Processes and dynamics of linkage to care from mobile/outreach and facility-based HIV testing models in hard-to-reach settings in rural Tanzania. Qualitative findings of a mixed methods study
Bibliographic record
Abstract
BACKGROUND: Like other countries, Tanzania instituted mobile and outreach testing approaches to address low HIV testing rates at health facilities and enhance linkage to care. Available evidence from hard-to-reach rural settings of Mbeya region, Tanzania suggests that clients testing HIV+ at facility-based sites are more likely to link to care, and to link sooner, than those testing at mobile sites. This paper (1) describes the populations accessing HIV testing at mobile/outreach and facility-based testing sites, and (2) compares processes and dynamics from testing to linkage to care between these two testing models from the same study context. METHODS: An explanatory sequential mixed-method study (a) reviewed records of all clients (n = 11,773) testing at 8 mobile and 8 facility-based testing sites over 6 months; (b), reviewed guidelines; (c) observed HIV testing sites (n = 10) and Care and Treatment Centers (CTCs) (n = 8); (d) applied questionnaires at 0, 3 and 6 months to a cohort of 1012 HIV newly-diagnosed clients from the 16 sites; and (e) conducted focus group discussions (n = 8) and in-depth qualitative interviews with cohort members (n = 10) and health care providers (n = 20). RESULTS: More clients tested at mobile/outreach than facility-based sites (56% vs 44% of 11,733, p < 0.001). Mobile site clients were more likely to be younger and male (p < 0.001). More clients testing at facility sites were HIV positive (21.5% vs. 7.9% of 11,733, p < 0.001). All sites in both testing models adhered to national HIV testing and care guidelines. Staff at mobile sites showed more proactive efforts to support linkage to care, and clients report favouring the confidentiality of mobile sites to avoid stigma. Clients who tested at mobile/outreach sites faced longer delays and waiting times at treatment sites (CTCs). CONCLUSIONS: Rural mobile/outreach HIV testing sites reach more people than facility based sites but they reach a different clientèle which is less likely to be HIV +ve and appears to be less "linkage-ready". Despite more proactive care and confidentiality at mobile sites, linkage to care is worse than for clients who tested at facility-based sites. Our findings highlight a combination of (a) patient-level factors, including stigma; and (b) well-established procedures and routines for each step between testing and initiation of treatment in facility-based sites. Long waiting times at treatment sites are a further barrier that must be addressed.
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 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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".