“Because of COVID…”: The impacts of COVID-19 on First Nation people accessing the HIV cascade of care in Manitoba, Canada
Bibliographic record
Abstract
BACKGROUND: The COVID-19 pandemic (March 2020-May 2023) had a profound effect around the world with vulnerable people being particularly affected, including worsening existing health inequalities. This article explores the impact of the pandemic on health services for First Nations people living with HIV (FN-PWLE) in Manitoba, Canada. This study investigated perceptions of both health care providers and FN-PWLE through qualitative interviews occurring between July 2020 and February 2022 to understand their experience and identify lessons learned that could be translated into health system changes. METHODS: Using a qualitative, participatory-action, intentional decolonizing approach for this study we included an Indigenous knowledge keeper and Indigenous research associates with lived experience as part of the study team. A total of twenty-five [25] in-depth semi-structured interviews were conducted with eleven healthcare providers (HCPs) and fourteen First Nation people with lived HIV experience (FN-PWLE). In total, 18/25 or 72% of the study participants self-identified as First Nation people. RESULTS: The COVID-19 pandemic negatively impacted health services access for FN-PWLE, a) disrupted relationships between FN-PWLE and healthcare providers, b) disrupted access to testing, in-person appointments, and medications, and c) intersectional stigma was compounded. Though, the COVID-19 pandemic also led to positive effects, including the creation of innovative solutions for the health system overall. CONCLUSIONS: The COVID-19 pandemic exaggerated pre-existing barriers and facilitators for Manitoba FN-PWLE accessing and using the healthcare system. COVID-19 impacted health system facilitators such as relationships and supports, particularly for First Nation people who are structurally disadvantaged and needing more wrap-around care to address social determinants of health. Innovations during times of crisis, included novel ways to improve access to care and medications, illustrated how the health system can quickly provide solutions to long-standing barriers, especially for geographical barriers. Lessons learned from the COVID-19 pandemic should be considered for improvements to the health system's HIV cascade of care for FN-PWLE and other health system improvements for First Nations people with other chronic diseases and conditions. Finally, this study illustrates the value of qualitative and First Nation decolonizing research methods. Further studies are needed, working together with First Nations organizations and communities, to apply these recommendations and innovations to change health care and people's lives.
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.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.024 | 0.007 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".