New Manual Quantitative Polymerase Chain Reaction Assay Validated on Tongue Swabs Collected and Processed in Uganda Shows Sensitivity That Rivals Sputum-based Molecular Tuberculosis Diagnostics.

BACKGROUND: Sputum-based testing is a barrier to increasing access to molecular diagnostics for tuberculosis (TB). Many people with TB are unable to produce sputum, and sputum processing increases assay complexity and cost. Tongue swabs are emerging as an alternative to sputum, but performance limits are uncertain. METHODS: From June 2022 to July 2023, we enrolled 397 consecutive adults with cough >2 weeks at 2 health centers in Kampala, Uganda. We collected demographic and clinical information, sputum for TB testing (Xpert MTB/RIF Ultra and 2 liquid cultures), and tongue swabs for same-day quantitative polymerase chain reaction (qPCR) testing. We evaluated tongue swab qPCR diagnostic accuracy versus sputum TB test results, quantified TB targets per swab, assessed the impact of serial swabbing, and compared 2 swab types (Copan FLOQSWAB and Steripack spun polyester). RESULTS: Among 397 participants, 43.1% were female, median age was 33 years, 23.5% were diagnosed with human immunodeficiency virus, and 32.0% had confirmed TB. Sputum Xpert Ultra and tongue swab qPCR results were concordant for 98.2% (95% confidence interval [CI]: 96.2-99.1) of participants. Tongue swab qPCR sensitivity was 92.6% (95% CI: 86.5 to 96.0) and specificity was 99.1% (95% CI: 96.9 to 99.8) versus microbiological reference standard. A single tongue swab recovered a 7-log range of TB copies, with a decreasing recovery trend among 4 serial swabs. Swab types performed equivalently. CONCLUSIONS: Tongue swabs are a promising alternative to sputum for molecular diagnosis of TB, with sensitivity approaching sputum-based molecular tests. Our results provide valuable insights for developing successful tongue swab-based TB diagnostics.

New manual qPCR assay validated on tongue swabs collected and processed in Uganda shows sensitivity that rivals sputum-based molecular TB diagnostics.

Background: Reliance on sputum-based testing is a key barrier to increasing access to molecular diagnostics for tuberculosis (TB). Many people with TB are unable to produce and sputum processing increases the complexity and cost of molecular assays. Tongue swabs are emerging as an alternative to sputum, but performance limits are uncertain. Methods: From June 2022 to July 2023, we enrolled 397 consecutive adults with cough >2 weeks at two health centers in Kampala, Uganda. We collected routine demographic and clinical information, sputum for routine TB testing (one Xpert MTB/RIF Ultra® and two liquid cultures), and up to four tongue swabs for same-day qPCR. We evaluated tongue swab qPCR diagnostic accuracy in reference to sputum TB test results, quantified TB targets per swab, assessed the impact of serial swabbing, and compared two swab types (Copan FLOQSWAB® and Steripack® spun polyester swabs). Results: Among 397 participants, 43.1% were female, median age was 33 years, 23.5% were living with HIV (PLHIV) and 32.3% had confirmed TB. Sputum Xpert Ultra and tongue swab qPCR results were concordant for 98.2% [96.2-99.1] of participants. Tongue swab qPCR sensitivity was 91.0% [84.6-94.9] and specificity 98.9% [96.2-99.8] vs. microbiological reference standard (MRS). A single tongue swab recovered a seven-log range of TB copies, with a decreasing recovery trend among four serial swabs. We found no difference between swab types. Conclusions: Tongue swabs show promise as an alternative to sputum for TB diagnosis, with sensitivity approaching sputum-based molecular tests. Our results provide valuable insights for developing successful tongue swab-based TB diagnostics.

A microfluidic device and instrument prototypes for the detection of Escherichia coli in water samples using a phage-based bioluminescence assay.

Current quantification methods of Escherichia coli (E. coli) contamination in water samples involve long incubation, laboratory equipment and facilities, or complex processes that require specialized training for accurate operation and interpretation. To address these limitations, we have developed a microfluidic device and portable instrument prototypes capable of performing a rapid and highly sensitive bacteriophage-based assay to detect E. coli cells with detection limit comparable to traditional methods in a fraction of the time. The microfluidic device combines membrane filtration and selective enrichment using T7-NanoLuc-CBM, a genetically engineered bacteriophage, to identify 4.1 E. coli CFU in 100 mL of drinking water within 5.5 hours. The microfluidic device was designed and tested to process up to 100 mL of real-world drinking water samples with turbidities below 10 NTU. Prototypes of custom instrumentation, compatible with our valveless microfluidic device and capable of performing all of the assay's units of operation with minimal user intervention, demonstrated similar assay performance to that obtained on the benchtop assay. This research is the first step towards a faster, portable, and semi-automated, phage-based microfluidic platform for improved in-field water quality monitoring in low-resource settings.

