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A Rapid Diagnostic Platform for Colorimetric Differential Detection of Dengue and Chikungunya Viral Infections Ruisheng Wang, Serge Y. Ongagna-Yhombi, Zhengda Lu, Elizabeth Centeno-Tablante, Susannah Colt, Xiangkun Elvis Cao, Yue Ren, Washington B. Cárdenas, Saurabh Mehta, and David Erickson Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.9b00704 • Publication Date (Web): 21 Mar 2019 Downloaded from http://pubs.acs.org on March 21, 2019

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Analytical Chemistry

A Rapid Diagnostic Platform for Colorimetric Differential Detection of Dengue and Chikungunya Viral Infections Ruisheng Wanga, Serge Y. Ongagna-Yhombib,c, Zhengda Lub, Elizabeth Centeno-Tablantec, Susannah Coltc, Xiangkun Caob, Yue Renb, Washington B. Cárdenasd, Saurabh Mehtac, David Ericksonb,c*. aMeinig

School of Biomedical Engineering, Cornell University, Ithaca, NY 14853, United States. School of Mechanical and Aerospace Engineering, Cornell University, Ithaca, NY 14853, United States. cDivision of Nutritional Sciences, Cornell University, Ithaca, NY 14853, United States. dEscuela Superior Politécnica del Litoral (ESPOL), Guayaquil, Guayas 090902, Ecuador. bSibley

ABSTRACT: In this work, we demonstrate a rapid diagnostic platform with potential to transform clinical diagnosis of acute febrile illnesses in resource-limited settings. Acute febrile illnesses such as dengue and chikungunya, which pose high burdens of disease in tropical regions, share many nonspecific symptoms and are difficult to diagnose based on clinical history alone in the absence of accessible laboratory diagnostics. Through a unique color-mixing encoding and readout strategy, our platform enabled consistent and accurate multiplexed detection of dengue and chikungunya IgM/IgG antibodies in human clinical samples within 30 minutes. Our multiplex assay offers several advantages over conventional rapid diagnostic tests deployed in resource-limited settings, including a low sample volume requirement and the ability to concurrently detect four analytes. Our platform is a step towards multiplexed diagnostics that will be transformative for disease management in resource-limited settings by enabling informed treatment decisions through accessible evidence-based diagnosis.

Acute febrile illnesses, a term that encompasses a range of medical conditions with fever as a common determinant, pose a significant burden in developing settings, which are often resource-limited. The lack of diagnostic tools and trained personnel often leads to suboptimal symptoms-based diagnosis and in turn less-than-ideal disease management. Mosquitos of the genus Aedes transmit several etiologic agents of acute febrile illnesses, including dengue virus (DENV) and chikungunya virus (CHIKV), which cause infections that share overlapping symptoms but have different management strategies. When a differential diagnosis cannot be made based on symptoms alone, accessible evidence-based laboratory diagnosis is crucial for clinical management of disease. DENV is a flavivirus with four serotypes (DENV1-4). While infection with one serotype typically results in immunity limited to that specific serotype, subsequent secondary infections with a different serotype increase the risk of developing severe hemorrhagic fever 1. An estimated 2.5 billion people are at risk for dengue with 390 million infections occurring globally every year 2,3. CHIKV is an alphavirus that can cocirculate with DENV in endemic regions. A characteristic feature of CHIKV infection is joint pain that persists for weeks to years post-acute infection. While CHIKV infection prevalence varies from year to year, epidemics across the globe have infected millions of people, with recent outbreaks occurring in the Caribbean and South America 4. Diagnostics for dengue and chikungunya viral infections in endemic regions, if available at all, are often limited to serology-based rapid diagnostic tests (RDTs). Compared to culture or RNA detection, serology-based RDTs are preferred for field-use due to their simplicity and the broader diagnostic window associated with antibody detection 5. RDTs in the form

