Literature DB >> 1594800

Estimating transmission probabilities for chlamydial infection.

B P Katz1.   

Abstract

Estimates of transmission probabilities for sexually transmitted diseases historically come from studies of uninfected individuals exposed to those with a high disease prevalence (for example, prostitutes). However, changes in sexual behaviour, much of which relates to concerns about AIDS, has made identification of populations suitable for such studies extremely difficult. This paper presents a method for estimating these probabilities that utilizes a deterministic model and routinely collected data available in many clinics. Variance estimates for the estimators are also derived. Data for chlamydial infection and sensitivity analyses for the input parameters and assumptions illustrate the method.

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Year:  1992        PMID: 1594800     DOI: 10.1002/sim.4780110502

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  10 in total

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2.  A Stochastic Model for Assessing Chlamydia trachomatis Transmission Risk Using Longitudinal Observational Data.

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3.  Evaluation of intra- and extra-epithelial secretory IgA in chlamydial infections.

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4.  Per-partnership transmission probabilities for Chlamydia trachomatis infection: evidence synthesis of population-based survey data.

Authors:  Joanna Lewis; Peter J White; Malcolm J Price
Journal:  Int J Epidemiol       Date:  2021-05-17       Impact factor: 7.196

5.  The Cervicovaginal Microbiota-Host Interaction Modulates Chlamydia trachomatis Infection.

Authors:  Vonetta L Edwards; Steven B Smith; Elias J McComb; Jeanne Tamarelle; Bing Ma; Michael S Humphrys; Pawel Gajer; Kathleen Gwilliam; Alison M Schaefer; Samuel K Lai; Mishka Terplan; Katrina S Mark; Rebecca M Brotman; Larry J Forney; Patrik M Bavoil; Jacques Ravel
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6.  Nonoptimal Vaginal Microbiota After Azithromycin Treatment for Chlamydia trachomatis Infection.

Authors:  Jeanne Tamarelle; Bing Ma; Pawel Gajer; Mike S Humphrys; Mishka Terplan; Katrina S Mark; Anne C M Thiébaut; Larry J Forney; Rebecca M Brotman; Elisabeth Delarocque-Astagneau; Patrik M Bavoil; Jacques Ravel
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7.  Exploiting temporal network structures of human interaction to effectively immunize populations.

Authors:  Sungmin Lee; Luis E C Rocha; Fredrik Liljeros; Petter Holme
Journal:  PLoS One       Date:  2012-05-07       Impact factor: 3.240

8.  Individual and population level effects of partner notification for Chlamydia trachomatis.

Authors:  Christian L Althaus; Janneke C M Heijne; Sereina A Herzog; Adrian Roellin; Nicola Low
Journal:  PLoS One       Date:  2012-12-12       Impact factor: 3.240

Review 9.  How robust are the natural history parameters used in chlamydia transmission dynamic models? A systematic review.

Authors:  Bethan Davies; Sarah-Jane Anderson; Katy M E Turner; Helen Ward
Journal:  Theor Biol Med Model       Date:  2014-01-30       Impact factor: 2.432

10.  Estimating age-dependent per-encounter chlamydia trachomatis acquisition risk via a Markov-based state-transition model.

Authors:  Yu Teng; Nan Kong; Wanzhu Tu
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  10 in total

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