The Impact of COVID-19 Restrictions on the Health and Well-being of Women Living in Informal Settlements in Uganda.
Bibliographic record
Abstract
Abstract Background: The COVID-19 pandemic significantly impacted Uganda, with the first case reported in March 2020, resulting in extensive public health restrictions, including a lockdown, curfew, and closure of schools and workplaces. Urban residents, particularly those living in poverty in informal settlements, faced heightened challenges due to inadequate access to basic services, financial hardships, and increased caregiving responsibilities, especially for women. Women faced heightened risks of gender-based violence and engaged in transactional sex as coping mechanisms. This study explored the strategies used by women in Kampala and Mbale cities to meet basic needs during the pandemic and their implications for HIV infection vulnerability. Methods: Researchers conducted in-depth discussions with 282 women from various age groups in Kampala and Mbale's largest informal settlements, gathering insights into their pandemic experiences. These discussions, held in local languages, explored women's social, family, and financial challenges, as well as their perceptions of HIV risks. Transcripts were translated by local language experts before analysis. The team analyzed the transcripts using NVivo version 14 software, identifying patterns and themes that revealed survival strategies employed by women. Results: The study identified three interconnected themes that capture the complex strategies and challenges faced by women in informal settlements in Kampala and Mbale during the COVID-19 pandemic. Women struggled to cope with financial hardships and increased caregiving responsibilities, often resorting to desperate measures like transactional sex to survive, despite their resilience. The pandemic exacerbated vulnerabilities, heightening risks of HIV transmission and mental health issues, particularly among women living in poverty. While support networks provided some relief, they often fell short of meeting the diverse needs of women in these communities. Conclusions: The study shows that women in Uganda's informal settlements demonstrated resilience by taking on new roles and engaging in trading, but their reliance on transactional sex revealed stark power imbalances, increasing their vulnerability to gender-based violence, unintended pregnancies, and HIV infection. This highlights the urgent need for targeted interventions that address the complex challenges women face in crisis situations, which could enhance their resilience and alleviate their multiple struggles, with valuable lessons for similar contexts in low- and middle-income countries.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".