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Record W4200343173 · doi:10.1186/s12978-021-01307-4

Looking ahead in the COVID-19 pandemic: emerging lessons learned for sexual and reproductive health services in low- and middle-income countries

2021· editorial· en· W4200343173 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueReproductive Health · 2021
Typeeditorial
Languageen
FieldMedicine
TopicCOVID-19 Impact on Reproduction
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsReproductive healthPandemicPsychological interventionReproductive medicineMedicineService (business)Service delivery frameworkNursingBusinessEnvironmental healthCoronavirus disease 2019 (COVID-19)PopulationPregnancyMarketing

Abstract

fetched live from OpenAlex

The COVID-19 pandemic has caused widespread disruption to essential health service provision globally, including in low- and middle-income countries (LMICs). Recognising the criticality of sexual and reproductive health (SRH) services, we review the actual reported impact of the COVID-19 pandemic on SRH service provision and evidence of adaptations that have been implemented to date. Across LMICs, the available data suggests that there was a reduction in access to SRH services, including family planning (FP) counselling and contraception access, and safe abortion during the early phase of the pandemic, especially when movement restrictions were in place. However, services were quickly restored, or alternatives to service provision (adaptations) were explored in many LMICs. Cases of gender-based violence (GBV) increased, with one in two women reporting that they have or know a woman who has experienced violence since the beginning of the pandemic. As per available evidence, many adaptations that have been implemented to date have been digitised, focused on getting SRH services closer to women. Through the pandemic, several LMIC governments have provided guidelines to support SRH service delivery. In addition, non-governmental organisations working in SRH programming have played significant roles in ensuring SRH services have been sustained by implementing several interventions at different levels of scale and to varying success. Most adaptations have focused on FP, with limited attention placed on GBV. Many adaptations have been implemented based on guidance and best practices and, in many cases, leveraged evidence-based interventions. However, some adaptations appear to have simply been the sensible thing to do. Where evaluations have been carried out, many have highlighted increased outputs and efficiency following the implementation of various adaptations. However, there is limited published evidence on their effectiveness, cost, value for money, acceptability, feasibility, and sustainability. In addition, the pandemic has been viewed as a homogenous event without recognising its troughs and waves or disentangling effects of response measures such as lockdowns from the pandemic itself. As the pandemic continues, neglected SRH services like those targeting GBV need to be urgently scaled up, and those being implemented with any adaptations should be rigorously tested.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.017
metaresearch head score (Gemma)0.014
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.697
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0170.014
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.090
GPT teacher head0.444
Teacher spread0.354 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it