Jump to navigation
A household-level model of malaria transmission is developed to understand the role of reactive case detection in malaria elimination in diverse transmission settings.
We present a universal, data-driven decomposition of chaos as an intermittently forced linear system.
Containing the recent West African outbreak of Ebola virus (EBOV) required the deployment of substantial global resources.
We propose an alternative data-driven method to infer networked nonlinear dynamical systems by using sparsity-promoting optimization to select a subset of nonlinear interactions representing dynam