The impact of COVID-19 on sexual and reproductive health service access and provision in Botswana: a cross-sectional study
Bibliographic record
Abstract
Abstract Introduction : Measures intended to curb COVID-19 transmission and mortality may have indirect effects on access to, provision, and uptake of essential healthcare services including sexual and reproductive health (SRH). These indirect effects may disproportionately affect women and vulnerable groups through impaired delivery of contraception, antenatal and HIV care services. In Botswana, SRH needs were significant prior to the onset of the COVID-19 pandemic, with a high HIV prevalence, high rates of unintended pregnancy and a high maternal mortality ratio. We aimed to understand the impact of COVID-19 restrictions on SRH access and provision in Botswana. Methods : This observational, cross-sectional study was conducted in Botswana over a 5-week period in early 2021. Data were collected through an online survey disseminated as part of the International Sexual Health and REproductive Health (I-SHARE) Survey. Respondents answered questions on SRH, including sexual behaviours, access to contraception, antenatal and postnatal care and HIV management, in the 3 months before and during Botswana's COVID-19 restrictions. Results : 409 participants (82% female) completed the survey. 87% (n = 356) reported following COVID-19 restrictions 'a lot' or 'very strictly'. 54% (n = 221) reported worsening of their household economic situation since the onset of COVID-19 restrictions, and a quarter reported a relationship breakdown with their partner. Since the onset of COVID-19 restrictions, respondents reported difficulties in accessing contraception (15%); STI/HIV treatment (15%) and maternity services (29%). Reasons for hindered access to SRH services included movement restrictions or lack of transport; closure of, inaccessibility of, or lack of appropriately-trained staff at healthcare facilities; and fear of acquiring COVID-19. Contraception use reflected that of previous studies conducted in Botswana with condom use predominating (49%) and limited long-acting reversible contraceptive coverage (13%). Conclusion : Botswana's COVID-19 restrictions had indirect effects on the breadth of SRH services studied, resulting in reduced access to contraception, maternity care and HIV treatment. Prioritisation of SRH services in future national emergencies may minimize disruption to SRH care and prevent avoidable harms including unintended pregnancies, maternal and neonatal mortality, and HIV transmission. Achieving better coverage of long-acting contraceptives may help to mitigate against disruptions to contraception access.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".