Screening for Chlamydial Infection. A Model Program Based on Prevalence

Sex Transm Dis. 1998 Apr;25(4):201-10. doi: 10.1097/00007435-199804000-00005.

Abstract

Background: Chlamydial infection accounts for substantial health care costs. The high frequency of asymptomatic infections necessitates screening to detect affected persons. Selective screening using risk assessment criteria attempts to target limited resources to women at increased risk. However, most risk assessment criteria have not accounted for prevalence of infection.

Objectives: To describe currently available screening options, to demonstrate the relationship between prevalence and probability of infection, and to propose a model program incorporating clinic prevalence in selective screening decisions.

Study design: A simple model demonstrating the relationship between clinic prevalence, a risk score based on risk assessment, and probability of infection was developed using basic clinical epidemiological principles.

Results: The probability of infection can be estimated from the clinic prevalence and risk score. If the estimated probability of infection exceeds previously established test thresholds, laboratory testing is warranted. As the clinic prevalence increases, the risk score necessary to justify laboratory testing decreases. Thus, the cutoffs for risk assessment criteria should be adjusted to account for clinic prevalence. In the proposed model program, the availability of resources, such as the number of tests available to a screening program, can be accommodated by appropriate adjustment of thresholds for laboratory testing.

Conclusion: The prevalence-based chlamydial screening program may provide a pragmatic strategy for areas with limited resources.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Adult
  • Chlamydia Infections / epidemiology
  • Chlamydia Infections / prevention & control*
  • Female
  • Humans
  • Mass Screening* / methods
  • Mass Screening* / statistics & numerical data
  • Patient Selection
  • Prevalence
  • Program Evaluation
  • Quality Control
  • Risk Assessment