Literature DB >> 8211533

Contact tracing and the estimation of sexual mixing patterns: the epidemiology of gonococcal infections.

G P Garnett1, R M Anderson.   

Abstract

BACKGROUND AND OBJECTIVES: The concept of a core group of individuals who change sexual partners frequently has played an important role in the study of the epidemiology of sexually transmitted diseases (STDs). It is widely believed that the core group is important in the persistence of infection and that it provides a sensible target for control interventions. GOAL OF THIS STUDY AND STUDY
DESIGN: Simple mathematical models are used to assess the significance of sexual mixing between core and noncore groups. Published data from contact tracing studies, which base the definition of the core group on gonorrhea incidence by area of residence, are used to derive estimates of the degree of mixing within and between groups.
RESULTS: Analyses reveal patterns of high mixing within core groups in the urban study sites, which suggests that within-group transmission ensures the persistence of gonococcal infection in the community as a whole.
CONCLUSIONS: An extension of the analysis of contact tracing data to facilitate the development of mathematical models of STD transmission is detailed.

Entities:  

Mesh:

Year:  1993        PMID: 8211533     DOI: 10.1097/00007435-199307000-00001

Source DB:  PubMed          Journal:  Sex Transm Dis        ISSN: 0148-5717            Impact factor:   2.830


  29 in total

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5.  Trichomonas vaginalis epidemiology: parameterising and analysing a model of treatment interventions.

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6.  Estimating duration in partnership studies: issues, methods and examples.

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8.  Heterogeneities in the transmission of infectious agents: implications for the design of control programs.

Authors:  M E Woolhouse; C Dye; J F Etard; T Smith; J D Charlwood; G P Garnett; P Hagan; J L Hii; P D Ndhlovu; R J Quinnell; C H Watts; S K Chandiwana; R M Anderson
Journal:  Proc Natl Acad Sci U S A       Date:  1997-01-07       Impact factor: 11.205

9.  Revisiting assumptions about age-based mixing representations in mathematical models of sexually transmitted infections.

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