BACKGROUND:Gestational Zika virus (ZIKV) infection is associated with the development of congenital Zika syndrome (CZS), which includes microcephaly and fetal demise. The magnitude and quality of orthoflavivirus-specific humoral immunity have been previously linked to the development of CZS. However, the role of ZIKV NS1-specific humoral immunity in mothers and children with prenatal ZIKV exposure and CZS remains undefined. In addition, considering that most of the at-risk population lives in dengue virus (DENV)-endemic areas, it is not clear what is the association between pre-existing DENV NS1-specific humoral immunity and CZS. METHODS:Here, we studied 328 mothers and children with a clinical diagnosis and seropositivity for ZIKV infection during pregnancy, included during the 2015-2016 ZIKV epidemic in Colombia. We also performed clinical evaluation and pediatric neurological follow-up. The relative levels of circulating NS1-specific IgM and IgG against ZIKV and DENV were evaluated in mothers and children, and the association with the development of microcephaly was analyzed. RESULTS:DENV and ZIKV IgG-NS1 antibodies in pregnant women were placentally transferred, and this passage and its duration in children depended on the maternal levels of the antibodies. We reported that higher concentrations of pre-existing DENV, but not ZIKV IgG-NS1 antibodies, were associated with a reduced risk of CZS-related microcephaly. Also, we observed that the IgM-NS1 response in infants is long-term and has a minor association with poor outcomes. CONCLUSIONS:The development of microcephaly in children prenatally exposed to ZIKV is associated with low plasma levels of placentally transferred, pre-existing DENV IgG-NS1 antibodies. These data are compatible with a protective role of anti-NS1 IgG antibodies against ZIKV infection during pregnancy and highlight the promising role of NS1 as an orthoflavivirus vaccine target in high-risk populations.

Background:Rapid and safe deployment of lateral-flow antigen tests, coupled with uncompromised quality assurance, is critical for outbreak control and pandemic preparedness, yet real-world performance assessment still lacks laboratory and quantitative approaches that remain uncommon in current regulatory science. The approach proposed here can help standardize and accelerate early phase appraisal of antigen tests in preparation for clinical validation. Objective:The aim of this study is to present a quantitative, laboratory-anchored framework that links image-based test line intensities and the population distribution of naked-eye limits of detection (LoD) to a probabilistic prediction of positive percent agreement (PPA) as a function of viral-load-related variables (eg, quantitative real-time polymerase chain reaction [qRT-PCR] cycle thresholds [Cts]). Using dilution-series calibrations and a Bayesian model, the predicted PPA-vs-Ct curve closely tracks the observed PPA in a real-world self-testing cohort. Methods:The proposed methodology combines: (1) a quantitative evaluation of the test signal response to concentrations of target protein and inactive virus or active virus, (2) a statistical characterization of the LoD using the observer's visual acuity of the test band, and (3) a calibration of a gold-standard method (eg, qRT-PCR cycles) against virus concentration. We elaborate these quantitative methods and unfold a Bayesian-based predictive model to describe the real-world performance of the antigen test, quantified by the probability of positive agreement as a function of viral-load variables like qRT-PCR Cts. Results:We applied the methodology by characterizing each brand of COVID-19 antigen test and estimating its real-world probability of agreement with qRT-PCR. We aligned protein and inactivated-virus standard curves at matched signal intensities and fit a linear calibration linking protein to viral concentrations. Using logistic regression, we modeled the PPA as a continuous function of qRT-PCR Ct, then integrated this curve over a predefined reference Ct distribution to obtain the expected sensitivity. This standardization enables consistent performance comparisons across sites. Conclusions:Modeling performance under real-world conditions requires coupling laboratory evaluation with the population's ability to perceive the test's visual signal. We represent observer capability as a probability density function of the LoD over the signal-intensity domain. Rather than reporting bin-based sensitivity, we summarize performance with the PPA as a continuous function of qRT-PCR Ct. Our framework produces PPA-Ct curves by composing (1) normalized signal-to-concentration models from the laboratory, (2) the observer LoD distribution, and (3) a Ct-to-viral-load calibration. The resulting inferences are inherently context-bound-disease-, assay-, and setup-specific. External validity depends on the particular antigen lateral-flow test, the user population (visual acuity and interpretation), and cross-laboratory qRT-PCR calibration. Comprehensive clinical studies under intended-use conditions are still required before making generalized claims.

