Impact of Ebola and COVID-19 pandemic on patterns in uptake of short-acting and long-acting contraceptive methods in Sierra Leone: a country-wide observational study
Bibliographic record
Abstract
Abstract Background The Ebola epidemic and COVID-19 pandemic disrupted essential healthcare services globally, including family planning, but the extent of disruptions in Sierra Leone is largely unknown. This study aimed to evaluates the impact of these crises on the uptake of contraceptive methods—short-acting contraceptives (SAC) and long-acting reversible contraceptives (LARC)— among adolescent girls and women ages 10-45 years in Sierra Leone from 2013 to 2022. Methods We conducted a retrospective, cross-sectional study using aggregated DHIS2 data from adolescent girls and women aged 10-45 years. We describe and visualize the trends in the uptake of SAC and LARC before Ebola (March 2013 to April 2014), during Ebola (May 2014 to February 2016), after Ebola and before COVID-19 (March 2016 to February 2020), and during COVID-19 (March 2020 to February 2022). Proportional shifts and age-specific patterns were assessed to identify changes in contraceptive preferences. Results During the Ebola outbreak (2014–2016), SAC uptake declined temporarily while LARC uptake modestly increased. A recovery in SAC uptake followed during the inter-epidemic period (2016–2019). Conversely, the COVID-19 pandemic (2020–2022) saw an initial spike in SAC uptake, which subsequently returned to pre-pandemic levels. In contrast, LARC uptake consistently increased throughout both pandemics and the post-pandemic period. Notably, a proportional shift toward LARC methods was observed. Trends across age groups were variable, with adolescents demonstrating resilience in their use of contraceptives during the COVID-19 pandemic. Conclusion LARC services demonstrated remarkable stability during health emergencies, underscoring the resilience of long-term methods and the adaptability of women in making informed choices about their reproductive health amidst disruptions. These findings highlight the importance of strengthening healthcare systems to ensure continued access to reliable contraceptive options, particularly during crises.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".