11 citations · 35 across the 21 of their papers we have counts for
6 papers · 1 filter
Likelihood-Free Dynamical Survival Analysis Applied to the COVID-19 Epidemic in Ohio
Colin Klaus, Matthew Wascher, Wasiur R. KhudaBukhsh +1
The Dynamical Survival Analysis (DSA) is a framework for modeling epidemics based on mean field dynamics applied to individual (agent) level history of infection and recovery. Rece…
Dynamic Survival Analysis for non-Markovian Epidemic Models
Francesco Di Lauro, Wasiur R. KhudaBukhsh, Istvan Z. Kiss +3
We present a new method for analyzing stochastic epidemic models under minimal assumptions. The method, dubbed DSA, is based on a simple yet powerful observation, namely that popul…
Incorporating age and delay into models for biophysical systems
Wasiur R. KhudaBukhsh, Hye-Won Kang, Eben Kenah +1
In many biological systems, chemical reactions or changes in a physical state are assumed to occur instantaneously. For describing the dynamics of those systems, Markov models that…
Survival Dynamical Systems for the Population-level Analysis of Epidemics
Wasiur R. KhudaBukhsh, Boseung Choi, Eben Kenah +1
Motivated by the classical Susceptible-Infected-Recovered (SIR) epidemic models proposed by Kermack and Mckendrick, we consider a class of stochastic compartmental dynamical system…
The large graph limit of a stochastic epidemic model on a dynamic multilayer network
Karly A. Jacobsen, Mark G. Burch, Joseph H. Tien +1
We consider an SIR-type (Susceptible Infected Recovered) stochastic epidemic process with multiple modes of transmission on a contact network. The network is given by a…
Network-Based Analysis of a Small Ebola Outbreak
Mark G. Burch, Karly A. Jacobsen, Joseph H. Tien +1
We present a method for estimating epidemic parameters in network-based stochastic epidemic models when the total number of infections is assumed to be small. We illustrate the met…