How the Disruption in Sexually Transmitted Infection Care Due to the COVID-19 Pandemic Could Lead to Increased Sexually Transmitted Infection Transmission Among Men Who Have Sex With Men in The Netherlands: A Mathematical Modeling Study
Bibliographic record
Abstract
BACKGROUND: During the COVID-19 pandemic, the disruption in care for sexually transmitted infections (STIs) and the social distancing measures have led to reductions in STI testing and sexual behavior. We assessed the impact of these COVID-19-related changes on transmission of Chlamydia trachomatis (CT) and Neisseria gonorrhoeae (NG) among men who have sex with men (MSM) in The Netherlands. METHODS: We developed a mathematical model for CT and NG transmission among MSM, accounting for COVID-19-related changes in sexual behavior and testing in 2020 to 2021. Changes in 2020 were estimated from data from the Dutch COVID-19, Sex, and Intimacy Survey among MSM and the National Database of STI Clinics. Because of the lack of data for 2021, we examined several scenarios covering a range of changes. RESULTS: A reduction of 10% and 40% in STI testing of symptomatic and asymptomatic, respectively, individuals with a 10% to 20% reduction in numbers of casual partners (according to partner status and activity level) during the second lockdown, resulted in a 2.4% increase in CT prevalence, but a 2.8% decline in NG prevalence in 2021. A 5% and 30% reduction in STI testing of symptomatic and asymptomatic, respectively, individuals with the same reduction in casual partners resulted in a 0.6% increase in CT prevalence and a 4.9% decrease in NG prevalence in 2021. CONCLUSIONS: The disruption in STI care due to COVID-19 might have resulted in a small increase in CT prevalence, but a decrease in NG prevalence. Scaling up STI care is imperative to prevent increases in STI transmission.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".