of lateral flow assays (LFAs) are one of the few diagnostic technologies to be successfully adopted in developing settings as they meet the World Health Organization’s ASSURED criteria for diagnostic tests 6. Limitations of current LFAs, as is the case with dengue and chikungunya RDTs 7,8, are limited sensitivity compared to enzyme-linked immunosorbent assay (ELISA) and difficulty to combine in multiplexed format for detection of targets 9. The ability to detect and distinguish between multiple diseases facilitates patient management as well as disease surveillance. In the case of DENV and CHIKV infections, differential diagnosis facilitates appropriate disease management; for example, nonsteroidal anti-inflammatory drugs (NSAIDs) administered for CHIKV infection should not be used in patients coinfected with DENV as they can increase the risk of hemorrhage 10. Strategies for multiplexing of LFAs have included the use of multiple different-colored lines to detect viral proteins from dengue, yellow fever, and Ebola viruses 11; the use of multiple same-colored lines to detect antibodies to HIV, hepatitis C, and hepatitis A viruses 12; and the use of multiple single-plex strips arranged in disc format to detect 10 foodborne pathogens 13. The expansion of multiplexing capability by only increasing the number of test lines for each additional analyte is ultimately limited by space constraints of the test strip membrane. A simple way to enhance the capabilities of LFAs is by adopting the “disposables with a reader” model 14. In this model, an optical reader can be harnessed to enable semiquantitative or even quantitative readout and eliminate subjective interpretation of test results. Readout with an optical reader also enables novel strategies for expanding multiplexing

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capability such as interpretation of mixed colors, which can be exploited for detection of multiple analytes on a single test line. Here, we describe a rapid diagnostic platform consisting of a low-cost reader in conjunction with a multicolor 4-plex immunoassay that was used to detect and distinguish between DENV immunoglobulin M (IgM) and immunoglobulin G (IgG) and CHIKV IgM and IgG antibodies in human clinical samples. Our rapid diagnostic platform, as demonstrated to be in good agreement with ELISA, overcomes many of the limitations of existing RDTs through a unique assay architecture and readout mechanism. Materials and Methods Experimental design The objective of the study was to develop and validate a rapid diagnostic platform capable of detecting and distinguishing between multiple pathogen-induced host biomarkers. Platform development consisted of hardware, software, and assay development. The assay component was designed to enable multiplexed detection of four targets on a single strip, with enhanced sensitivity and specificity achieved through screening of protein reagents along with optimization of assay architecture, sample dilution, and buffers. The reader component was designed to enable unbiased and consistent analysis of test results. The platform was validated first using spiked buffer samples, followed by human clinical samples. Envelope proteins Four DENV and three CHIKV envelope proteins were screened for antibody recognition and cross reactivity using the dot blot format. Recombinant DENV1-4 (CalBioreagents) and CHIKV E1, E1-A226V, E2 (CalBioreagents) envelope proteins expressed in insect cells with >95% purity were conjugated to latex nanoparticles and screened for specific and nonspecific binding against mouse monoclonal anti-DENV (CalBioreagents) and anti-CHIKV antibodies (CalBioreagents), mouse monoclonal anti-pan DENV envelope antibodies (MyBioSource), rabbit polyclonal anti-CHIKV antibodies (IBT Bioservices), as well as a subset of positive patient clinical samples. DENV3 and DENV4 envelope proteins exhibited high cross reactivity with anti-CHIKV antibodies and were therefore excluded from the final conjugate mixture. Protein conjugation to nanoparticles DENV and CHIKV envelope proteins were covalently conjugated, via lysine residues, to colored 400nm latex nanoparticles using the Latex Conjugation Kit (Expedeon) according to manufacturer’s instructions. DENV envelope proteins were conjugated to red latex nanoparticles and CHIKV envelope proteins to blue latex nanoparticles. The conjugates were resuspended to 0.5% (w/v) in a storage buffer we developed that consists of 50mM borate, 10% sucrose, 1% BSA, 0.5% Tween-20, and 0.02% sodium azide and stored at 4°C. Sucrose in the storage buffer facilitates conjugate release and helps stabilize the conjugates when dried by forming a protective coating. Test strip preparation Components required to assemble the lateral flow test strip are as follows: sample pad, conjugate pad, nitrocellulose membrane, and absorbent pad. Prior to assembly, capture reagents were first dispensed and immobilized on the nitrocellulose membrane. Hi-Flow Plus 180 Membrane Cards

