Evidence map›Paper›PMID 34275875›Full record

ArticleBMJ global health2021

Modelling costs of community-based HIV self-testing programmes in Southern Africa at scale: an econometric cost function analysis across five countries.

Marc d'Elbée, Gabriela B Gomez, Linda Alinafe Sande, Lawrence Mwenge, Collin Mangenah, Cheryl Johnson, Graham F Medley, Melissa Neuman, Karin Hatzold, Elizabeth Lucy Corbett and 2 more

Abstract read
In one paragraph

Article in BMJ global health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–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

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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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

12 authors.

Marc d'ElbéeDepartment of Global Health and Development, London School of Hygiene & Tropical Medicine, London, UK marc.delbee@lshtm.ac.uk.
Gabriela B GomezDepartment of Global Health and Development, London School of Hygiene & Tropical Medicine, London, UK.
Linda Alinafe SandeDepartment of Global Health and Development, London School of Hygiene & Tropical Medicine, London, UK.ORCID 0000-0002-4246-5338
Lawrence MwengeZambart, Lusaka, Zambia.
Collin MangenahDepartment of Health Economics, Centre for Sexual Health HIV/AIDS Research, Harare, Zimbabwe.ORCID 0000-0002-0733-0622
Cheryl JohnsonGlobal HIV, Hepatitis and STI Programme, World Health Organisation, Geneva, Switzerland.
Graham F MedleyDepartment of Global Health and Development, London School of Hygiene & Tropical Medicine, London, UK.
Melissa NeumanMRC International Statistics and Epidemiology Group, London School of Hygiene & Tropical Medicine, London, UK.ORCID 0000-0002-8870-6504
Karin HatzoldPopulation Services International, Washington, DC, USA.
Elizabeth Lucy CorbettDepartment of HIV/AIDS & TB, Malawi-Liverpool-Wellcome Trust Clinical Research Programme, Blantyre, Malawi.
Gesine Meyer-RathDepartment of Internal Medicine, Health Economics and Epidemiology Research Office (HE2RO) - University of the Witwatersrand, Johannesburg, South Africa.
Fern Terris-PrestholtDepartment of Global Health and Development, London School of Hygiene & Tropical Medicine, London, UK.

Funding

Medical Research Council MR/R010161/1World Health Organization 001
6 · The paper itself

Abstract

backgroundFollowing success demonstrated with the HIV Self-Testing AfRica Initiative, HIV self-testing (HIVST) is being added to national HIV testing strategies in Southern Africa. An analysis of the costs of scaling up HIVST is needed to inform national plans, but there is a dearth of evidence on methods for forecasting costs at scale from pilot projects. Econometric cost functions (ECFs) apply statistical inference to predict costs; however, we often do not have the luxury of collecting large amounts of location-specific data. We fit an ECF to identify key drivers of costs, then use a simpler model to guide cost projections at scale.

methodsWe estimated the full economic costs of community-based HIVST distribution in 92 locales across Malawi, Zambia, Zimbabwe, South Africa and Lesotho between June 2016 and June 2019. We fitted a cost function with determinants related to scale, locales organisational and environmental characteristics, target populations, and per capita Growth Domestic Product (GDP). We used models differing in data intensity to predict costs at scale. We compared predicted estimates with scale-up costs in Lesotho observed over a 2-year period.

resultsThe scale of distribution, type of community-based intervention, percentage of kits distributed to men, distance from implementer's warehouse and per capita GDP predicted average costs per HIVST kit distributed. Our model simplification approach showed that a parsimonious model could predict costs without losing accuracy. Overall, ECF showed a good predictive capacity, that is, forecast costs were close to observed costs. However, at larger scale, variations of programme efficiency over time (number of kits distributed per agent monthly) could potentially influence cost predictions. DISCUSSION: Our empirical cost function can inform community-based HIVST scale-up in Southern African countries. Our findings suggest that a parsimonious ECF can be used to forecast costs at scale in the context of financial planning and budgeting.

Indexed as

HIV InfectionsSelf-TestingAfrica, SouthernHumansMalawiMaleMass Screeninghealth economicshealth services researchHIV

Identifiers

PMID34275875
PMCPMC8287624

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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.