Epidemiology of chlamydial infection: are we losing ground?

Screening programmes to identify and treat young women with chlamydial infection have been developed in several countries. The goals of these screening programmes are, for the individual, to reduce a woman’s likelihood of experiencing important reproductive health complications, and, for the population, to reduce the incidence and prevalence of chlamydial infection in the population at risk. The primary objective of this commentary is to address whether we are losing ground in our efforts to prevent chlamydial infection and its complications.

Screening programmes to identify and treat young women with chlamydial infection have been developed in several countries. The goals of these screening programs may be conceptualised at two complementary levels.¹ For the individual, screening is intended to reduce a woman’s likelihood of experiencing important reproductive health complications, such as pelvic inflammatory diseases (PID), tubal infertility and ectopic pregnancy. For the population, screening programmes may reduce the incidence and prevalence of chlamydial infection in the population at risk. Reducing prevalence and incidence should also reduce transmission, preventing additional cases of reproductive complications.

How do we gauge the success or failure of a screening programme for chlamydial infection? Screening programmes should decrease the incidence of PID, infertility and ectopic pregnancy.² Although randomised clinical trials suggest screening can be successful,³ demonstrating efficacy through surveillance is extremely challenging. PID, infertility and ectopic pregnancy have multiple potential aetiologies. Consequently, changes in rates over time may not be attributable solely to changes in the epidemiology of chlamydial infection.

At first glance, surveillance estimates of the prevalence and incidence of chlamydial infection appear to provide direct measures of the effectiveness of chlamydial screening programmes.^4–7 Indeed, recent increases in the incidence and prevalence of chlamydial infection despite ongoing screening has raised questions about screening programmes’ effectiveness and the effects of screening on immunological responses.^{7 8} However, surveillance data must be interpreted cautiously. The primary objective of this commentary is to address whether we are losing ground in our efforts to prevent chlamydial infection and its complications.

DETERMINANTS OF INCIDENCE AND PREVALENCE

Unlike non-transmissible diseases, the incidence of infectious diseases is influenced by the prevalence of the disease.⁹ Because acquisition of Chlamydia requires contact with an infected sexual partner, the prevalence of chlamydial infection in the pool of potential partners is a key determinant of the incidence. If the partner is not infected, transmission is impossible. The incidence is also influenced by the rate of sexual partner change and other sexual behaviours, such as condom use. The duration of infection influences the likelihood of transmission and, thereby, also influences the incidence.⁹ Screening programmes, in theory, should reduce incidence through reductions in the duration of the infection. Similarly, prevalence is a function of the incidence and duration.¹⁰

For surveillance purposes, incidence and prevalence are often estimated through cases reported to a central health authority. The annual incidence rate and the prevalence are calculated as follows:

Incidence rate (IR) = Cases Reported / population at risk * 1 year

Prevalence = Cases reported / persons tested in specific populations

For estimation of the IR, the denominator is usually derived from census estimates of the population. In contrast, estimation of the prevalence is usually based on specific populations, such as women attending family planning clinics. In the calculation of the IR, it is not possible to distinguish from new cases and existing cases with routine surveillance data. In addition, clinic prevalence is often used as an estimate of population prevalence, a problem we will address below.

The observed IR and prevalence are influenced by several factors, creating uncertainty in these estimates. Potentially important biases affecting the estimates include reporting by clinicians, coverage of the population, case (or risk) mix of the population tested and the performance of the diagnostic tests used to identify cases. Healthcare seeking behaviour (who chooses to seek health care) will also influence the estimates over time. The magnitude of the bias associated with these factors can influence the IR and prevalence estimates differentially, so we will consider the IR and prevalence separately.

POTENTIAL BIAS IN THE ANNUAL INCIDENCE RATE

Reporting bias
Although reporting of chlamydial infection is mandated in each of the 50 US states, compliance with reporting is variable. Generally, private physicians may report less consistently than publicly funded clinics, causing underestimation of cases. Reporting bias may also distort rates in subpopulations. For example, racial/ethnic groups that are more likely to use publicly funded clinics will have more complete reporting than groups that use private physicians. This differential can exaggerate disparities in rates.

Reporting for chlamydial infection was not required in all 50 states and the District of Columbia until the year 2000. As of 1988, only 26 states required reporting. Although the denominators of calculated IR were adjusted to represent only the states reporting, as additional states required reporting, the observed prevalence and incidence would have changed over time simply because the rates in the new states were varied. Such changes could mask or exaggerate any true changes in national rates over time.

Coverage
Coverage is one of the most important factors responsible for an observed increase in the annual incidence rate of chlamydial infection. Coverage reflects the proportion of the population that is reached with screening activities. Because the incidence rate denominator is relatively constant, increases in coverage will generally lead to more cases being identified. Consequently, the observed IR increases. These observed increases may occur in the face of an unchanging, increasing or even declining true incidence rate.

