Jump to navigation
The eradication of diseases has long been a focus of the global health community and researchers in epidemiology and other related fields.
Decision makers need efficient algorithms to draw meaningful conclusions from detailed stochastic simulations with respect to a goal-oriented objective.
Understanding the environmental conditions of disease transmission is important in the study of vector-borne diseases.
This work develops compressive sampling strategies for computing the dynamic mode decomposition (DMD) from heavily subs
Contact rates tend to increase with density but saturate at higher density.
Stochastic simulations of reaction-diffusion processes are frequently used for modelling epidemiological processes.