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Intensified partner notification and repeat testing can improve the effectiveness of screening in reducing Chlamydia trachomatis prevalence: a mathematical modelling study
  1. Ben B Hui1,
  2. Jane S Hocking2,
  3. Sabine Braat3,4,
  4. Basil Donovan1,
  5. Christopher K Fairley5,6,
  6. Rebecca Guy1,
  7. Simone Spark7,
  8. Anna Yeung8,
  9. Nicola Low9,
  10. David Regan1
  1. 1 The Kirby Institute, UNSW Sydney, Kensington, New South Wales, Australia
  2. 2 Melbourne School of Population and Global Health, University of Melbourne, Parkville, Victoria, Australia
  3. 3 Centre for Epidemiology and Biostatistics, School of Population and Global Health, University of Melbourne, Parkville, Victoria, Australia
  4. 4 MISCH (Methods and Implementation Support for Clinical and Health) Research Hub, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Parkville, Victoria, Australia
  5. 5 Melbourne Sexual Health Centre, Alfred Health, Carlton, Victoria, Australia
  6. 6 Central Clinical School, Monash University, Melbourne, Victoria, Australia
  7. 7 School of Public Health, Monash University, Melbourne, Victoria, Australia
  8. 8 MAP Centre for Urban Health Solutions, Unity Health Toronto, St Michael’s Hospital, Toronto, Ontario, Canada
  9. 9 Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
  1. Correspondence to Dr Ben B Hui, The Kirby Institute, The Kirby Institute, Kensington, NSW 2052, Australia; b.hui{at}unsw.edu.au

Abstract

Background The Australian Chlamydia Control Effectiveness Pilot (ACCEPt) was a cluster randomised controlled trial designed to assess the effectiveness of annual chlamydia testing through general practice in Australia. The trial showed that testing rates increased among sexually active men and women aged 16–29 years, but after 3 years the estimated chlamydia prevalence did not differ between intervention and control communities. We developed a mathematical model to estimate the potential longer-term impact of chlamydia testing on prevalence in the general population.

Methods We developed an individual-based model to simulate the transmission of Chlamydia trachomatis in a heterosexual population, calibrated to ACCEPt data. A proportion of the modelled population were tested for chlamydia and treated annually at coverage achieved in the control and intervention arms of ACCEPt. We estimated the reduction in chlamydia prevalence achieved by increasing retesting and by treating the partners of infected individuals up to 9 years after introduction of the intervention.

Results Increasing the testing coverage in the general Australian heterosexual population to the level achieved in the ACCEPt intervention arm resulted in reduction in the population-level prevalence of chlamydia from 4.6% to 2.7% in those aged 16–29 years old after 10 years (a relative reduction of 41%). The prevalence reduces to 2.2% if the proportion retested within 4 months of treatment is doubled from the rate achieved in the ACCEPt intervention arm (a relative reduction of 52%), and to 1.9% if the partner treatment rate is increased from 30%, as assumed in the base case, to 50% (a relative reduction of 59%).

Conclusion A reduction in C. trachomatis prevalence could be achieved if the level of testing as observed in the ACCEPt intervention arm can be maintained at a population level. More substantial reductions can be achieved with intensified case management comprising retesting of those treated and treatment of partners of infected individuals.

  • Chlamydia trachomatis
  • mathematical model
  • infection control

Data availability statement

The modelling code is publicly available and informed by publicly available data. No dataset was generated. The model code is written in Java and is available on GitHub at the following address: https://bbcbh@github.com/bbcbh/Package_ACCEPtPlus.git. All other data used in the analysis are already published.

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Data availability statement

The modelling code is publicly available and informed by publicly available data. No dataset was generated. The model code is written in Java and is available on GitHub at the following address: https://bbcbh@github.com/bbcbh/Package_ACCEPtPlus.git. All other data used in the analysis are already published.

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Footnotes

  • Handling editor Laith J Abu-Raddad

  • Twitter @nicolamlow

  • Contributors BBH is responsible for the overall content as guarantor. BBH, JSH, NL and RG contributed to conceptualisation of the study. BBH developed the model. BBH, JSH, NL and RG discussed the main model findings. BBH and RG wrote the original manuscript. JSH and RG supervised the work and contributed resources. All authors reviewed and edited the manuscript.

  • Funding This work was supported by the Australian National Health and Medical Research Council (NHMRC) Project Grant (1007937) and an NHMRC Partnership Grant (1056803). JSH is supported by an NHMRC Senior Research Fellowship Grant (1136117). CKF is supported by an NHMRC Leadership Investigator Grant (GNT1172900).

  • Competing interests None declared.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.