A Novel Malaria Lateral Flow Assay for Detecting Plasmodium falciparum Lactate Dehydrogenase in Busia, Uganda.

Rapid diagnostic tests (RDTs) for Plasmodium falciparum commonly detect histidine-rich protein 2 (HRP-2), but HRP-2 deletions are increasingly recognized. We evaluated a prototype test detecting parasite lactate dehydrogenase (pLDH) and compared it to commercially available RDTs at a health facility in Uganda, using quantitative polymerase chain reaction as a gold standard. The prototype pLDH test had a high sensitivity for infections with at least 100 parasites/µL (98%), comparable to HRP-2, and greater than an existing pLDH RDT (89%). Specificity for the prototype test was 99.5%, which is greater than the HRP-2 tests (93-95%). Therefore, the prototype pLDH test may be an attractive alternative malaria diagnostic.

Automated liquid handling robot for rapid lateral flow assay development.

The lateral flow assay (LFA) is one of the most popular technologies on the point-of-care diagnostics market due to its low cost and ease of use, with applications ranging from pregnancy to environmental toxins to infectious disease. While the use of these tests is relatively straightforward, significant development time and effort are required to create tests that are both sensitive and specific. Workflows to guide the LFA development process exist but moving from target selection to an LFA that is ready for field testing can be labor intensive, resource heavy, and time consuming. To reduce the cost and the duration of the LFA development process, we introduce a novel development platform centered on the flexibility, speed, and throughput of an automated robotic liquid handling system. The system comprises LFA-specific hardware and software that enable large optimization experiments with discrete and continuous variables such as antibody pair selection or reagent concentration. Initial validation of the platform was demonstrated during development of a malaria LFA but was readily expanded to encompass development of SARS-CoV-2 and Mycobacterium tuberculosis LFAs. The validity of the platform, where optimization experiments are run directly on LFAs rather than in solution, was based on a direct comparison between the robotic system and a more traditional ELISA-like method. By minimizing hands-on time, maximizing experiment size, and enabling improved reproducibility, the robotic system improved the quality and quantity of LFA assay development efforts.

A SARS-CoV-2 coronavirus nucleocapsid protein antigen-detecting lateral flow assay.

Inexpensive, simple, rapid diagnostics are necessary for efficient detection, treatment, and mitigation of COVID-19. Assays for SARS-CoV2 using reverse transcription polymerase chain reaction (RT-PCR) offer good sensitivity and excellent specificity, but are expensive, slowed by transport to centralized testing laboratories, and often unavailable. Antigen-based assays are inexpensive and can be rapidly mass-produced and deployed at point-of-care, with lateral flow assays (LFAs) being the most common format. While various manufacturers have produced commercially available SARS-Cov2 antigen LFAs, access to validated tests remains difficult or cost prohibitive in low-and middle-income countries. Herein, we present a visually read open-access LFA (OA-LFA) using commercially-available antibodies and materials for the detection of SARS-CoV-2. The LFA yielded a Limit of Detection (LOD) of 4 TCID50/swab of gamma irradiated SARS-CoV-2 virus, meeting the acceptable analytical sensitivity outlined by in World Health Organization target product profile. The open-source architecture presented in this manuscript provides a template for manufacturers around the globe to rapidly design a SARS-CoV2 antigen test.

Antibody Screening Results for Anti-Nucleocapsid Antibodies Toward the Development of a Lateral Flow Assay to Detect SARS-CoV-2 Nucleocapsid Protein.

