Impact of COVID-19 on access to and delivery of sexual and reproductive healthcare services in countries with universal healthcare systems: A systematic review
Bibliographic record
Abstract
OBJECTIVES: The COVID-19 pandemic has caused unforeseen impacts on sexual and reproductive healthcare (SRH) services worldwide, and the nature and prevalence of these changes have not been extensively synthesized. We sought to synthesise reported outcomes on the impact of COVID-19 on SRH access and delivery in comparable countries with universal healthcare systems. METHODS: Following PRISMA guidelines, we searched MEDLINE, Embase, PsycInfo, and CINAHL from January 1st, 2020 to June 6th, 2023. Original research was eligible for inclusion if the study reported on COVID-19 and SRH access and/or delivery. Twenty-eight OECD countries with comparable economies and universal healthcare systems were included. We extracted study characteristics, participant characteristics, study design, and outcome variables. The methodological quality of each article was assessed using the Quality Assessment with Diverse Studies (QuADS) tool. The Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines were followed for reporting the results. This study was registered on PROSPERO (#CRD42021245596). SYNTHESIS: Eighty-two studies met inclusion criteria. Findings were qualitatively synthesised into the domains of: antepartum care, intrapartum care, postpartum care, assisted reproductive technologies, abortion access, gynaecological care, sexual health services, and HIV care. Research was concentrated in relatively few countries. Access and delivery were negatively impacted by a variety of factors, including service disruptions, unclear communication regarding policy decisions, decreased timeliness of care, and fear of COVID-19 exposure. Across outpatient services, providers favoured models of care that avoided in-person appointments. Hospitals prioritized models of care that reduced time and number of people in hospital and aerosol-generating environments. CONCLUSIONS: Overall, studies demonstrated reduced access and delivery across most domains of SRH services during COVID-19. Variations in service restrictions and accommodations were heterogeneous within countries and between institutions. Future work should examine long-term impacts of COVID-19, underserved populations, and underrepresented countries.
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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 | 0.025 | 0.099 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.012 |
| Bibliometrics | 0.015 | 0.018 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".