title: A Comparison of Two Mathematical Modeling Frameworks for Evaluating Sexually Transmitted Infection Epidemiology.
abstract: BACKGROUND
  Different models of sexually transmitted infections (STIs) can yield substantially different conclusions about STI epidemiology, and it is important to understand how and why models differ. Frequency-dependent models make the simplifying assumption that STI incidence is proportional to STI prevalence in the population, whereas network models calculate STI incidence more realistically by classifying individuals according to their partners' STI status.
  
  
  METHODS
  We assessed a deterministic frequency-dependent model approximation to a microsimulation network model of STIs in South Africa. Sexual behavior and demographic parameters were identical in the 2 models. Six STIs were simulated using each model: HIV, herpes, syphilis, gonorrhea, chlamydia, and trichomoniasis.
  
  
  RESULTS
  For all 6 STIs, the frequency-dependent model estimated a higher STI prevalence than the network model, with the difference between the 2 models being relatively large for the curable STIs. When the 2 models were fitted to the same STI prevalence data, the best-fitting parameters differed substantially between models, with the frequency-dependent model suggesting more immunity and lower transmission probabilities. The fitted frequency-dependent model estimated that the effects of a hypothetical elimination of concurrent partnerships and a reduction in commercial sex were both smaller than estimated by the fitted network model, whereas the latter model estimated a smaller impact of a reduction in unprotected sex in spousal relationships.
  
  
  CONCLUSIONS
  The frequency-dependent assumption is problematic when modeling short-term STIs. Frequency-dependent models tend to underestimate the importance of high-risk groups in sustaining STI epidemics, while overestimating the importance of long-term partnerships and low-risk groups.
authors: From the Centres for *Infectious Disease Epidemiology and Research and †Social Science Research, University of Cape Town, Cape Town, South Africa.
authors: Leigh F
authors: LF
authors: Johnson
authors: Nathan
authors: N
authors: Geffen
mesh_terms: D005260:Female; D006801:Humans; D008297:Male; D015233:Models, Statistical; D015995:Prevalence; D040242:Risk Reduction Behavior; D012725:Sexual Behavior / Q000706:statistics & numerical data*; D012747:Sexual Partners; D012749:Sexually Transmitted Diseases / Q000453:epidemiology / Q000635:transmission