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Editorial

The Arrested Immunity Hypothesis and the Epidemiology of Chlamydia Control

Brunham, Robert C. MD*†; Rekart, Michael L. MD, MHSc*†

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Sexually Transmitted Diseases: January 2008 - Volume 35 - Issue 1 - p 53-54
doi: 10.1097/OLQ.0b013e31815e41a3
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Case detection, antimicrobial treatment, and contact tracing are at the heart of control strategies for many important communicable bacterial diseases. Together with behavioral messages regarding safe sexuality, these have been the approaches taken in several countries to control sexually transmitted Chlamydia trachomatis.1 Advances in nucleic acid amplification tests (NAATs) and single-dose azithromycin treatment make chlamydia an imminently feasible target for control. Chlamydia infection impacts reproductive health primarily for women, and control using these tools significantly reduced the reproductive impact of untreated infection in a prospective trial.2 The goal of chlamydia control has been to improve the reproductive health of women by interrupting transmission through shortening the duration of infection.3 Thus several national and regional chlamydia control programs were launched in the late 1980s and throughout the 1990s.

We are now approaching 20 years of experience with chlamydia control programs, and at least 5 trends in chlamydia epidemiology are emerging. The first of these trends includes the development of 2 distinct epidemiologic profiles of reported case rates (as a measure of population based annual incidence) following the introduction of control programs. In Sweden, Norway, Finland, and Canada, case rates declined for a decade following program introduction but then have steadily increased from the mid- to late 1990s. In Australia, the United States, and the United Kingdom, case rates steadily increased following program rollout without an initial decline phase.4–6 It is not established what caused these 2 distinct epidemiologic response profiles, but it could reflect differences in populationwide versus incremental introduction of control activities. Second, increase in reinfection rates has paralleled increases in case rates. In British Columbia, Canada, reinfections now account for 14% of annual reported cases, with most reinfections (>90%) occurring within the first year after initial infection.7 Third, reproductive sequelae rates (ectopic pregnancy and tubal infertility) have declined in jurisdictions where they have been measured. Again, in British Columbia, 40–60% declines in ectopic pregnancy and tubal infertility rates have been recorded during the era of chlamydia control.8 Fourth, in Sweden, case detection based on NAATs has been sufficiently intense to select for the emergence of a single novel genetic variant of C. trachomatis. This clone emerged in as little as 2–4 years and is able to escape conventional NAAT detection in such a manner that it now accounts for 20–65% of all chlamydia strains identified in selected Swedish counties.9 The usual evolutionary response of a pathogen to “test and treat” public health programs has been to acquire antimicrobial resistance, often though lateral gene transfer. Thus it may be of fundamental biologic interest that the evolutionary response of chlamydia has been to acquire genetic escape not from the drug treatment but from the detection method itself. And fifth, A.M. Jolly and colleagues sampled the case-contact network structure at 3 distinct time intervals during the era of chlamydia control in Manitoba and demonstrated a remarkable reduction in the size of the largest sexual networks during the control era (A.M. Jolly, personal communication). Shrinkage in size of the giant component of sexual networks might have been expected to result in increased control, but this has not been the experience in Manitoba where case rates continue to rise.10

In British Columbia, Canada, where the epidemiology of chlamydia control has been analyzed in greatest detail, we have suggested that raising case rates are due to early treatment interfering with the development of protective immune responses.7 We have termed this the arrested immunity hypothesis. Because both the development of protective immune responses and the tissue damaging effects of infection appear to depend on the duration of infection, and because early detection and treatment would be expected to reduce infection duration, this hypothesis can explain both the raising case rates and the declining sequelae rates. A prediction of the arrested immunity hypothesis was that one would expect chlamydia antibody seroprevalence rates to fall while chlamydia case rates rise in the face of control efforts. Remarkably, this is precisely what has been observed in Finland and recently reported at the International Society for STD Research by Jorma Paavonen.11 In Finland, chlamydia case rates have risen by 60% while population seroprevalence rates have fallen by 50%.

