Public health funding and chlamydia and gonorrhea rates among adolescents during the COVID-19 pandemic in Ontario, Canada: An interrupted time series study
Bibliographic record
Abstract
OBJECTIVES: We estimated the association between local public health infectious and communicable diseases (ICD) funding and chlamydia and gonorrhea trends before and during the COVID-19 pandemic among adolescents aged 13-19 in Ontario, Canada. STUDY DESIGN: Quasi-experimental, interrupted time series. METHODS: We conducted a population-based analysis using repeated cross-sectional data of chlamydia and gonorrhea incidence among adolescents across Ontario's 34 regional public health units from January 2015 to October 2022. We used negative binomial-regression to estimate changes in chlamydia and gonorrhea incidence before and during the COVID-19 pandemic, and whether these changes differed by 2019 ICD per capita public health funding. RESULTS: During the study period, there were 51,230 adolescent cases of chlamydia and 5256 of gonorrhea with most cases in females and older adolescents (age 18-19). Pre-pandemic, chlamydia rates increased over time (Risk ratio (RR) = 1.01, 95 % confidence interval (CI): 1.01-1.01, per month). There was an immediate decrease in chlamydia rates post-pandemic onset (RR = 0.26, 95 % CI: 0.12-0.53) though higher rates were observed with increasing 2019 ICD per capita funding (RR = 1.11, 95 % CI: 1.05-1.17, per dollar of ICD per capita funding, post-pandemic onset). Similar trends were observed for gonorrhea, but estimates had lower precision. CONCLUSION: Higher pre-pandemic 2019 ICD per capita funding may have allowed greater sexual health screening services during the COVID-19 pandemic, potentially mitigating a larger drop in STI detection. Results suggest that higher public health funding may allow for greater resilience of sexual health services during public health emergencies.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".