Background:Sensitivity-expressed as percent positive agreement (PPA) with a reference assay-is a primary metric for evaluating lateral-flow antigen tests (ATs), typically benchmarked against a quantitative reverse transcription polymerase chain reaction (qRT-PCR). In SARS-CoV-2 diagnostics, ATs detect nucleocapsid protein, whereas qRT-PCR detects viral RNA copy numbers. Since observed PPA depends on the underlying viral load distribution (proxied by the number of cycle thresholds [Cts], which is inversely related to load), study-specific sampling can bias sensitivity estimates. Cohort differences-such as enrichment for high- or low-Ct specimens-therefore complicate cross-test comparisons, and real-world datasets often deviate from regulatory guidance to sample across the full concentration range. Although logistic models relating test positivity to Ct are well described, they are seldom used to reweight results to a standardized reference viral load distribution. As a result, reported sensitivities remain difficult to compare across studies, limiting both accuracy and generalizability. Objective:The aim of this study was to develop and validate a statistical methodology that estimates the sensitivity of ATs by recalibrating clinical performance data-originally obtained from uncontrolled viral load distributions-against a standardized reference distribution of target concentrations, thereby enabling more accurate and comparable assessments of diagnostic test performance. Methods:AT sensitivity is estimated by modeling the PPA as a function of qRT-PCR Ct values (PPA function) using logistic regression on paired test results. Raw sensitivity is the proportion of AT positives among PCR-positive samples. Adjusted sensitivity is calculated by applying the PPA function to a reference Ct distribution, correcting for viral load variability. This enables standardized comparisons across tests. The method was validated using clinical data from a community study in Chelsea, Massachusetts, demonstrating its effectiveness in reducing sampling bias. Results:Over a 2-year period, paired ATs and qRT-PCR-positive samples were collected from 4 suppliers: A (n=211), B (n=156), C (n=85), and D (n=43). Ct value distributions varied substantially, with suppliers A and D showing lower Ct (high viral load) values in the samples, and supplier C skewed toward higher Ct values (low viral load). These differences led to inconsistent raw sensitivity estimates. To correct for this, we used logistic regression to model the PPA as a function of Cts and applied these models to a standardized reference Ct distribution. This adjustment reduced bias and enabled more accurate comparisons of test performance across suppliers. Conclusions:We present a distribution-aware framework that models PPA as a logistic function of Ct and reweights results to a standardized reference Ct distribution to produce bias-corrected sensitivity estimates. This yields fairer, more consistent comparisons across AT suppliers and studies, strengthens quality control, and supports regulatory review. Collectively, our results provide a robust basis for recalibrating reported sensitivities and underscore the importance of distribution-aware evaluation in diagnostic test assessment.

