Identification

Author

Christopher BL, Bisset KR, Eubank SG, Feng X, Marathe MV

Title

EpiSimdemics: An efficient algorithm for simulating the spread of infectious disease over large realistic social networks

Year

2008

Publication type

Conference

Journal

High Performance Computing, Networking, Storage and Analysis, 2008. SC 2008. International Conference for

Created

2014-04-07 22:22:59+00:00

Modified

2016-06-28 16:45:31.762772+00:00

Details

Pages

1-12

Access

Language

English

URL http://people.cs.vt.edu/badityap/classes/cs6604-Fall13/readings/bisset-episimdemics.pdf
DOI

10.1109/SC.2008.5214892

Accessed

2016-06-28

Extended information

Abstract

Preventing and controlling outbreaks of infectious diseases such as pandemic influenza is a top public health priority. We describe EpiSimdemics - a scalable parallel algorithm to simulate the spread of contagion in large, realistic social contact networks using individual-based models. EpiSimdemics is an interaction-based simulation of a certain class of stochastic reaction-diffusion processes. Straightforward simulations of such process do not scale well, limiting the use of individual-based models to very small populations. EpiSimdemics is specifically designed to scale to social networks with 100 million individuals. The scaling is obtained by exploiting the semantics of disease evolution and disease propagation in large networks. We evaluate an MPI-based parallel implementation of EpiSimdemics on a mid-sized HPC system, demonstrating that EpiSimdemics scales well. EpiSimdemics has been used in numerous sponsor defined case studies targeted at policy planning and course of action analysis, demonstrating the usefulness of EpiSimdemics in practical situations.