The global COVID-19 pandemic has created an urgent demand for large numbers of inexpensive, accurate, rapid, point-of-care diagnostic tests. Analyte-based assays are suitably rapid and inexpensive and can be rapidly mass-produced, but for sufficiently accurate performance, they require highly optimized antibodies and assay conditions. We used an automated liquid handling system, customized to handle arrays of lateral flow (immuno)assays (LFAs) in a high-throughput screen, to identify anti-nucleocapsid antibodies that will perform optimally in an LFA. We tested 1021 anti-nucleocapsid antibody pairs as LFA capture and detection reagents with the goal of highlighting pairs that have the greatest affinity for the nucleocapsid protein of SARS-CoV-2 within the LFA format. In contrast to traditional antibody screening methods (e.g., ELISA, bio-layer interferometry), the method described here integrates real-time reaction kinetics with transport in, and immobilization directly onto, nitrocellulose. We have identified several candidate antibody pairs that are suitable for further development of an LFA for SARS-CoV-2.

Screening Antibodies Raised against the Spike Glycoprotein of SARS-CoV-2 to Support the Development of Rapid Antigen Assays.

Severe acute respiratory coronavirus-2 (SARS-CoV-2) is a novel viral pathogen and therefore a challenge to accurately diagnose infection. Asymptomatic cases are common and so it is difficult to accurately identify infected cases to support surveillance and case detection. Diagnostic test developers are working to meet the global demand for accurate and rapid diagnostic tests to support disease management. However, the focus of many of these has been on molecular diagnostic tests, and more recently serologic tests, for use in primarily high-income countries. Low- and middle-income countries typically have very limited access to molecular diagnostic testing due to fewer resources. Serologic testing is an inappropriate surrogate as the early stages of infection are not detected and misdiagnosis will promote continued transmission. Detection of infection via direct antigen testing may allow for earlier diagnosis provided such a method is sensitive. Leading SARS-CoV-2 biomarkers include spike protein, nucleocapsid protein, envelope protein, and membrane protein. This research focuses on antibodies to SARS-CoV-2 spike protein due to the number of monoclonal antibodies that have been developed for therapeutic research but also have potential diagnostic value. In this study, we assessed the performance of antibodies to the spike glycoprotein, acquired from both commercial and private groups in multiplexed liquid immunoassays, with concurrent testing via a half-strip lateral flow assays (LFA) to indicate antibodies with potential in LFA development. These processes allow for the selection of pairs of high-affinity antispike antibodies that are suitable for liquid immunoassays and LFA, some of which with sensitivity into the low picogram range with the liquid immunoassay formats with no cross-reactivity to other coronavirus S antigens. Discrepancies in optimal ranking were observed with the top pairs used in the liquid and LFA formats. These findings can support the development of SARS-CoV-2 LFAs and diagnostic tools.

Clinical validation of an open-access SARS-COV-2 antigen detection lateral flow assay, compared to commercially available assays.

Rapid tests for SARS-COV-2 infection are important tools for pandemic control, but current rapid tests are based on proprietary designs and reagents. We report clinical validation results of an open-access lateral flow assay (OA-LFA) design using commercially available materials and reagents, along with RT-qPCR and commercially available comparators (BinaxNOW® and Sofia®). Adult patients with suspected COVID-19 based on clinical signs and symptoms, and with symptoms ≤7 days duration, underwent anterior nares (AN) sampling for the OA-LFA, Sofia®, BinaxNOW ™, and RT-qPCR, along with nasopharyngeal (NP) RT-qPCR. Results indicate a positive predictive agreement with NP sampling as 69% (60% -78%) OA-LFA, 74% (64% - 82%) Sofia®, and 82% (73% - 88%) BinaxNOW™. The implication for these results is that we provide an open-access LFA design that meets the minimum WHO target product profile for a rapid test, that virtually any diagnostic manufacturer could produce.

Field evaluation of a prototype tuberculosis lipoarabinomannan lateral flow assay on HIV-positive and HIV-negative patients.

Detection of tuberculosis at the point-of-care (POC) is limited by the low sensitivity of current commercially available tests. We describe a diagnostic accuracy field evaluation of a prototype urine Tuberculosis Lipoarabinomannan Lateral Flow Assay (TB-LAM LFA) in both HIV-positive and HIV-negative patients using fresh samples with sensitivity and specificity as the measures of accuracy. This prototype combines a proprietary concentration system with a sensitive LFA. In a prospective study of 292 patients with suspected pulmonary tuberculosis in Uganda, the clinical sensitivity and specificity was compared against a microbiological reference standard including sputum Xpert MTB/RIF Ultra and solid and liquid culture. TB-LAM LFA had an overall sensitivity of 60% (95%CI 51-69%) and specificity of 80% (95%CI 73-85%). When comparing HIV-positive (N = 86) and HIV-negative (N = 206) patients, there was no significant difference in sensitivity (sensitivity difference 8%, 95%CI -11% to +24%, p = 0.4351) or specificity (specificity difference -9%, 95%CI -24% to +4%, p = 0.2051). Compared to the commercially available Alere Determine TB-LAM Ag test, the TB-LAM LFA prototype had improved sensitivity in both HIV-negative (difference 49%, 95%CI 37% to 59%, p<0.0001) and HIV-positive patients with CD4+ T-cell counts >200cells/µL (difference 59%, 95%CI 32% to 75%, p = 0.0009). This report is the first to show improved performance of a urine TB LAM test for HIV-negative patients in a high TB burden setting. We also offer potential assay refinement solutions that may further improve sensitivity and specificity.