BACKGROUND:Infections by dengue virus (DENV) and Zika virus (ZIKV) have some similar symptoms and a cross-reactive immune response, although with different risk populations and outcomes. Here, we evaluated the virologic characteristics and the nonstructural protein 1 (NS1)-specific antibody responses to DENV and ZIKV in children suspected of dengue in different epidemiologic moments in Colombia.METHODS:Viral RNA, circulating NS1 and IgM/IgG specific for DENV and ZIKV were performed by reverse transcription-quantitative polymerase chain reaction and enzyme-linked immunosorbent assay (ELISA) in 301 children suspected of dengue enrolled in a hospital setting during the ZIKV epidemic and a primary healthcare setting during a DENV epidemic. For the detection of DENV and ZIKV-specific IgM, an NS1-based ELISA was validated using characterized pediatric samples. Clinical and laboratory parameters were also evaluated.RESULTS:DENV RNA or NS1 antigen was detected in the plasma of 62% of children, and in none, the ZIKV RNA was found. NS1-based ELISA for DENV and ZIKV IgM showed a sensitivity/specificity of 90/84% and 73/98%, respectively. Of 114 children without detectable viremia or antigenemia, 30.7%, 17.5%, 22% and 30% were IgM-DENV + , IgM-ZIKV + , IgM-DENV + ZIKV + and IgM-DENV - ZIKV - , respectively. The ZIKV/DENV IgM-NS1 ratio allows the identification of the infecting orthoflavivirus in 88% of the children with IgM-DENV + ZIKV + , confirming a high predominance of DENV infections in the 2 pediatric settings.CONCLUSION:Overall, 88% of the children with clinical suspicion of dengue had an identifiable orthoflaviviral infection, with 80% caused by DENV, 7% by ZIKV and 0.7% classified as recent infections or coinfection, demonstrating active viral cocirculation in the pediatric population of southern Colombia. The IgM-NS1 detection improved the identification of orthoflaviviral infections in children without viremia or antigenemia, suggesting it is a helpful complementary tool for medical personnel in tropical regions with high viral cocirculation and different clinical scenes.

AbstractControlling spread of disease due to infectious agents require a quick response from public health sector. In the ongoing COVID-19 pandemic, the use of antigen tests has shown to be an excellent tool to inform authorities and mitigate the spread of the disease. In this communication we demonstrated how performance of an antigen test -- as a diagnosticin vitrodevice -- can be properly validated using quantitative laboratory experimentation and self-testing data from a clinical study. We also show how clinical performance of an antigen test can be predicted using mathematical modeling. The proposed appraisal methodology of antigen test performance under real-world conditions could be a useful tool to inform regulatory decision making. This approach allows to standardize, democratize, and speed up the process of validation, analysis, and comparison of antigen rapid tests, and thus to help developing effective public health response strategies.

Sensitivity is a key measure of lateral-flow antigen test (AT) performance, typically compared against qRT-PCR as the gold standard. For COVID-19, diagnostic sensitivity assesses the ability of ATs to detect SARS-CoV-2 nucleoprotein. However, sensitivity estimates can be strongly skewed by variations of the target concentrations within the clinical sample sets. Independent studies evaluating ATs from different manufacturers often display disparate target concentration distributions, making it difficult to compare sensitivity across products. We propose a new methodology to enhance the accuracy of sensitivity calculations, ensuring more reliable comparisons across ATs. Sensitivity is estimated by modeling the probability of positive agreement (PPA) as a function of qRT-PCR cycle thresholds (Cts) via logistic regression of antigen test results. Raw sensitivity is calculated as the ratio of antigen test positives to total PCR positives. Adjusted sensitivity is derived by applying the PPA function to a reference concentration distribution, enabling uniform sensitivity comparisons across tests. This approach minimizes the impact of uneven sampling and external factors, as demonstrated using clinical data from a study in Chelsea, Massachusetts, USA. Over two years, paired antigen and PCR positive tests from four AT suppliers were analyzed: A (211 tests), B (156), C (85), and D (43). The qRT-PCR Ct distributions varied, with suppliers A and D having more high viral load samples, while supplier C had more low viral load samples, causing significant discrepancies in raw sensitivity. Using the PPA function estimated from each supplier's dataset, we calculated the corresponding adjusted sensitivities for common reference Ct distributions, highlighting how sample heterogeneity impacts raw sensitivity. Our approach successfully mitigates this variability, allowing for more accurate sensitivity comparisons. This study demonstrates that sensitivity estimates from real-world data are susceptible to deviations caused by external factors, particularly the heterogeneity of qRT-PCR Ct distributions across studies. We present data supporting a novel methodology that adjusts for this variability by calculating the PPA function from raw data and determining the expected sensitivity based on a reference distribution of qRT-PCR Cts, allowing for more consistent and accurate sensitivity assessments. ### Competing Interest Statement Irene Bosch is a founder of IDX20, a company affiliated with this study. Miguel Bosch is a founder of Info Analytics Innovations, a company also affiliated with this study. The authors declare no additional conflicts of interest. ### Funding Statement This research was supported by Reagan-Udall Foundation through Grant #02282022 RUF and by the NIH Rapid Acceleration of Diagnostics for Underserved Populations (RADx-UP) program, Grant # R0502A, both awarded to IDX20. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Advarra gave ethical approval for this work I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data is available at the Rapid Acceleration of Diagnostics - Underserved Populations (RADxUP, a program funded by the National Institutes of Health (NIH), under the repository conditions.