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(MilliporeSigma) were used as the backbone of the test strips as the card contains a nitrocellulose membrane along with adhesive sections that facilitate attachment of other components. The membrane has a capillary flow rate of 45 seconds/cm, the slowest offered by the manufacturer, which serves to maximize sensitivity and minimize reagent consumption by increasing the contact time between capture reagents and analyte of interest. Three capture reagent lines, one control and two test, were dispensed 3mm apart on the nitrocellulose membrane using an Automated Lateral Flow Reagent Dispenser (ClaremontBio) and a Legato 200 Dual Syringe Infusion Pump (KD Scientific) operating at a rate of 6.7 ml/min. The first test line, corresponding to the first line the sample encounters, was composed of recombinant Protein G (MilliporeSigma) at 3mg/ml. Protein G binds to human IgG with high affinity but does not cross react with human IgM, IgA, IgE, or serum albumin. The second test line was composed of mouse monoclonal anti-human IgM (Thermo Fisher Scientific), which does not cross react with human IgG or IgA, at 1mg/ml. The control line consisted of a 1:1 mixture of mouse monoclonal anti-dengue and anti-chikungunya envelope protein antibodies (CalBioreagents) at 1mg/ml. All capture reagents were diluted to their respective concentrations using a buffer consisting of 1×PBS and 2% sucrose. Following dispensing of capture reagents, membrane cards were dried at 37°C for 2h and then stored in a desiccator at room temperature prior to assembly. To prepare the conjugate pad for assembly, individual DENV (DENV1, DENV2) and CHIKV (E1, E1A226V, E2) conjugates were mixed in a 3:3:2:2:2 ratio to obtain an overall 1:1 DENV to CHIKV conjugates ratio and the mixture was diluted to 0.05% (w/v) using the conjugate storage buffer. Glass Fiber Conjugate Pad Strips (MilliporeSigma) were soaked in the diluted conjugate mixture and dried at 37°C overnight. For strip assembly, the conjugate pad was attached below the nitrocellulose membrane with 2mm overlap. Cellulose Fiber Sample Pad Strips (MilliporeSigma) were used as both the sample and absorbent pads and were attached below the conjugate pad with 2mm overlap and above the nitrocellulose membrane with 1mm overlap. The assembled card was cut into individual test strips of 5mm width using a rotary paper trimmer and stored in a desiccator at room temperature. Test protocol For testing, human plasma/serum samples were first diluted 1/20 fold in 1×PBS. Each test strip required 20μl of diluted sample, which corresponds to 1μl of undiluted sample, to be dispensed on the sample pad followed by 70μl of an optimized running buffer designed to minimize nonspecific binding that consisted of 75mM Tris, 450mM NaCl, 1% BSA, 1% Tween20, and 0.02% sodium azide. After 30 minutes, tests strips were imaged using the reader for analysis. Reader design The frame and casing of the reader were 3D printed using black ABS plastic. Image acquisition was enabled by a CMOS image sensor module (OmniVision), which was fixed in a 3D printed holder. A focusing lens with 25mm focal length (Thorlabs) was mounted in the holder and aligned to the optical path of the camera sensor, thus allowing acquisition of focused images in compacted space. An LED array consisting of 6 LEDs (Cree) with 7500K color temperature was also attached to the holder to provide internal illumination during imaging. A Raspberry


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Pi was used to modulate operation of the image sensor and LEDs as well as data transmission. A 802.11b/g/n WiFi adapter (Adafruit) enabled wireless data transmission between the

reader and smartphone/PC. Three rechargeable 18650 lithium ion batteries (Panasonic) were used to power the reader.

Figure 1. Rapid diagnostic platform consisting of 4-plex color encoded lateral flow test strip and optical reader. (A) Architecture of multiplex lateral flow test strip. Red and blue nanoparticle conjugates are able to bind to DENV and CHIKV antibodies present in the sample, respectively. Nanoparticle-conjugate labeled IgG antibodies are captured by the first test line (shown in red for illustrative purposes) and labeled IgM antibodies are captured by the second test line (shown in blue), leading to color development. When both DENV and CHIKV antibodies of the same isotype are present in the sample, an intermediate color that is a mixture of red and blue develops at the test line. Unbound nanoparticle conjugates are both captured by the control line (shown in purple). (B) Exploded view of optical reader designed to minimize variations in color detection. (C) Inner assembly of optical reader. (D) Fully assembled optical reader with lightproof casing. The sliding tray shown open is closed during imaging to eliminate ambient light. Indicator lights reflect imaging progress. (E) Examples of test strip appearance corresponding to various diagnostic scenarios. Purple was used for illustrative purposes to denote cases where both DENV and CHIKV antibodies of the same isotype are present.

