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Study 12 of 16LL-37 literatureThe Lancet. Microbe · ObservationalTop journal2026

Minimal supply chain and forecasting testing volumes for clinical bacteriology laboratories in resource-limited settings for individual patient care: a costing study.

The mean consumable cost per hospital admission for bacteriology testing in resource-limited settings is estimated at $6·23 in the strict minimum scenario.

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this study against the rest of the ll-37 corpus
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Preclinical
7
Observational · this one
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Open-label
2
Randomised
2
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Summary and findings

This study aimed to assemble a costed consensus list of minimum equipment and consumables for clinical bacteriology laboratories in resource-limited settings. It involved experts from various regions and utilized data from laboratories in Benin and Ethiopia. The findings provide insights into the costs associated with establishing and operating such laboratories.

How much of this paper we could read: full text read (0.70). We had a clear abstract, so the summary below closely tracks the paper. What this means →
$6·23 mean consumable cost per hospital admission in the strict minimum scenario, 95% uncertainty range 5·42-7·54.2026

Abstract

The authors’ words, as The Lancet. Microbe supplied them

<h4>Background</h4>Inadequate access to clinical bacteriology testing in low-resource settings compromises individual patient care and contributes to antimicrobial resistance. Funders, policy makers, and health administrators working to expand bacteriology testing in sub-Saharan Africa require evidence-based guidance. The aim of this study was to assemble a costed consensus list of minimum equipment and consumables required to implement and operate a functional clinical bacteriology laboratory in secondary and tertiary care hospitals in sub-Saharan Africa, to guide funders and health administrators.<h4>Methods</h4>A consensus list of minimum materials for diagnosing bloodstream infections was assembled by experts from Africa, North America, and Europe, representing academia, funders, and implementers. A modelling study was performed to estimate costs across several testing scenarios developed using a formal framework for forecasting testing volumes and reagent usage. Outcomes assessed were consumable costs per hospital admission and per investigation of septic episode and costs of non-recurring items at the time of establishment of a laboratory. Data from two accredited bacteriology laboratories providing individual patient care in Benin and Ethiopia were used to inform expected positivity rates, reagent usage, and testing volumes. Supplier quotes from North America and Europe were used to provide average unit costs and 95% uncertainty ranges.<h4>Findings</h4>The estimated mean consumable cost per hospital admission was, in 2023 USD, $6·23 (95% uncertainty range 5·42-7·54) in the strict minimum scenario and $10·86 (9·82-12·31) in the standard scenario. The mean cost for the minimal equipment list at the time of establishment of a laboratory was estimated at $30 763 (28 403-33 043; plus an annual equipment maintenance cost of $3076 [2840-3304]), which includes purchase of commercial quality control strains and other non-recurring consumables. Available data suggest that costs from national distributors in sub-Saharan Africa could be three-fold higher than those described. Finally, we provide a transparent and adaptable basis for estimating minimal testing volumes and reagent usage, enabling tailored procurement planning in regions currently without clinical bacteriology laboratories.<h4>Interpretation</h4>These results inform national antimicrobial resistance action plans on supply procurement, costing, and the ability to benchmark and forecast minimal acceptable testing volumes for the diagnosis of bloodstream infections for individual patient care.<h4>Funding</h4>Fonds de recherche du Québec - Santé.

Background

This paper addresses the need for improved access to clinical bacteriology testing in low-resource settings, which is crucial for individual patient care and combating antimicrobial resistance. Prior knowledge indicates that inadequate testing capabilities hinder effective diagnosis and treatment. This study is significant as it provides a structured approach to estimating the costs and resources needed to establish functional bacteriology laboratories in sub-Saharan Africa.

Methods

A consensus list of minimum materials was developed by experts from Africa, North America, and Europe. The study utilized a modeling approach to estimate costs related to various testing scenarios, focusing on consumable costs per hospital admission and the costs of establishing a laboratory. Data were sourced from two accredited bacteriology laboratories in Benin and Ethiopia, with supplier quotes from North America and Europe used for cost estimation.

Results

The estimated mean consumable cost per hospital admission was $6·23 in the strict minimum scenario (95% uncertainty range 5·42-7·54) and $10·86 in the standard scenario (95% uncertainty range 9·82-12·31). The mean cost for the minimal equipment list was estimated at $30 763 (95% uncertainty range 28 403-33 043), with an annual maintenance cost of $3076 (95% uncertainty range 2840-3304).

Interpretation

These findings provide a basis for understanding the financial implications of establishing bacteriology laboratories in resource-limited settings. While the costs are statistically significant, their clinical relevance may vary based on local economic conditions and healthcare priorities. The potential for costs to be three-fold higher in local contexts presents a significant confound that limits the generalizability of the results.

Key findings

  • $6·23 mean consumable cost per hospital admission in the strict minimum scenario, 95% uncertainty range 5·42-7·54.
  • $10·86 mean consumable cost per hospital admission in the standard scenario, 95% uncertainty range 9·82-12·31.
  • $30 763 estimated mean cost for minimal equipment list at establishment of a laboratory, 95% uncertainty range 28 403-33 043.
  • $3076 annual equipment maintenance cost, 95% uncertainty range 2840-3304.
  • Costs from national distributors in sub-Saharan Africa could be three-fold higher than those described.

Limitations

  • Estimates based on modeling may not reflect actual costs.
  • Findings may not be universally applicable across all sub-Saharan African contexts.
  • Potential for costs to be three-fold higher from local distributors.

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