A new scale-free network model for simulating and predicting epidemics

J Theor Biol. 2013 Jan 21:317:11-9. doi: 10.1016/j.jtbi.2012.09.020. Epub 2012 Sep 28.

Abstract

The course of epidemics often resembles a scale-free network, but some specific elements should be considered in developing a new model. This study introduces a time-shifting and discontinuous forcing function H into the scale-free network model to fit the specific period and intensity of the infection, and redefines the probability p as abortive infection rate. For the non-human vectors or hosts, three new factors (new connectivity K(i)(t), new links M, and time delay τ) were introduced in the proposed model of this study. The simulation results of six types of epidemic transmissions show that the proposed Scale-Free Epidemic Models, SFE-1 and SFE-2, are accurate. SFE-1 model and SFE-2 model are useful for the transmission categories from human and insects/vertebrates, respectively. Further comparisons of different races/ethnicities and different transmission categories of AIDS cases in the United States were also analyzed. Both SFE models can be used to predict epidemics and can suggest the results more clearly, irrespective of whether the epidemics are under control. Therefore, the proposed SFE models can help the government determine the level of caution required and predict the results of policy decisions, thus helping to balance socioeconomic and health concerns.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Acquired Immunodeficiency Syndrome / epidemiology
  • Animals
  • Colorado / epidemiology
  • Communicable Diseases / epidemiology
  • Communicable Diseases / transmission
  • Computer Simulation*
  • Epidemics / statistics & numerical data*
  • Humans
  • Insecta
  • Models, Biological*
  • Singapore / epidemiology
  • Sweden / epidemiology
  • Taiwan / epidemiology
  • Vertebrates