Image analysis For image analysis, a 430×1000 pixel region of the membrane was converted to grayscale and pixel intensities were averaged across the width of the strip to obtain a profile that was used to determine the location of the test and control lines. Red and blue channel pixel intensities were similarly averaged across the width of the strip to obtain average intensity profiles for the individual colors. A second order polynomial was fit to seven

points on the average intensity profile and subtracted from the data for baseline correction, which enabled the comparison of test line intensities across different samples. Peak intensities in the red and blue channel average intensity profiles corresponded to the individual signal intensities of each of the four antibodies of interest. For cases when the antibody of interest was absent from the sample or below the limit of detection, the representative signal intensity for that antibody



was taken to be the maximum intensity of the test line region 100 pixels across the length of the strip. Statistical analysis Matlab was used for data visualization and statistical analysis. F-test was used to test for equality of population variances and unpaired one-tailed t-test was used to test for equality of population means. When calculating confidence intervals for ROC analysis, the number of bootstrap replicas was set to 1000. Results Colorimetric multiplex assay design The assay component of the platform was designed to enable multiplexed detection of four targets on a single strip, with enhanced sensitivity and specificity achieved through protein screening along with optimization of assay architecture and reagents. Components of the assay test strip (Fig. 1A) are as follows: a sample pad for dispensing of sample, a conjugate pad for holding antigen-conjugated colored nanoparticles, a nitrocellulose membrane for immobilizing capture reagents, and an absorbent pad for wicking excess flow. DENV and CHIKV envelope proteins, which enable receptor binding and membrane fusion, were selected as bioconjugation targets since they are recognized by host antibodies during infection 15,16. To maximize sensitivity and specificity of IgM and IgG detection, four DENV (DENV1-4) and three CHIKV (E1, E1-A226V, E2) envelope proteins were initially screened for antibody recognition and cross reactivity using a dot blot format. DENV3 and DENV4 envelope proteins exhibited high cross reactivity with anti-CHIKV antibodies and were therefore excluded from the final conjugate mixture to increase assay specificity. Since anti-DENV antibodies were highly cross reactive among the four DENV serotypes 17, the exclusion of DENV3 and DENV4 envelope proteins was expected to minimally impact assay sensitivity. For CHIKV, the inclusion of E1-A226V and E2 envelope proteins served to increase assay sensitivity as it has been demonstrated that the E1 antigen alone has limited sensitivity for detecting IgM antibodies against the A226V mutant strain 18 and that anti-E2 IgG antibodies persist longer than anti-E1 antibodies in patient plasma and can still be detected at 21 months post-illness onset 16. To enable color-based multiplexing, DENV and CHIKV envelope proteins were covalently conjugated to colored 400nm latex nanoparticles. DENV envelope proteins (DENV1-2) were conjugated to red latex nanoparticles and CHIKV envelope proteins (E1, E1-A226V, E2) to blue latex nanoparticles. A mixture of red and blue nanoparticle conjugates was dried on the conjugate pad. When reconstituted by the addition of sample and running buffer, the functionalized latex nanoparticles can bind to any anti-CHIKV IgG/IgM and antiDENV IgG/IgM antibodies present in the sample. As this mixture migrates up the nitrocellulose membrane, labeled antibody-nanoparticle complexes bind to the immobilized capture reagents on the membrane in sandwich format which contributes to the development of colorimetric signals at the test lines. For the IgG test line, Protein G was used to capture IgG antibodies since Protein G does not cross react with human IgM, IgA, IgE, or serum albumin. For the IgM test line, monoclonal anti-human IgM was used to capture IgM antibodies. We noticed the IgM test line signal was enhanced when the IgG test line was placed before the IgM test line in the direction of flow. One possible explanation for this signal enhancement is that the binding of sample IgGs to Protein G at the first test line