Multiplexed and Extraction-Free Amplification for Simplified SARS-CoV-2 RT-PCR Tests.

The rapid onset of the global COVID-19 pandemic has led to challenges for accurately diagnosing the disease, including supply shortages for sample collection, preservation, and purification. Currently, most diagnostic tests require RNA extraction and detection by RT-PCR; however, extraction is expensive and time-consuming and requires technical expertise. With these challenges in mind, we report extraction-free, multiplexed amplification of SARS-CoV-2 RNA from 246 clinical samples, resulting in 86% sensitivity and 100% specificity. The multiplex RT-PCR uses the CDC singleplex targets and has an LoD of 2 c/µL. We also report on amplification using a range of master mixes in different transport media. This work can help guide which combinations of reagents will enable accurate results when availability of supplies changes throughout the pandemic. Implementing these methods can reduce complexity and cost, minimize reagent usage, expedite time to results, and increase testing capacity.

SARS-CoV-2 Coronavirus Nucleocapsid Antigen-Detecting Half-Strip Lateral Flow Assay Toward the Development of Point of Care Tests Using Commercially Available Reagents.

The SARS-CoV-2 pandemic has created an unprecedented need for rapid diagnostic testing to enable the efficient treatment and mitigation of COVID-19. The primary diagnostic tool currently employed is reverse transcription polymerase chain reaction (RT-PCR), which can have good sensitivity and excellent specificity. Unfortunately, implementation costs and logistical problems with reagents during the global SARS-CoV-2 pandemic have hindered its universal on demand adoption. Lateral flow assays (LFAs) represent a class of diagnostic that, if sufficiently clinically sensitive, may fill many of the gaps in the current RT-PCR testing regime, especially in low- and middle-income countries (LMICs). To date, many serology LFAs have been developed, though none meet the performance requirements necessary for diagnostic use cases, primarily due to the relatively long delay between infection and seroconversion. However, on the basis of previously reported results from SARS-CoV-1, antigen-based SARS-CoV-2 assays may have significantly better clinical sensitivity than serology assays. To date, only a very small number of antigen-detecting LFAs have been developed. Development of a half-strip LFA is a useful first step in the development of any LFA format. In this work, we present a half-strip LFA using commercially available antibodies for the detection of SARS-CoV-2. We have tested this LFA in buffer and measured an LOD of 0.65 ng/mL (95% CI of 0.53 to 0.77 ng/mL) ng/mL with recombinant antigen using an optical reader with sensitivity equivalent to a visual read. Further development, including evaluating the appropriate sample matrix, will be required for this assay approach to be made useful in a point of care setting, though this half-strip LFA may serve as a useful starting point for others developing similar tests.

Wash-Free, Digital Immunoassay in Polydisperse Droplets.

Immunoassays are important for the detection of proteins to enable disease identification and monitor treatment, but many immunoassays suffer from sensitivity limitations. The development of digital assays has enabled highly sensitive biomarker detection and quantification, but the necessary devices typically require precisely controlled volumes to reduce biases in concentration estimates from compartment size variation. These constraints have led to systems that are often expensive, cumbersome, and challenging to operate, confining many digital assays to centralized laboratories. To overcome these limitations, we have developed a simplified digital immunoassay performed in polydisperse droplets that are prepared without any specialized equipment. This polydisperse digital droplet immunoassay (ddIA) uses proximity ligation to remove the need for wash steps and simplifies the system to a single reagent addition step. Using interleukin-8 (IL-8) as an example analyte, we demonstrated the concept with samples in buffer and diluted whole blood with limits of detection of 0.793 pM and 1.54 pM, respectively. The development of a one-pot, washless assay greatly improves usability compared to traditional immunoassays or digital-based systems that rely heavily on wash steps and can be run with common and readily available laboratory equipment such as a heater and simple fluorescent microscope. We also developed a stochastic model with physically meaningful parameters that can be utilized to optimize the assay and enable quantification without standard curves, after initial characterization of the parameters. Our polydisperse ddIA assay serves as an example of sensitive, lower-cost, and simpler immunoassays suitable for both laboratory and point-of-care applications.

