Rise and fall of the new variant of Chlamydia trachomatis in Sweden: mathematical modelling study

Diagnosis of Chlamydia trachomatis genital infections in the era of genomic medicine

PURPOSE

Chlamydial genital infections constitute significant sexually transmitted infections worldwide. The often asymptomatic status of C. trachomatis (CT) infections leads to an increased burden on human reproductive health, especially in middle- and low-income settings. Early detection and management of these infections could play a decisive role in controlling this public health burden. The objective of this review is to provide an insight into the evolution of diagnostic methods for CT infections through the development of new molecular technologies, emphasizing on -omics' technologies and their significance as diagnostic tools both for effective patient management and control of disease transmission.

METHODS

Narrative review of the diagnostic methodologies of CT infections and the impact of the introduction of -omics' technologies on their diagnosis by review of the literature.

RESULTS

Various methodologies are discussed with respect to working principles, required specifications, advantages, and disadvantages. Implementing the most accurate methods in diagnosis is highlighted as the cornerstone in managing CT infections.

CONCLUSION

Diagnostics based on -omics' technologies are considered to be the most pertinent modalities in CT testing when compared to other available methods. There is a need to modify these effective and accurate diagnostic tools in order to render them more available and feasible in all settings, especially aiming on turning them to rapid point-of-care tests for effective patient management and disease control.

Changes in the Trend of Sexually Acquired Chlamydia Infections in Sweden and the Role of Testing: A Time Series Analysis

BACKGROUND

We investigated the notification trends of sexually acquired chlamydia (chlamydia) and its association with testing in Sweden before (1992-2004) and after (2009-2018) the discovery of a new variant of Chlamydia trachomatis (nvCT).

METHODS

We applied monthly time series analysis to study chlamydia trends and annual time series to study chlamydia rates adjusted for testing. We analyzed incidence nationally and by county group (based on able and unable to detect nvCT at time of discovery).

RESULTS

We present data on 606,000 cases of chlamydia and 9.9 million persons tested. We found a U-shaped chlamydia trend during the period 1992-2004, with an overall increase of 83.7% from 1996 onward. The period 2009-2018 began with a stable trend at a high incidence level followed by a decrease of 19.7% during the period 2015-2018. Peaks were seen in autumn and through during winter and summer. Similar results were observed by groups of county, although with varying levels of increase and decrease in both periods. Furthermore, increased testing volume was associated with increased chlamydia rates during the first period (P = 0.019) but not the second period.

CONCLUSIONS

Our results showed that chlamydia trends during the period 2009-2018 were not driven by testing, as they were during the period 1992-2004. This suggests less biased notified chlamydia rates and thus possibly a true decrease in chlamydia incidence rates. It is important to adjust case rates for testing intensity, and future research should target other potential factors influencing chlamydia rates.

Targeted surveillance strategies for efficient detection of novel antibiotic resistance variants

Genotype-based diagnostics for antibiotic resistance represent a promising alternative to empiric therapy, reducing inappropriate antibiotic use. However, because such assays infer resistance based on known genetic markers, their utility will wane with the emergence of novel resistance. Maintenance of these diagnostics will therefore require surveillance to ensure early detection of novel resistance variants, but efficient strategies to do so remain undefined. We evaluate the efficiency of targeted sampling approaches informed by patient and pathogen characteristics in detecting antibiotic resistance and diagnostic escape variants in Neisseria gonorrhoeae, a pathogen associated with a high burden of disease and antibiotic resistance and the development of genotype-based diagnostics. We show that patient characteristic-informed sampling is not a reliable strategy for efficient variant detection. In contrast, sampling informed by pathogen characteristics, such as genomic diversity and genomic background, is significantly more efficient than random sampling in identifying genetic variants associated with resistance and diagnostic escape.

Surveillance to maintain the sensitivity of genotype-based antibiotic resistance diagnostics

The sensitivity of genotype-based diagnostics that predict antimicrobial susceptibility is limited by the extent to which they detect genes and alleles that lead to resistance. As novel resistance variants are expected to emerge, such sensitivity is expected to decline unless the new variants are detected and incorporated into the diagnostic. Here, we present a mathematical framework to define how many diagnostic failures may be expected under varying surveillance regimes and thus quantify the surveillance needed to maintain the sensitivity of genotype-based diagnostics.