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functions similar to the IgG adsorbent addition step in IgM capture ELISA, which removes IgGs from the sample matrix to reduce interference. For the control line, a mixture of antiDENV and anti-CHIKV antibodies was used to confirm conjugate functionality. Color coding of test and control lines for different diagnostic scenarios is shown in Fig. 1E. Multiplexing was enabled using red and blue latex nanoparticles, as each test line was able to detect two diseasespecific antibodies of the same isotype for a total of four different antibody targets on a single test strip. When DENV antibodies are present in the sample a red color develops on the test line(s) for the corresponding isotype, and when CHIKV antibodies are present in the sample a blue color develops. When both DENV and CHIKV antibodies of the same isotype are present, an intermediate color develops, the hue of which is dependent on the relative concentrations of the two antibodies. In this scenario, an optical reader for readout is essential to eliminate subjective interpretation of test results. In addition, inclusion of a reader enables semi-quantitative readout in which a signal intensity cutoff can be set to distinguish between positive and negative samples, which ultimately enhances assay specificity. Optical reader design Previously, our group has developed an optical reader for readout of a multiplex fluorescent immunoassay 19. In this work, we present a new low-cost reader device (Fig. 1B) constructed of primarily off-the-shelf components and designed for color detection and differentiation to provide unbiased and consistent analysis of test results. The reader automatically images the test strip membrane region containing the test and control lines and wirelessly transfers RGB color data to smartphone/PC for analysis. Compared to imaging with a cellphone, imaging with the reader minimized variations and ensured greater consistency. The opaque outer casing of the reader (Fig. 1D) eliminated variations in lighting conditions during imaging and internal sensor mounts (Fig. 1C) maintained a consistent imaging distance. Since the reader was optimized for color detection and capable of detecting faint traces of color, sample volume requirements were minimized for our 4-plex assay, which only required 1μl of undiluted serum/plasma sample. The 1μl sample volume is a significant improvement over existing DENV and CHIKV RDTs, which typically require 5-50μl of undiluted sample for a singleplex test 7,8. Semi-quantitative readout of assay results was achieved through processing of RGB data collected by the reader. Red and blue channel pixel intensities were averaged across the width of the test strip to obtain average intensity profiles for the individual colors (Fig. 2A). Peak intensities in the red and blue channel average intensity profiles at the test lines corresponded to the individual signal intensities of each of the four antibody targets. Color detection and differentiation in spiked samples To validate our assay’s ability to detect antibodies across a wide concentration range, spiked buffer samples with eight different anti-DENV IgG and anti-CHIKV IgG concentrations ranging from 100ng/ml to 400µg/ml were separately tested, imaged, and analyzed (Fig. 2B). Spiked IgM samples were not tested due to the lack of commercially available anti-DENV IgM and antiCHIKV IgM antibodies. For IgG testing, samples were dispensed on the sample pad of the test strip and flushed with


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an optimized high-salt running buffer to enable migration through the conjugate pad and nitrocellulose membrane and incubated to permit signal development. Following an incubation period of 30 minutes, test strips were imaged with the reader for analysis. The extracted test line signal intensities (Fig. 2B) demonstrated that our assay was able to detect disease-specific antibodies across the concentration range with good repeatability. With the optimized conjugate mixture and running buffer, no cross reactivity was observed between antiDENV antibodies and CHIKV conjugates or anti-CHIKV antibodies and DENV conjugates.

Figure 2. Color-based detection of DENV and CHIKV antibodies in spiked samples. (A) Processing of test strip data from optical reader. Red and blue channel data were averaged across the width of the strip to obtain an average intensity profile along the length of the strip. Peak intensities at the test lines correspond to the representative signal intensities of antibody targets. The red channel contains data on DENV antibodies and the blue channel on CHIKV antibodies. For each channel, the first band (from left to right) corresponds to IgG, the second to IgM, and the third to control. (B) Signal intensities of separate DENV and CHIKV IgG samples across a concentration range. Each concentration was tested in triplicate and error-bars denote one standard deviation. (C) Extracted signal intensities of combined DENV and CHIKV IgG samples mixed in inverse proportions. Each mixture was

tested in triplicate and error-bars denote one standard deviation. Actual images of test lines are shown above the data points to illustrate the difficulty of extracting color components by nakedeye and the utility of reader-enabled interpretation.