General methods for quantitative interpretation of results of digital variable-volume assays.

In digital assays, devices are typically considered to require precisely controlled volumes since variation in compartment volumes causes biases in concentration estimates. To enable more possibilities in device design, we derived two methods to accurately calculate target concentrations from raw results when the compartment volume may vary and may not follow known parametrically described distributions. The Digital Variable Volume (dvv) method uses volumes of ON compartments (those with positive signals) and the total sample volume, while the Digital Variable Volume Approximation (dvva) method uses the number of ON compartments, the total number of compartments, and a set of separately measured volumes. We verified the trueness of the dvv and dvva methods using simulated assays where volumes followed an empirical distribution (based on measured droplet volumes) and well known distributions with a wide range of standard deviations. We applied both methods to digital PCR experiments with polydisperse volumes, and also derived equations to estimate standard errors and limits of detection. The dvv method allows the compartment volume to follow any distribution in each assay run, the dvva method allows for quantification without in-assay volume measurements, and both methods potentially enable new designs of digital assays.

Sensitivity enhancement in lateral flow assays: a systems perspective.

Lateral flow assays (LFAs) are rapid, inexpensive, easy-to-manufacture and -use tests widely employed in medical and environmental applications, particularly in low resource settings. Historically, LFAs have been stigmatized as having limited sensitivity. However, as their global usage expands, extensive research has demonstrated that it is possible to substantially improve LFA sensitivity without sacrificing their advantages. In this critical review, we have compiled state-of-the-art approaches to LFA sensitivity enhancement. Moreover, we have organized and evaluated these approaches from a system-level perspective, as we have observed that the advantages and disadvantages of each approach have arisen from the integrated and tightly interconnected chemical, physical, and optical properties of LFAs.

Simple Polydisperse Droplet Emulsion Polymerase Chain Reaction with Statistical Volumetric Correction Compared with Microfluidic Droplet Digital Polymerase Chain Reaction.

Nucleic acid amplification technology, such as polymerase chain reaction (PCR), has enabled highly sensitive and specific disease detection and quantification, leading to more accurate diagnosis and treatment regimens. Lab-on-a-chip applications have developed methods to partition single biomolecules, such as DNA and RNA, into picoliter-sized droplets. These individual reaction vessels lead to digitization of PCR enabling improved time to detection and direct quantification of nucleic acids without a standard curve, therefore simplifying assay analysis. Though impactful, these improvements have generally been restricted to centralized laboratories with trained personnel and expensive equipment. To address these limitations and make this technology more applicable for a variety of settings, we have developed a statistical framework to apply to droplet PCR performed in polydisperse droplets prepared without any specialized equipment. The polydisperse droplet system allows for accurate quantification of droplet digital PCR (ddPCR) and reverse transcriptase droplet digital PCR (RT-ddPCR) that is comparable to commercially available systems such as BioRad's ddPCR. Additionally, this approach is compatible with a range of input sample volumes, extending the assay dynamic range beyond that of commercial ddPCR systems. In this work, we show that these ddPCR assays can reduce overall assay time while still providing quantitative results. We also report a multiplexed ddPCR assay and demonstrate proof-of-concept methods for rapid droplet preparation in multiple samples simultaneously. Our simple polydisperse droplet preparation and statistical framework can be extended to a variety of settings for the quantification of nucleic acids in complex samples.

Polydisperse emulsion digital assay to enhance time to detection and extend dynamic range in bacterial cultures enabled by a statistical framework.

