A contact-network-based simulation model for evaluating interventions under "what-if" scenarios in epidemic

Authors:
Tianyou Zhang;Michael Lees;Chee Keong Kwoh;Xuju Fu;Gary Kee Khoon Lee;Rick Siow Mong Goh
Affiliations:
Institute of High Performance Computing, Singapore;Nanyang Technological University, Singapore;Nanyang Technological University, Singapore;Institute of High Performance Computing, Singapore;Institute of High Performance Computing, Singapore;Institute of High Performance Computing, Singapore
Venue:
Proceedings of the Winter Simulation Conference
Year:
2012

Citing 3
Cited 0

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

Proceedings of the 2008 ACM/IEEE conference on Supercomputing
Simulation of scale-free networks

Proceedings of the 2nd International Conference on Simulation Tools and Techniques
EpiFast: a fast algorithm for large scale realistic epidemic simulations on distributed memory systems

Proceedings of the 23rd international conference on Supercomputing

Quantified Score

Hi-index	0.00

Visualization

Abstract

Infectious disease pandemics/epidemics have been serious concerns worldwide. Simulations for public health interventions are practically helpful in assisting policy makers to make wise decisions to control and mitigate the spread of infectious diseases. In this paper, we present our contact network based simulation model, which is designed to accommodate various "what-if" scenarios under single and combined interventions. With the incorporation of parallel computing and optimization techniques, our model is able to reflect the dynamics of disease spread in a realistic social contact network based on Singapore city, simulating combined intervention strategies as well as control effect at different levels of a social component. The framework of our model and experimental results show that it is a useful tool for epidemiological study and public health policy planning.