Degree Distributions in Sexual Networks: A Framework for Evaluating Evidence

Deven T. Hamilton, Mark S. Handcock, Martina Morris

Sexually Transmitted Diseases · 2008 · 76 citations · 45 references

Abstract

Power-law models do not fit the data better than alternative models, and they consistently make inaccurate epidemic predictions. Better models are needed to represent the behavioral basis of sexual networks and the structures that result, if these data are to be used for disease transmission modeling.

References

45