At higher analyte concentrations the Hook effect was observed, in which an excess of unlabeled analytes compete with labeled analytes for binding sites at the test line, leading to a decrease in signal intensity 20. This makes quantitative detection difficult as two antibody concentrations can be extracted for the same intensity value. We found sample dilution to be a simple yet effective method to address the Hook effect for our assay. Taking into account reference ranges for total IgG and IgM in serum 21 and the concentrations of the test line capture reagents, we found a sample dilution factor of 20 to be optimal for testing of clinical samples. This dilution factor shifted most of the signal intensities to occur before the Hook effect inflection point, thereby increasing quantitative detection potential. Total IgG and IgM reference range was used as a proxy to estimate upper and lower bounds of analyte concentration as diseasespecific antibody levels vary and are not well characterized in the literature. To validate the ability of the platform to accurately interpret mixed samples, five different anti-DENV IgG and anti-CHIKV IgG concentrations ranging from 100ng/ml to 50µg/ml were mixed in inverse proportions and tested using our platform (Fig. 2C). Because the samples in this case contained mixtures of DENV and CHIKV antibodies, the test lines that developed were of intermediate hues between blue and red. The extracted red and blue intensities at the test line, which correspond to the signal intensities of DENV and CHIKV antibodies, demonstrated the utility of reader-enabled interpretation of test results. In instances where a high concentration of one antibody was mixed with a low concentration of the other antibody (e.g. 100ng/ml DENV with 10µg/ml CHIKV, a 100-fold concentration differential), the signal intensity of the low concentration antibody was impossible to detect by naked eye (Fig. 2C) but could still be detected and captured by the reader with good repeatability. Validation with clinical samples De-identified human plasma samples (Antibody Systems) from Colombia were used to assess the performance of our diagnostic platform in testing human clinical samples. The plasma samples were collected from male and female subjects with ages ranging from 18 to 74 and represented diverse DENV and CHIKV infection statuses as these diseases are endemic to the region. Each sample was screened for DENV IgG/IgM, CHIKV IgG/IgM, and Zika virus (ZIKV) IgG/IgM using EUROIMMUN ELISA kits, per manufacturer’s instructions. ZIKV ELISA was included in sample screening as serological cross reactivity has been shown between ZIKV and DENV 22. Based on set ELISA cutoffs, 40 samples were identified as DENV IgG positive, 10 DENV IgM positive, 29 CHIKV IgG positive, 12 CHIKV IgM positive, and 8 ZIKV IgG positive. 10 samples that were negative for DENV, CHIKV, and ZIKV antibodies served as the control group for testing. Samples were stored frozen until testing, in which 1µl of each sample was diluted 20-fold and dispensed onto the test strip for analysis. ELISA results for human samples are shown in Fig. 3A. The samples covered a range of extinction value ratios that correspond to different concentrations of DENV and CHIKV antibodies. Semi-quantitative classification of positive and



negative samples was made based on the manufacturer recommended cut-off ratio of 1.1. For each of the four analytes, extinction ratios for positive and negative sample groups were statistically distinct (P < 0.001). Test strip intensity results for human samples are shown in Fig. 3B. Samples were tested in random order and in duplicate and test line signal intensities were averaged and subsequently grouped based on ELISA classification. For each of the four targets, test line intensities for ELISA positive and ELISA negative sample groups were statistically distinct (P < 0.001). Receiver operating characteristic (ROC) curve analysis was subsequently conducted to determine optimal cutoff intensities.

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positive/negative classification. The optimal intensity cutoff, as subsequently determined through ROC curve analysis (Fig. 4), is represented by the horizontal dotted line.