However, arrested immunity is unlikely to be the only explanation for raising case rates following the introduction of chlamydia control programs. Changes in diagnostic test sensitivity, access to chlamydia screening and changes in sexual behavior could also contribute to raising rates. It is in the evaluation of these other potential contributors to the epidemiology of chlamydia control that the paper by David Fine and colleagues in this issue of the journal is important. In the northwest region (Region X) of the United States, populationwide chlamydia control programs have been in place since 1988. Following an initial decade-long decline in case rates, chlamydia rates steadily increased by over 46% between 1997 through 2004 in this region. Fine et al. carefully controlled for the confounding effects of changing laboratory test characteristics and demographic and sexual risk behaviors of client populations and showed an independent 5% per year increase in chlamydia positivity over this 8-year period. Thus the authors conclude that there has occurred a true increase in chlamydia case rates unexplained by these important variables. They suggest that unmeasured changes in sexual networks may have contributed to the raising case rates perhaps similar to the changes reported by Jolly et al. How such changes in sexual networks might influence incidence is as yet unclear.

Understanding the impact of public health efforts on communicable disease control is at the heart of evidence-based public health. However, the outcome of efforts can be poorly predicted, in part, because of incomplete understanding of the forces that determine the dynamic equilibrium of a directly transmissible infectious disease in a population. Clearly characteristics of herd immunity, infection transmission within heterogeneous social networks, and the intervention itself are all able to result in highly nonlinear outcomes. In this regard, mathematical models of disease dynamics can help guide thinking through the complex maze of nonlinear relationships between control effort perturbation and disease outcome. A simple compartmental model of chlamydia transmission dynamics vividly illustrated the wavelike oscillation in infection prevalence that can occur following control interventions that provide early treatment but which reduce the development of host immunity.7 The model shows that reintroduction of treated subjects back into their unchanged sexual risk environment can paradoxically increase population prevalence of infection. Further study of the social and biologic determinants of disease and infection dynamics should improve our ability to predict optimal strategies for communicable disease control. It may be that for sexually transmitted infections such as chlamydia, where there may exist a trade-off between early treatment and enhanced susceptibility to reinfection, vaccination will emerge as the optimal control strategy.

References

1. Public Health Agency of Canada. Canadian Guidelines on Sexually Transmitted Infections, 2006. Available at: www.publichealth.gc.ca/sti.
2. Scholes D, Stergachis A, Heidrich FE, et al. Prevention of pelvic inflammatory disease by screening for cervical Chlamydia infection. N Engl J Med 1996; 21:1399–1401.
3. Brunham RC. Parran Award Lecture: Insights into the epidemiology of sexually transmitted diseases from Ro = betacD. Sex Transm Dis 2005; 32:722–724.
4. CDC. Sexually Transmitted Disease Surveillance 2005. Available at: www.cdc.gov/std/chlamydia2005/ctsurvsupp2005short.pdf.
5. Health Protection Agency. Increasing rates of Chlamydia trachomatis and the role of screening. CDR Wkly 2006; 16:5–7.
6. Vajdic CM, Middleton M, Bowden FJ, et al. The prevalence of genital Chlamydia trachomatis in Australia 1997–2004: A systematic review. Sex Health 2005; 2:169–183.
7. Brunham RC, Poubohloul B, Mak S, et al. The unexpected impact of a Chlamydia trachomatis infection control program on susceptibility to reinfection. J Infect Dis 2004; 192:1836–1844.
8. Brunham RC, Poubohloul B, Mak S, et al. Reply to Hagdu and to Moss et al. J Infect Dis 2006; 193:1338–1339.
9. Herrmann, B. A new genetic variant of Chlamydia trachomatis. Sex Transm Infect 2007; 83:253–254.
10. Wylie JL, Cabral T, Jolly AM. Identification of networks of sexually transmitted infections: A molecular, geographic, and social network analysis. J Infect Dis 2005; 191:899–906.
11. Surcel H-M, Kaasila M, Lyytikainen E, et al. C trachomatis seroprevalence atlas of Finland 1983–2003. Paper presented at: 17th International Society for STD Research/10th International Union against STIs Meeting; July 2007; Seattle. Abstract O-0009.
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