Evidence map›Paper›PMID 31515967›Full record

ArticleJournal of the International AIDS Society2019

Monitoring viral load for the last mile: what will it cost?

Brooke E Nichols, Sarah J Girdwood, Thomas Crompton, Lynsey Stewart-Isherwood, Leigh Berrie, Dorman Chimhamhiwa, Crispin Moyo, John Kuehnle, Wendy Stevens, Sydney Rosen and 1 more

Abstract read
In one paragraph

Article in Journal of the International AIDS Society, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

23 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Brooke E NicholsDepartment of Global Health, School of Public Health, Boston University, Boston, MA, USA.ORCID 0000-0003-4682-4999
Sarah J GirdwoodHealth Economics and Epidemiology Research Office, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.ORCID 0000-0002-8492-028X
Thomas CromptonGIS Mapping Department, Right to Care, Johannesburg, South Africa.
Lynsey Stewart-IsherwoodNational Health Laboratory Service, Johannesburg, South Africa.
Leigh BerrieNational Health Laboratory Service, Johannesburg, South Africa.
Dorman ChimhamhiwaGIS Mapping Department, Right to Care, Johannesburg, South Africa.
Crispin MoyoEQUIP Zambia, Lusaka, Zambia.
John KuehnleUnited States Agency for International Development, Lusaka, Zambia.
Wendy StevensNational Health Laboratory Service, Johannesburg, South Africa.
Sydney RosenDepartment of Global Health, School of Public Health, Boston University, Boston, MA, USA.
EQUIP Health

Funding

Translational ScienceP30AI042853 · NIAID · MIRIAM HOSPITAL · PI LARRY K BROWN · 1998 to 2026
$51.7M
NIAID NIH HHS P30 AI042853
6 · The paper itself

Abstract

introductionRoutine viral load testing is the WHO-recommended method for monitoring HIV-infected patients on ART, and many countries are rapidly scaling up testing capacity at centralized laboratories. Providing testing access to the most remote populations and facilities (the "last mile") is especially challenging. Using a geospatial optimization model, we estimated the incremental costs of accessing the most remote 20% of patients in Zambia by expanding the transportation network required to bring blood samples from ART clinics to centralized laboratories and return results to clinics.

methodsThe model first optimized a sample transportation network (STN) that can transport 80% of anticipated sample volumes to centralized viral load testing laboratories on a daily or weekly basis, in line with Zambia's 2020 targets. Data incorporated into the model included the location and infrastructure of all health facilities providing ART, location of laboratories, measured distances and drive times between the two, expected future viral load demand by health facility, and local cost estimates. We then continued to expand the modelled STN in 5% increments until 100% of all samples could be collected. RESULTS AND DISCUSSION: The cost per viral load test when reaching 80% patient volumes using centralized viral load testing was a median of $18.99. With an expanded STN, the incremental cost per test rose to $20.29 for 80% to 85% and $20.52 for 85% to 90%. Above 90% coverage, the incremental cost per test increased substantially to $31.57 for 90% to 95% and $51.95 for 95% to 100%. The high numbers of kilometres driven per sample transported and large number of vehicles needed increase costs dramatically for reaching the clinics that serve the last 5% of patients.

conclusionsProviding sample transport services to the most remote clinics in low- and middle-income countries is likely to be cost-prohibitive. Other strategies are needed to reduce the cost and increase the feasibility of making viral load monitoring available to the last 10% of patients. The cost of alternative methods, such as optimal point-of-care viral load equipment placement and usage, dried blood/plasma spot specimen utilization, or use of drones in geographically remote facilities, should be evaluated.

Indexed as

Cost of IllnessHIV-1HIV InfectionsHumansPoint-of-Care SystemsViral LoadZambiacost modellinggeospatial modellinghealth systemspatient monitoringviral loadviral load scale-up

Identifiers

PMID31515967
PMCPMC6742838

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.