In 1999, screening for chlamydial infection in young women was included as a Healthcare Effectiveness Data and Information Set (HEDIS) measure for insurance companies in the USA. Consequently, coverage was monitored to assess the proportion of the population of young women who were tested for chlamydial infection. Comparing the reported coverage among Medicaid and privately insured women for the period 1999–2005 reveals a striking relationship. The coverage and incidence rates rise in parallel. Using simple linear regression to investigate the relationships further, we see a strong and significant relationship with R2 values between 0.926 and 0.966 (corresponding to correlation coefficients of 0.962 to 0.983), indicating a large proportion of the variance in the IR is explained by coverage.

Case mix and diagnostic test performance
The risk-related composition of the population being tested, or case mix, and the diagnostic test accuracy can have substantial effects on the observed IR over time. As these effects are similar for the IR and prevalence, I will describe their potential influence in detail when discussing effects on prevalence.

ESTIMATING RATES OF REINFECTION

In addition to changes in the incidence rate and prevalence of chlamydial infection, reported rates of reinfection have increased in some settings.⁷ Reinfection represents women who have been screened or tested for chlamydial infection and then return after some period of time with another infection. The rise in reinfection has been hypothesised to be because of a reduction in the immune response brought about by the shortened duration of infection associated with screening.^{7 8} Although this hypothesis may have merit, estimating reinfection from routine data sources is problematic.

First, we must consider what is meant by the term “reinfection rate”. This term has occasionally been used to refer to the number of repeat infections (for example, second or third) divided by the population in the community. In other words, it is calculated like the annual incidence rate, but with the numerator, which usually reflects all cases replaced by those cases that are second infections. The problem with this formulation is that the denominator does not truly reflect the population at risk. When one considers “reinfections”, only those persons who have had a previous infection are at risk. If the denominator includes the entire population, the reinfection rate will increase simply because the number of persons previously diagnosed with chlamydial infection is increasing over time. In other words, the denominator is remaining relatively constant, but the pool of persons at risk for inclusion in the numerator is increasing.

Another uncertainty in the estimation of reinfection rates relates to undiagnosed infections. For example, a person with undiagnosed chlamydial infection may spontaneously clear their infection. If this person subsequently acquires a new infection and is diagnosed, the infection will be counted as a first infection even though it is actually a reinfection. As a consequence, if a screening programme is introduced into a population with a steady infection rate, the number of persons with reinfections will appear to increase because the pool of persons eligible to have a second infection is increasing as more first infections are diagnosed.

Finally, reinfection rates are difficult to assess from clinic data because follow up is not strictly controlled. A clinic setting is not a cohort study and persons may or may not return for subsequent testing. Changes in the proclivity of persons to return for subsequent evaluations will directly affect the observed rates of reinfection.

Testing frequency and incidence rates
As a final caution, it is important to recognise that testing frequency can influence observed incidence rates of overall infection or reinfection. In the simplest case, if we assume that a chlamydial infection would persist for about 1 year in a young woman, then testing and treating that woman’s infection during that year will give her the opportunity to be infected again. If she acquires another infection and the infection is detected, the incidence rate will increase, but this increase is brought about by her opportunity for infection created by the original screening and treatment. Because of the initial screening and treatment, followed by reinfection and repeat testing, she has contributed two cases rather than one.

CONCLUSION

The premise of this debate was that national screening programmes might be causing a rise in chlamydial infection incidence, because of the potential effects on acquired immunity and resultant increased risk of reinfection. Determining whether we are losing ground in our prevention efforts is challenging using surveillance data, given the measurement issues described. However, one telling piece of information is the coverage of women eligible for screening. In the USA, the proportion of eligible women screened remains low—below 50%. Rises in the incidence rate correlate directly with rises in coverage. However, despite the increases in coverage, I doubt that we are currently reaching enough women to have a substantial impact on the prevalence of chlamydial infection in the general population or the incidence of complications, especially given that men are not actively screened. In other words, I do not believe that our screening programmes have been successful enough to induce a reduction in acquired immunity. Rather, given our limited success to date, I believe we have much more ground to be gained.

REFERENCES


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W C Miller
Sexually Transmitted Infections 2008;84:82-86; doi:10.1136/sti.2007.028662

Correspondence to:
William C Miller, CB# 7435, 2105F McGavran-Greenberg, Department of Epidemiology, UNC – Chapel Hill, Chapel Hill, NC 27599-7435 USA; bill_miller[at]unc.edu

Accepted for publication 11 January 2008 - http:// sti.bmj.com.proxy.lib.ltu.se/cgi/content/full/84/2/82

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