An Automated Surveillance System (SurCeGGID) for the French Sexually Transmitted Infection Clinics: Epidemiological Monitoring Study
Bibliographic record
Abstract
BACKGROUND: Viral and bacterial sexually transmitted infections (STIs) are public health concerns worldwide, but surveillance systems are not comprehensive enough to design and monitor accurately STI control strategies in most countries. In 2016, 320 STI clinics (CeGIDDs in French) were implemented in France, primarily targeting most exposed populations, although access is free of charge for anybody. OBJECTIVE: This article describes the mandatory surveillance system (SurCeGIDD) based on CeGIDD's individual data aiming to better guide STI prevention. METHODS: A decree ensured the use of software to manage consultations in CeGIDDs and to transfer surveillance data. A web service was implemented to secure data transfer from CeGIDDs' software to a centralized database. CeGIDDs can also transfer data in CSV format via a secured data-sharing platform. Then, data are automatically checked before integration. Data on sociodemographic variables, sexual exposure, blood exposure, symptoms, STI tests, STI diagnoses, and sexual health services delivery were collected for the previous year (n-1). Preliminary and descriptive analyses of 2017-2018 data transmitted in 2018 and 2019, respectively, were performed using numbers and proportions for qualitative variables. RESULTS: In 2017, 54/320 (16.9%) CeGIDDs transmitted their data. In 2018, this number of participants increased to 143/320 (44.7%) CeGIDDs. The corresponding volume of records increased from 2414 in 2017 to 382,890 in 2018. In 2018, most attendances were hospital based (263,480/382,890, 68.81%). In 2018, attendees were mostly men 227,326/379,921 (59.84%), while 151,963/379,921 (40%) were women 632/379,921 (0.17%) transgenders. The median age was 27 years for men, 23 years for women, and 30 years for transgender. Half of the attendees (81,964/174,932, 46.85%) were heterosexual men, 69,016/174,932 (39.45%) heterosexual women, 20,764/174,932 (11.87%) men who have sex with men, and 3188/174,932 (1.82%) women who have sex with women. A majority of them were born in France (227,698/286,289, 79.53%) and unemployed 115,913/211,707 (54.75%). The positivity rates were 0.37% for 205,348 HIV serologies, 1.31% for 131,551 hepatitis B virus serologies, 7.16% for 161,241 Chlamydia trachomatis PCR, 2.83% for 146,649 gonorrhea PCR, 1.04% for the syphilis combination of treponema and nontreponema serologies, and 5.96% for 13,313 Mycoplasma genitalium PCR. CONCLUSIONS: Despite challenges, the effectiveness of the SurCeGIDD surveillance based on routine patients' records was demonstrated. The wide range of information, including socioeconomic determinants, might help to better guide and evaluate the prevention policies and services delivery. However, the growing volumes of information will require adapted tools and algorithms for the data management and analyses.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".