A comparison of computational efficiencies of stochastic algorithms in terms of two infection models

Math Biosci Eng. 2012 Jul;9(3):487-526. doi: 10.3934/mbe.2012.9.487.

Abstract

In this paper, we investigate three particular algorithms: a stochastic simulation algorithm (SSA), and explicit and implicit tau-leaping algorithms. To compare these methods, we used them to analyze two infection models: a Vancomycin-resistant enterococcus (VRE) infection model at the population level, and a Human Immunodeficiency Virus (HIV) within host infection model. While the first has a low species count and few transitions, the second is more complex with a comparable number of species involved. The relative efficiency of each algorithm is determined based on computational time and degree of precision required. The numerical results suggest that all three algorithms have the similar computational efficiency for the simpler VRE model, and the SSA is the best choice due to its simplicity and accuracy. In addition, we have found that with the larger and more complex HIV model, implementation and modification of tau-Leaping methods are preferred.

Publication types

  • Comparative Study
  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Algorithms*
  • Computer Simulation / statistics & numerical data
  • Enterococcus / drug effects
  • Gram-Positive Bacterial Infections / drug therapy
  • Gram-Positive Bacterial Infections / epidemiology*
  • Gram-Positive Bacterial Infections / transmission*
  • HIV Infections / epidemiology*
  • HIV Infections / transmission*
  • Humans
  • Models, Statistical*
  • Population Dynamics
  • Vancomycin Resistance