An Advanced Infectious Disease Spreading Model—SEICD and Its Simulation

DOI

10.2991/icecee-15.2015.269How to use a DOI?

Keywords

infectious disease spreading; SEICD model; graph theory; simulation

Abstract

Focus on describing the transmission of infectious disease, this paper mainly develop a new model--SEICD. The model is based on the classic infectious disease model called SEIR. In view of the characteristics of most infectious disease, we make a series of improvements in depth. By the improved model, we adapt graph theory to describe the complex relationships of the real society, simulate the population changing of different states in the model, and analyze the influence of the relative infectiousness k in the situation of infectious diseases spread. Considered all above, a best critical relative infectiousness kc to distinguish whether the regions under epidemic stress can be under control can be got.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Ming Xi Zhao
PY  - 2015/06
DA  - 2015/06
TI  - An Advanced Infectious Disease Spreading Model—SEICD and Its Simulation
BT  - Proceedings of the 2015 International Conference on Electrical, Computer Engineering and Electronics
PB  - Atlantis Press
SP  - 1440
EP  - 1443
SN  - 2352-538X
UR  - https://doi.org/10.2991/icecee-15.2015.269
DO  - 10.2991/icecee-15.2015.269
ID  - Zhao2015/06
ER  -