmission complexity

Abstract

In the transmission of infectious illnesses like tuberculosis, mathematical models are crucial in public health. The fundamental paradigm is compartmental modelling, which classifies people into categories such as susceptible, latent, active, and recovered. Extensions and variations in this model can be utilized to capture intricate details. To research TB transmission dynamics, structural models including age-structured, agent-based, stochastic, SEIR, spatial, drug-resistant, vaccination, contact tracking, and treatment models are employed. Populations are divided into age groups by age-structured models, intricate interactions are shown by agent-based models, disease outbreaks are simulated by stochastic models, social networks are considered by SEIR models, and treatment success rates are considered by treatment models. Real-world mathematical simulations of TB transmission in public health settings offer useful tools for comprehending TB dynamics, making decisions, allocating resources, and assisting in the reduction and eradication of tuberculosis.