The International Sexual Health And REproductive Health during COVID-19 (I-SHARE) Study: A Multicountry Analysis of Adults from 30 Countries Prior to and During the Initial Coronavirus Disease 2019 Wave
Bibliographic record
Abstract
BACKGROUND: There is limited evidence to date about changes to sexual and reproductive health (SRH) during the initial wave of coronavirus disease 2019 (COVID-19). To address this gap, our team organized a multicountry, cross-sectional online survey as part of a global consortium. METHODS: Consortium research teams conducted online surveys in 30 countries. Sampling methods included convenience, online panels, and population-representative. Primary outcomes included sexual behaviors, partner violence, and SRH service use, and we compared 3 months prior to and during policy measures to mitigate COVID-19. We conducted meta-analyses for primary outcomes and graded the certainty of the evidence. RESULTS: Among 4546 respondents with casual partners, condom use stayed the same for 3374 (74.4%), and 640 (14.1%) reported a decline. Fewer respondents reported physical or sexual partner violence during COVID-19 measures (1063 of 15 144, 7.0%) compared to before COVID-19 measures (1469 of 15 887, 9.3%). COVID-19 measures impeded access to condoms (933 of 10 790, 8.7%), contraceptives (610 of 8175, 7.5%), and human immunodeficiency virus/sexually transmitted infection (HIV/STI) testing (750 of 1965, 30.7%). Pooled estimates from meta-analysis indicate that during COVID-19 measures, 32.3% (95% confidence interval [CI], 23.9%-42.1%) of people needing HIV/STI testing had hindered access, 4.4% (95% CI, 3.4%-5.4%) experienced partner violence, and 5.8% (95% CI, 5.4%-8.2%) decreased casual partner condom use (moderate certainty of evidence for each outcome). Meta-analysis findings were robust in sensitivity analyses that examined country income level, sample size, and sampling strategy. CONCLUSIONS: Open science methods are feasible to organize research studies as part of emergency responses. The initial COVID-19 wave impacted SRH behaviors and access to services across diverse global settings.
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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 | 0.009 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.007 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".