ABSTRACT
BACKGROUND: Chlamydia case reports decreased in 2020 in North Carolina (NC). COVID-19 social distancing restrictions and NAAT shortages undoubtedly impacted chlamydia screening practices, but the magnitude is unknown. Persons coinfected with gonorrhea may be less susceptible to changing screening practices because symptoms are more likely to be present. We assessed coinfection rates over time to estimate missed chlamydia case reports in 2020. METHOD(S): We reviewed all chlamydia cases reported to NC surveillance during 2012 to 2020 to identify those with gonorrhea diagnosed within 14 days of their chlamydia diagnosis. We calculated yearly proportions of gonorrhea coinfection by gender. We mulitplied the number of coinfections in 2020 by the inverse proportion of coinfections observed during the most recent 3-year period (2017-2019) to estimate the number of chlamydia cases likely to have been reported in 2020 without COVID- 19. RESULT(S): During 2012 to 2020, 526,882 chlamydia cases were reported in NC (men: N=151,665;women: N=375,146;unknown gender: N=71). Gonorrhea coinfection was identified in 14.0% of chlamydia cases in men and 8.2% in women. Gonorrhea coinfections increased steadily between 2012 (men: 1248;women: 2878) and 2020 (men: 3597;women: 4251). Proportions of coinfected cases remained stable by gender between 2012 and 2019 (Range: men: 11.1%-14.6%;women: 7.5%- 8.6%), increasing in 2020 (men: 17.2%;women: 9.7%). Dividing the 2020 coinfection counts by the most recent 3-year average coinfection proportion (men: 14.3%;women: 8.3%), we estimated 25,137 men and 51,074 women should have been reported with chlamydia in 2020. Subtracting the 2020 case reports from these estimates, 11,700 chlamydia cases went unreported in 2020 (4262 men;7438 women). CONCLUSION(S): Chlamydia went undiagnosed in 2020 due to the COVID-19 pandemic. Quantifying the number of unreported, and possibly untreated, chlamydia cases can help health departments mitigate their impact on transmission rates and long-term sequelae associated with failure to treat.
ABSTRACT
Background: Knowing the true incidence of HIV-1 infections (recent infections) among people newly diagnosed is pivotal to monitoring the course of the epidemic. We have developed a Primer ID Next Gen Sequencing (PID-NGS) assay to identify recent infection by measuring within-host viral diversity over multiple regions of the HIV-1 genome. We implemented a state-wide project to identify recent infections and transmitted drug resistance mutations (DRMs) in diagnostic samples in near real time. Methods: Serum samples from individuals with newly HIV-1 diagnoses (diagnostic sample collected within 30 days of diagnosis) were sequenced. PID-NGS libraries were constructed covering the coding regions for protease, a portion of reverse transcriptase, integrase, and the env gene. The use of the PID-NGS strategy allows for significant error correction and also a definition of the sampling depth of the viral population. Recent infection was defined as within 9-month of infection. DRMs were summarized at detection sensitivities of 30%, 10% and 1% based on viral population sampling depth. Results: From Jan 2018 to Jun 2021, we successfully sequenced partial genomes from 743 individuals with new diagnoses. Year 2020 had the lowest number of new diagnoses (Fig 1a, red bar). Overall, 39.2% of samples were inferred to have represented infection within the previous 9 months. Percent of recent infection varied significantly over the years, increasing from 29.6% in late 2018 to 50.9% in early 2020, but decreasing significantly to 32.7% in 2021 (Fig 1a, blue lines). Individuals younger than 30 y/o were more likely to be identified with recent infection (p<0.01). NNRTI DRMs, especially K103N, were the most abundant DRMs. Fig 1b shows the trend of DRMs over the four years. We observed a trend of decrease in the overall NNRTI DRMs and an increase in the NRTI DRMs in the population. Further analysis suggests that the increase in NRTI DRMs were from TAMs and their revertants, while clinically important NRTI DRMs (K65R and M184) were low (<1%). Conclusion: We have demonstrated a state-wide, all-in-one platform to monitor HIV-1 recency and DRMs in new diagnoses. The number of new diagnoses decreased significantly in 2020 in concert with the COVID-19 pandemic which suggests a decrease in overall HIV testing. The decline in the percentage of recent infections in early 2021 signals a return to broader HIV-1 testing and diagnosis. The increase of other NRTI DRMs suggests ongoing evolution at these sites within the viral population.