Response strategies for promoting gender equality in public health emergencies: a rapid scoping review
Bibliographic record
Abstract
OBJECTIVES: The COVID-19 pandemic threatens to widen existing gender inequities worldwide. A growing body of literature assesses the harmful consequences of public health emergencies (PHEs) for women and girls; however, evidence of what works to alleviate such impacts is limited. To inform viable mitigation strategies, we reviewed the evidence on gender-based interventions implemented in PHEs, including disease outbreaks and natural disasters. METHODS: We conducted a rapid scoping review to identify eligible studies by systematically searching the databases MEDLINE, Global Health and Web of Science with the latest search update on 28 May 2021. We used the Sustainable Development Goals as a guiding framework to identify eligible outcomes of gender (in)equality. RESULTS: Out of 13 920 records, 16 studies met our eligibility criteria. These included experimental (3), cohort (2), case-control (3) and cross-sectional (9) studies conducted in the context of natural disasters (earthquakes, droughts and storms) or epidemics (Zika, Ebola and COVID-19). Six studies were implemented in Asia, seven in North/Central America and three in Africa. Interventions included economic empowerment programmes (5); health promotion, largely focused on reproductive health (10); and a postearthquake resettlement programme (1). Included studies assessed gender-based outcomes in the domains of sexual and reproductive health, equal opportunities, access to economic resources, violence and health. There was a dearth of evidence for other outcome domains relevant to gender equity such as harmful practices, sanitation and hygiene practices, workplace discrimination and unpaid work. Economic empowerment interventions showed promise in promoting women's and girls' economic and educational opportunities as well as their sexual and reproductive health during PHEs. However, some programme beneficiaries may be at risk of experiencing unintended harms such as an increase in domestic violence. Focused reproductive health promotion may also be an effective strategy for supporting women's sexual and reproductive health, although additional experimental evidence is needed. CONCLUSIONS: This study identified critical evidence gaps to guide future research on approaches to alleviating gender inequities during PHEs. We further highlight that interventions to promote gender equity in PHEs should take into account possible harmful side effects such as increased gender-based violence. REVIEW REGISTRATION: DOI 10.17605/OSF.IO/8HKFD.
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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 | 0.039 | 0.110 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.026 | 0.015 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".