Background: Pediatric dengue and sepsis share clinical and pathophysiologic aspects. Multiple inflammatory and regulatory cytokines, decoy receptors and vascular permeability factors have been implicated in the pathogenesis of both diseases. The differential pattern and dynamic of these soluble factors, and the relationship with clinical severity between pediatric dengue and sepsis could offer new diagnosis and therapeutic strategies. Methods: We evaluated the concentration levels of 11 soluble factors with proinflammatory, regulatory and vascular permeability involvement, in plasma from children with dengue or sepsis, both clinically ranging from mild to severe, in the early, late and convalescence phases of the disease. Results: During early acute infection, children with sepsis exhibited specific higher concentration levels of IL-6, vascular endothelial growth factor (VEGF), and its soluble decoy receptor II (sVEGFR2) and lower concentration levels of IL-10 and the soluble tumor necrosis factor receptor 2 (sTNFR2), in comparison with children with severe dengue. In addition, the circulating amounts of soluble ST2, and VEGF/sVEGFR2 were widely associated with clinical and laboratory indicators of dengue severity, whereas secondary dengue virus infections were characterized by an enhanced cytokine response, relative to primary infections. In severe forms of dengue, or sepsis, the kinetics and the cytokines response during the late and convalescence phases of the disease also differentiate. Conclusions: Dengue virus infection and septic processes in children are characterized by cytokine responses of a specific magnitude, pattern and kinetics, which are implicated in the pathophysiology and clinical outcome of these diseases.

Supplementary Tables 1-6 from Gene Expression Signature in Organized and Growth-Arrested Mammary Acini Predicts Good Outcome in Breast Cancer

Characterizing perturbation of molecular pathways in congenital Zika virus (ZIKV) infection is critical for improved therapeutic approaches. Leveraging integrative systems biology, proteomics, and RNA-seq, we analyzed embryonic brain tissues from an immunocompetent, wild-type congenital ZIKV infection mouse model. ZIKV induced a robust immune response accompanied by the downregulation of critical neurodevelopmental gene programs. We identified a negative correlation between ZIKV polyprotein abundance and host cell cycle-inducing proteins. We further captured the downregulation of genes/proteins, many of which are known to be causative for human microcephaly, including Eomesodermin/T-box Brain Protein 2 (EOMES/TBR2) and Neuronal Differentiation 2 (NEUROD2). Disturbances of distinct molecular pathways in neural progenitors and post-mitotic neurons may contribute to complex brain phenotype of congenital ZIKV infection. Overall, this report on protein-and transcript-level dynamics enhances understanding of the ZIKV immunopathological landscape through characterization of fetal immune response in the developing brain.

BackgroundThe co-circulation of flaviviruses in tropical regions has led to the hypothesis that immunity generated by a previous dengue infection could promote severe disease outcomes in subsequent infections by heterologous serotypes. This study investigated the influence of antibodies generated by previous Zika infection on the clinical outcomes of dengue infection.Methodology/principal findingsWe enrolled 1,043 laboratory confirmed dengue patients and investigated their prior infection to Zika or dengue. Severe forms of dengue disease were more frequent in patients with previous Zika infection, but not in those previously exposed to dengue.Conclusions/significanceOur findings suggest that previous Zika infection may represent a risk factor for subsequent severe dengue disease, but we did not find evidence of antibody-dependent enhancement (higher viral titer or pro-inflammatory cytokine overexpression) contributing to exacerbation of the subsequent dengue infection.

