Costing and cost-effectiveness of Cepheid Xpert HIV -1 Qual Assay using whole blood protocol versus PCR by Abbott Systems in Malawi
Bibliographic record
Abstract
Background Timely diagnosis of HIV in infants and children is an urgent priority. In Malawi, 40,000 infants annually are HIV exposed. However, gold standard polymerase-chain-reaction (PCR) based testing requires centralised laboratories, causing turn-around times (TAT) of 2 to 3 months and significant loss to follow-up. If feasible and acceptable, minimising diagnostic delays through HIV Point-of-care-testing (POCT) may be cost-effective. We assessed whether POCT Cepheid Xpert HIV-1 Qual assay whole blood (XpertHIV) was more cost-effective than PCR. Methods From July-August 2018, 700 PCR Abbott tests using dried blood spots (DBS) were performed on 680 participants who enrolled on the feasibility, acceptability and performance of the XpertHIV study. Newly identified HIV-positive DBS from the 680 participants were retested, so with confirmatory testing of the HIV-positive cases, 700 tests were performed. We conducted a cost-minimisation and cost-effectiveness analysis of XpertHIV against PCR, as the standard of care. A random sample of 200 caregivers from the 680 participants had semi-structured interviews to explore costs from a societal perspective of XpertHIV at Mulanje District Hospital, Malawi. Analysis used TAT as the primary outcome measure. Results were extrapolated from the study period (29 days) to a year (240 working days). Sensitivity analyses characterised individual and joint parameter uncertainty and estimated patient cost per test. Results During the study period, XpertHIV was cost-minimising at $42.34 per test compared to $66.66 for PCR. Over a year, XpertHIV remained cost-minimising at $16.12 compared to PCR at $27.06. From the patient perspective (travel, food, lost productivity), the cost per test of XpertHIV was $2.45. XpertHIV had a mean TAT of 7.10 hours compared to 153.15 hours for PCR. Extrapolates accounting for equipment costs, lab consumables and losses to follow up estimated annual savings of $2,193,538.88 if XpertHIV is used nationally, as opposed to PCR. Conclusions This preliminary evidence suggests that adopting POCT XpertHIV will save time, allowing HIV-exposed infants to receive prompt care and may improve outcomes. The Malawi government will pay less due to XpertHIV's cost savings and associated benefits.
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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 | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".