Assessment of diagnostic accuracy The ROC curve, which is obtained through calculating the sensitivity and specificity of a test at every possible cut-off, is widely used for selecting an optimal cut-off and assessing the diagnostic accuracy of a test 23. The ROC curve plots the true positive rate (sensitivity) against the false positive rate (1 – specificity) and shows the inverse relationship between sensitivity and specificity at various cut-offs. Common methods of selecting the optimal cut-off include selecting the point on the curve closest to (0, 1) or selecting the point that maximizes the Youden index, which is defined as sensitivity + specificity – 1 24. The Youden index method was used to determine the optimal cut-off values for test line intensities as the method was demonstrated to have lower overall misclassification rates than the (0, 1) method 24. Intensities above the cut-off value were interpreted to be positive and intensities below the cut-off were interpreted to be negative. For the four antibody targets, ROC curves are shown in Fig. 4A and optimal cut-off intensity values along with associated sensitivities and specificities are shown in Fig. 4B. Sensitivities and specificities were calculated with ELISA as the gold standard reference. Optimal cut-off intensities were 3.01, 4.86, 11.0, and 8.01 for DENV IgG, DENV IgM, CHIKV IgG, and CHIKV IgM, respectively. Associated sensitivities and specificities for the four analytes were as follows: 100% and 100% for DENV IgG, 100% and 78% for DENV IgM, 100% and 100% for CHIKV IgG, and 83% and 97% for CHIKV IgM. For comparison (Table S1), commercially available CHIKV IgM RDTs have sensitivities between 20-30% and specificities between 73-93% while DENV IgM RDTs have sensitivities between 52-95% and specificities between 86-92% 7,8. Compared to singleplex RDTs, our platform was able to achieve comparable or superior results using less sample volume and with four multiplexed targets in a single test.

Figure 3. ELISA and test strip results for human samples. (A) ELISA results for human samples. Extinction value ratios are shown as individual data points grouped by a cutoff value of 1.1, which is represented by the horizontal dotted line. In box plots, the central mark denotes the median, and the top and bottom edges of the box denote 25th and 75th percentiles, respectively. Whiskers extend to the most extreme data points not including outliers, which are represented with the + symbol. One-tailed t-test was used to test for equality of population means between positive and negative samples groups with *** denoting P < 0.001. (B) Test strip results for human samples from colorimetric data. Samples were tested in random order and in duplicate and average test line intensities are shown as individual data points grouped by ELISA


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Figure 4. ROC curve analysis results. (A) ROC curves for each of the four antibody targets generated using test strip results from clinical samples with ELISA as the gold standard reference. The dotted line represents an area under the curve (AUC) of 0.5. (B) Table listing metrics from ROC curve analysis, including areas under the curve, confidence intervals (CI), sensitivities, specificities, and optimal intensity cutoffs.

The area under the ROC curve (AUC) is a single measure that summarizes the discriminative power of a test across the range of possible cut-offs 25. AUC greater than 0.9 is considered high accuracy, 0.7-0.9 is considered moderate accuracy, 0.5-0.7 is considered low accuracy, and 0.5 a tossup 26. AUCs for the four analytes were as follows: 1.0 for DENV IgG, 0.94 for DENV IgM, 1.0 for CHIKV IgG, and 0.92 for CHIKV IgM. Discussion In this work, we developed a rapid diagnostic platform consisting of a low-cost reader combined with a colorimetric multiplex immunoassay that was capable of detecting and distinguishing between DENV IgM and IgG and CHIKV IgM and IgG antibodies in human clinical samples. The ability to detect and distinguish between color-labeled analytes at various concentrations with good repeatability was first demonstrated in spiked samples, followed by validation using human clinical samples. ROC curve analysis demonstrated our test to be in good agreement with conventionally used ELISA, as AUCs for all four analytes were greater than 0.9. These results demonstrate the potential for our diagnostic platform to serve as an accessible ELISA alternative in resource-limited settings, especially since our platform consists of a reader constructed of primarily off-the-shelf components along with a lateral flow test strip consumable, which has already shown good uptake in resource-limited settings. Accurate differential diagnosis

enables timely identification and appropriate management of disease as well as early indication of outbreaks. In the case of DENV for instance, an informed management strategy that depends on early diagnosis can reduce the mortality rate in severe DENV patients from 5% to

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