Chikungunya virus (CHIKV) has caused large outbreaks worldwide in recent years. Acute-phase CHIKV infection has been reported to cause mild to severe febrile illness, and in some patients, this may be followed by long-lasting polyarthritis. The mainstay of treatment includes nonsteroidal anti-inflammatory drugs and other disease-modifying agents, the use of which is based on the assumption of an immunological interference mechanism in the pathogenesis. The present study has been designed to generate preliminary evidence to test this hypothesis. The levels of 30 cytokines were estimated in serum samples of acute CHIKV-infected patients, fully-recovered patients, patients with chronic CHIKV arthritis, and controls, using a quantitative multiplex bead ELISA. The levels of the proinflammatory cytokines IL-1 and IL-6 were elevated in acute patients, but IFN-γ/β and TNF-α levels remained stable. IL-10, which might have an anti-inflammatory effect, was also elevated, indicating a predominantly anti-inflammatory response in the acute phase of infection. Elevation of MCP-1, IL-6, IL-8, MIP-1α, and MIP-1β was most prominent in the chronic phase. These cytokines and chemokines have been shown to play important roles in other arthritides, including epidemic polyarthritis (EPA) caused by Ross River virus (RRV) and rheumatoid arthritis (RA).The immunopathogenesis of chronic CHIKV arthritis might have similarities to these arthritides. The novel intervention strategies being developed for EPA and RA, such as IL-6 and IL-8 signaling blockade, may also be considered for chronic CHIKV arthritis.

Global public health infrastructure is unprepared for emerging pathogen epidemics, in part because diagnostic tests are not developed in advance. The recent Zika, Ebola, and SARS-CoV-2 virus epidemics are cases in point. We demonstrate here that multicolored gold nanoparticles, when coupled to cross-reactive monoclonal antibody pairs generated from a single immunization regimen, can be used to create multiple diagnostics that specifically detect and distinguish related viruses. The multiplex approach for specific detection centers on immunochromatography with pairs of antibody-conjugated red and blue gold nanoparticles, coupled with clustering algorithms to detect and distinguish related pathogens. Cross-reactive antibodies were used to develop rapid tests for i) Dengue virus serotypes 1–4, ii) Zika virus, iii) Ebola and Marburg viruses, and iv) SARS-CoV and SARS-CoV-2 viruses. Multiplexed rapid antigen tests based on multicolored nanoparticles and cross-reactive antibodies and can be developed prospectively at low cost to improve preparedness for epidemic outbreaks.

Platelet count is widely used for the diagnosis and follow-up of patients with dengue. Despite its close viral structural and symptomatic homology, ZIKV infection does not typically induce significant thrombocytopenia. To determine the effect of DENV-2 and ZIKV infection on human platelet precursors we utilized MEG-01 cell line to evaluate the viral infection, viability, innate gene expression and release of platelet-like particles (PLPs). DENV-2 induced a higher proportion of cell death at 48-72 h post-infection than ZIKV. The median range of intracellular NS1+/E+ cells was 11.2% (3.3%-25%) and 5% (3%-8.1%) for DENV-2 and ZIKV, respectively (p = 0.03). MEG-01 cells infected with DENV-2 quickly expressed higher levels of IFN-beta, indolamine 2,3-dioxygenase and CXCL10 mRNA compared to ZIKV infected cells and DENV-2 but not ZIKV infection reduced the number PLPs from stimulated MEG-01 cells. The results shed light into mechanisms including thrombocytopenia present in patients with DENV but absent in ZIKV infections.

