A Coupled Spatial-Network Model: A Mathematical Framework for Applications in Epidemiology.

There is extensive evidence that network structure (e.g., air transport, rivers, or roads) may significantly enhance the spread of epidemics into the surrounding geographical area.

Intraindividual variability over time of thrombin generation in patients with cirrhosis.

Background: Patients with cirrhosis are at high risk of thrombotic events, including portal vein thrombosis and venous thromboembolism. In such patients, hypercoagulability is not detected by conventional coagulation tests, but only by the thrombin generation assay (TGA) that integrates the role of pro- and anticoagulant factors. However, TGA use to predict clinical events depends on thrombin generation variability over time.

A Mean-Field Approximation of SIR Epidemics on an Erdös-Rényi Network Model.

The stochastic nature of epidemic dynamics on a network makes their direct study very challenging. One avenue to reduce the complexity is a mean-field approximation (or mean-field equation) of the dynamics; however, the classic mean-field equation has been shown to perform sub-optimally in many applications. Here, we adapt a recently developed mean-field equation for SIR epidemics on a network in continuous time to the discrete time case.

Heatmap centrality: A new measure to identify super-spreader nodes in scale-free networks.

The identification of potential super-spreader nodes within a network is a critical part of the study and analysis of real-world networks. Motivated by a new interpretation of the "shortest path" between two nodes, this paper explores the properties of the heatmap centrality by comparing the farness of a node with the average sum of farness of its adjacent nodes in order to identify influential nodes within the network. As many real-world networks are often claimed to be scale-free, numerical experiments based upon both simulated and real-world undirected and unweighted scale-free networks are used to illustrate the effectiveness of the proposed "shortest path" based measure with regards to its CPU run time and ranking of influential nodes.