Impacts of COVID-19 on contraceptive and abortion services in low- and middle-income countries: a scoping review
Bibliographic record
Abstract
The COVID-19 pandemic has disproportionate effects on people living in low- and middle-income countries (LMICs), exacerbating weak health systems. We conducted a scoping review to identify, map, and synthesise studies in LMICs that measured the impact of COVID-19 on demand for, provision of, and access to contraceptive and abortion-related services, and reproductive outcomes of these impacts. Using a pre-established protocol, we searched bibliographic databases (December 2019-February 2021) and key grey literature sources (December 2019-April 2021). Of 71 studies included, the majority (61%) were not peer-reviewed, and 42% were based in Africa, 35% in Asia, 17% were multi-region, and 6% were in Latin America and the Caribbean. Most studies were based on data through June 2020. The magnitude of contraceptive service-related impacts varied widely across 55 studies (24 of which also included information on abortion). Nearly all studies assessing changes over time to contraceptive service provision noted declines of varying magnitude, but severe disruptions were relatively uncommon or of limited duration. Twenty-six studies addressed the impacts of COVID-19 on abortion and postabortion care (PAC). Overall, studies found increases in demand, reductions in provision and increases in barriers to accessing these services. The use of abortion services declined, but the use of PAC was more mixed with some studies finding increases compared to pre-COVID-19 levels. The impacts of COVID-19 varied substantially, including the country context, health service, and population studied. Continued monitoring is needed to assess impacts on these key health services, as the COVID-19 pandemic evolves.
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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 | 0.017 | 0.081 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.021 | 0.023 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".