An online, open-access, cost comparison tool for presumptive tuberculosis testing using low complexity, automated, nucleic acid amplification tests (LCaNAAT) versus near point-of-care (NPOCs) molecular tests

This paper presents a newly developed, open-access Shiny-based cost comparison tool demonstrating that implementing lower-cost near point-of-care molecular tests as the initial tuberculosis diagnostic can achieve ambitious testing targets at roughly the same cost as current low-complexity automated nucleic acid amplification tests, thereby enabling significant budget savings and improved global access to rapid TB diagnosis.

The Gist

Imagine you are trying to find a few specific needles hidden in a massive, global haystack. Those "needles" are people with tuberculosis (TB), and finding them quickly is crucial to stopping the disease from spreading. For a long time, the only way to find these needles quickly was to use a giant, high-tech metal detector.

The Problem: The Expensive Metal Detector
This "metal detector" is what the paper calls LCaNAAT (the current standard rapid test). It works great, but it's like buying a Ferrari to drive to the grocery store. It costs a fortune to buy, it needs a specialized mechanic (maintenance) to keep running, and it guzzles expensive fuel (consumables). Because of this high price tag, many countries can't afford enough of them to check everyone who needs it.

The New Option: The Reliable Bicycle
Recently, a new type of tool has arrived: the NPOC (near point-of-care test). Think of this as a sturdy, reliable bicycle. It's not as flashy as the Ferrari, but it gets you to the same destination (finding the TB) just as fast. The best part? It costs a fraction of the price to buy, it's easy to fix, and it doesn't need expensive fuel.

The Tool: A "Budget Calculator" App
The authors of this paper built a digital calculator (an online app) to help health officials decide which vehicle to buy. Before, figuring out the costs was like trying to do complex math in your head while riding a bike. Now, they have a user-friendly dashboard where you can plug in your country's numbers.

The app lets you run two different "what-if" scenarios:

1. The "Status Quo" Scenario: What happens if we keep using the expensive Ferrari?
2. The "New Bike" Scenario: What happens if we switch to the affordable bicycles?

The Results: Going Further for Less Money
When the researchers tested this calculator with two imaginary countries (let's call them Country A and Country B), the results were surprising and exciting:

• Country A found that switching to the new tests would save them 38% to 43% of their budget.
• Country B found even bigger savings, between 40% and 55%.

The Big Picture
The main takeaway is simple: You don't have to spend more money to test more people.

By switching from the expensive "Ferrari" tests to the affordable "bicycle" tests, countries can actually test more people for the same amount of money (or even less). It's like realizing that if you stop buying one expensive luxury car, you could buy ten reliable bicycles for your whole family. This allows health programs to reach their ambitious goals of finding every case of TB, faster and cheaper, bringing the world one step closer to stopping the disease entirely.

In a nutshell: This paper introduces a free online tool that proves switching to cheaper, simpler TB tests can save countries huge amounts of money, allowing them to catch more cases and save more lives without breaking the bank.

Technical Summary

Technical Summary: Cost Comparison Tool for TB Diagnostics

1. Problem Statement

Despite the World Health Organization's (WHO) push for universal access to rapid tuberculosis (TB) diagnostics, global scale-up of molecular rapid diagnostics (mWRDs) remains constrained. While Low-Complexity Automated Nucleic Acid Amplification Tests (LCaNAAT) have improved detection rates, their widespread adoption is hindered by high capital expenditures, maintenance requirements, and consumable costs. Conversely, newer Near Point-of-Care (NPOC) molecular tests have emerged with lower costs and attractive global-access pricing, but TB program staff lack flexible tools to accurately assess the budget impact of transitioning from established LCaNAAT strategies to these newer NPOC alternatives.

2. Methodology

The authors developed a dynamic, open-access cost comparison tool to facilitate budget impact analysis. The development process involved the following technical steps:

• Initial Prototyping: A cost calculator was first built in Microsoft Excel for Mac (version 16.91). This version utilized a structured input sheet with standardized labels to organize key parameters.
• Model Architecture: The Excel model employed separate worksheets to define specific diagnostic scenarios and perform calculations, with a summary worksheet aggregating various cost metrics.
• Validation and Migration: After validation, the underlying logic was migrated to R (version 2025.09.1 + 401).
• Application Development: The final tool was deployed as a web-based application using the Shiny framework (app.R). This conversion ensures the tool is accessible globally as a free, open-source resource, allowing users to input country-specific data without requiring local software installation.
• Case Studies: The tool was applied to two hypothetical country case studies (Country A and Country B) to compare current LCaNAAT-based strategies against scenarios where NPOCs serve as the initial diagnostic test. Two distinct scenarios were modeled for each country:
  • Scenario 1: Based on current testing trends.
  • Scenario 2: Based on ambitious testing goals.

3. Key Contributions

• Open-Access Decision Support: The primary contribution is the creation of a flexible, free, and globally accessible online tool that allows TB program managers to model the financial implications of adopting NPOC technology.
• Standardized Cost Modeling: The tool standardizes the comparison between high-capital LCaNAAT systems and lower-cost NPOC systems, accounting for capital, maintenance, and consumable costs.
• Scalable Implementation: By moving from a static Excel file to a Shiny-based R application, the authors have created a scalable solution that can be easily updated with new pricing data or diagnostic parameters as the market evolves.

4. Results

The application of the tool to the hypothetical case studies yielded significant findings regarding cost efficiency:

• Country A:
  • Scenario 1 (Current Trends): Implementing NPOCs resulted in a 43% cost saving compared to LCaNAAT.
  • Scenario 2 (Ambitious Goals): Cost savings were 38%.
• Country B:
  • Scenario 1 (Current Trends): Implementing NPOCs resulted in a 55% cost saving.
  • Scenario 2 (Ambitious Goals): Cost savings were 40.5%.
• Strategic Insight: The analysis demonstrated that countries can achieve ambitious TB testing targets using NPOCs at roughly the same cost (or with significant savings) as current LCaNAAT strategies.

5. Significance

This study highlights the transformative potential of affordable molecular diagnostics in global TB control. By shifting from capital-intensive LCaNAAT systems to lower-cost NPOCs, TB programs can:

• Expand Access: Test and detect more cases within existing or only slightly increased budgets.
• Reduce Financial Barriers: Alleviate the burden of high capital and maintenance costs that currently constrain scale-up.
• Accelerate Progress: Speed up the timeline toward achieving universal access to rapid TB diagnosis, aligning more closely with WHO standards.

The tool serves as a critical bridge between technological innovation (NPOCs) and programmatic implementation, empowering stakeholders to make data-driven decisions that prioritize both fiscal sustainability and public health outcomes.