Microbiological culture remains the most sensitive method for detecting viable and infectious bacteria, but these methods often require at least 24 hours to visibly identify bacterial growth. Lab-on-a-chip applications have utilized methods to isolate bacteria in picoliter-sized reaction vessels, resulting in digitized signals that offer improved time-to-detection and improved quantification. Although a great improvement, these approaches typically require expensive and specialized equipment, trained laboratory personnel, and maximum addressable volumes that can be orders of magnitude less than needed for clinically relevant limits of detection. To address these limitations, we have developed a simple method for preparing and semi-quantitatively analyzing small-volume droplets for performing digital culture, allowing for the detection of bacteria. This work includes a description of the method, characterization of resulting droplet sizes, comparison to traditional culture, and a statistical framework to quantify results. Though polydisperse, the droplet size distribution was consistent over different experiments, and there was a correlation between the observed number of positive droplets and the bulk concentration that can serve as a calibration curve for samples with unknown droplet size distributions. This statistical framework enables the simplification of droplet preparation and allows for accurate quantification even with polydisperse droplet sizes. The application of this method can also be extended to a variety of settings for the detection or quantification of bacteria in complex samples.

Threshold-Based Quantification in a Multiline Lateral Flow Assay via Computationally Designed Capture Efficiency.

Lateral flow assays (LFAs) are widely used for yes/no detection of analytes, but they are not well-suited for quantification. We show that the sensitivity of the test line in a lateral flow assay can be tuned to appear at a specific sample concentration by varying the density of capture molecules at the test line and that when test lines tuned for different responses are combined into a single test strip, lines appear at specific thresholds of sample concentration. We also developed a model based on mass-action kinetics that accurately described test line signal and shape over a wide matrix of capture molecules and sample concentrations in single-line strips. The model was used to design a three-line test strip with lines designed to appear at logarithmically spaced sample concentrations, and the experiments showed a remarkable match to predictions. The response of this "graded ladder bar" format is due to the effect of test line concentration on capture efficiency at each test line, not on sample depletion effects, and the effect is maintained whether a system is under kinetic or equilibrium control. These features enable design of nonlinear responses (logarithmic here) and suggest robustness for different systems. Thus, the graded ladder bar format could be a useful tool for applications requiring quantification of sample concentrations over a wide dynamic range.

Improving Lateral Flow Assay Performance Using Computational Modeling.

The performance, field utility, and low cost of lateral flow assays (LFAs) have driven a tremendous shift in global health care practices by enabling diagnostic testing in previously unserved settings. This success has motivated the continued improvement of LFAs through increasingly sophisticated materials and reagents. However, our mechanistic understanding of the underlying processes that drive the informed design of these systems has not received commensurate attention. Here, we review the principles underpinning LFAs and the historical evolution of theory to predict their performance. As this theory is integrated into computational models and becomes testable, the criteria for quantifying performance and validating predictive power are critical. The integration of computational design with LFA development offers a promising and coherent framework to choose from an increasing number of novel materials, techniques, and reagents to deliver the low-cost, high-fidelity assays of the future.

Diagnostic accuracy of self-administered urine glucose test strips as a diabetes screening tool in a low-resource setting in Cambodia.

OBJECTIVE: Screening for diabetes in low-resource countries is a growing challenge, necessitating tests that are resource and context appropriate. The aim of this study was to determine the diagnostic accuracy of a self-administered urine glucose test strip compared with alternative diabetes screening tools in a low-resource setting of Cambodia. DESIGN: Prospective cross-sectional study. SETTING: Members of the Borey Santepheap Community in Cambodia (Phnom Penh Municipality, District Dangkao, Commune Chom Chao). PARTICIPANTS: All households on randomly selected streets were invited to participate, and adults at least 18 years of age living in the study area were eligible for inclusion. OUTCOMES: The accuracy of self-administered urine glucose test strip positivity, Hemoglobin A1c (HbA1c)>6.5% and capillary fasting blood glucose (cFBG) measurement ≥126 mg/dL were assessed against a composite reference standard of cFBGmeasurement ≥200 mg/dL or venous blood glucose 2 hours after oral glucose tolerance test (OGTT) ≥200 mg/dL. RESULTS: Of the 1289 participants, 234 (18%) had diabetes based on either cFBG measurement (74, 32%) or the OGTT (160, 68%). The urine glucose test strip was 14% sensitive and 99% specific and failed to identify 201 individuals with diabetes while falsely identifying 7 without diabetes. Those missed by the urine glucose test strip had lower venous fasting blood glucose, lower venous blood glucose 2 hours after OGTT and lower HbA1c compared with those correctly diagnosed. CONCLUSIONS: Low cost, easy to use diabetes tools are essential for low-resource communities with minimal infrastructure. While the urine glucose test strip may identify persons with diabetes that might otherwise go undiagnosed in these settings, its poor sensitivity cannot be ignored. The massive burden of diabetes in low-resource settings demands improvements in test technologies.