Mathematical Biology

Uncertainty Quantification in Complex Models of Complicated Biology Validated mathematical models of complex biological phenomena are increasingly recognized as invaluable for elucidating mechanisms that underlie real-world (experimental or clinical) observations. Agent-based models (ABMs) have emerged as a natural formulation of choice in such models, providing a logical structure for capturing the multiple time and spatial

Reproducible Stochastic Simulation Stochastic simulations are commonly used to quantitatively or semi-quantitatively describe the dynamics of biological systems. At various scales and in multiple applications, stochastic simulation better reflects observed biological processes and robustness. Various methods are widely used to incorporate stochasticity into biological simulation, such as the Gillespie stochastic simulation algorithm for systems biology

Unveiling the Hidden Threat: The Impact of Sub-Optimum Treatment on Acquired Immunity, Asymptomatic Cases, Malaria Dynamics Malaria remains a persistent global health issue, despite ongoing control efforts such as anti-malarial drugs and insecticide-treated bed-nets, indoor residual spraying, etc.. The greatest impact of malaria, a mosquito-borne illness, is felt in Africa. This study develops a compartmental