Background The focus on laboratory-based diagnosis of coronavirus disease 2019 (COVID-19) warrants alternative public health tools such as rapid antigen tests. While there are a number of commercially available antigen tests to detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), all cross-react with the genetically similar SARS-CoV-1 or require an instrument for results interpretation. Methodology/Principal findings We developed and validated rapid antigen tests that use pairs of murine-derived monoclonal antibodies (mAbs), along with gold nanoparticles, to detect SARS-CoV-2 with or without cross-reaction to SARS-CoV-1 and other coronaviruses. In this development, we demonstrate a robust antibody screening methodology for the selection of mAb pairs that can recognize SARS-CoV-2 spike (S) and nucleocapsid (N) proteins. Linear epitope mapping of the mAbs helped elucidate SARS-CoV-2 S and N interactions in lateral flow chromatography. A candidate rapid antigen test for SARS-CoV-2 N was validated using nasal swab specimens that were confirmed positive or negative by quantitative reverse-transcription polymerase chain reaction (RT-PCR). Test results were image-captured using a mobile phone and normalized signal pixel intensities were calculated; signal intensities were inversely correlated to RT-PCR cycle threshold (Ct) value. Conclusion/Significance Overall, our results suggest that the rapid antigen test is optimized to detect SARS-CoV-2 N during the acute phase of COVID-19. The rapid antigen tests developed in this study are alternative tools for wide scale public health surveillance of COVID-19.

Optimized methods for the detection of flavivirus infections in hyperendemic areas are still needed, especially for working with patient serum as a starting material. The focus-forming assay (FFA) reveals critical aspects of virus-host interactions, as it is a quantitative assay to determine viral loads. Automated image analysis provides evaluations of relative amounts of intracellular viral protein at the single-cell level. Here, we developed an optimized FFA for the detection of infectious Zika virus (ZIKV) and dengue virus (DENV) viral particles in cell cultures and clinical serum samples, respectively. Vero-76 cells were infected with DENV-2 (16681) or ZIKV (PRVA BC59). Using a panel of anti-DENV and anti-ZIKV NS1-specific monoclonal antibodies (mAbs), the primary mAbs, concentration, and the optimal time of infection were determined. To determine whether intracellular accumulation of NS1 improved the efficiency of the FFA, brefeldin A was added to the cultures. Focus formation was identified by conventional optical microscopy combined with CellProfiler™ automated image analysis software. The FFA was used with spike assays for ZIKV and clinical specimens from natural infection by DENV-1 and DENV-2. mAb 7744-644 for ZIKV and mAb 724-323 for DENV used at a concentration of 1 μg/ml and a time of 24 hours postinfection produced the best detection of foci when combining conventional counting and automated digital analysis. Brefeldin A did not improve the assessment of FFUs or their digitally assessed intensity at single-cell level. The FFA showed 95% ZIKV recovery and achieved the detection of circulating DENV-1 and DENV-2 in the plasma of acutely ill patients. The combination of the two techniques optimized the FFA, allowing the study of DENV and ZIKV in culture supernatants and clinical specimens from natural infection in hyperendemic areas.

This cohort study examines the performance of direct antigen rapid tests compared with that of quantitative real-time polymerase chain reaction for analyzing self-collected nasal specimens for the presence of SARS-CoV-2.

Se presenta el caso de una mujer de 38 años que consultó inicialmente por fiebre indiferenciada. A pesar de que el cuadro clínico evolucionó con manifestaciones clínicas de dengue con signos de alarma y de que la detección de IgM antidengue en una sola muestra indicaba que se trataba de un caso probable que había podido ocurrir durante los tres meses anteriores, la paciente consultó de forma reiterada, pues no presentaba una mejoría significativa. En el décimo día del inicio de los síntomas, se observó edema simétrico en múltiples articulaciones acompañado de dolor, así como lesiones hiperpigmentadas en el surco nasogeniano. Se confirmó el diagnóstico de chikungunya por la presencia de anticuerpos IgM. Aunque puede pasar desapercibida, en los países endémicos para dengue y chikungunya existe la posibilidad de la infección concomitante, la cual puede agravar la evolución clínica de cada una de estas enfermedades. Por ello, es necesario que el médico considere las características clínicas y de laboratorio de ambas enfermedades para diagnosticar su presencia simultánea, garantizar un manejo adecuado y minimizar las complicaciones.

High frequency screening of populations has been proposed as a strategy in facilitating control of the COVID-19 pandemic. We use computational modeling, coupled with clinical data from rapid antigen tests, to predict the impact of frequent viral antigen rapid testing on COVID-19 spread and outcomes. Using patient nasal or nasopharyngeal swab specimens, we demonstrate that the sensitivity/specificity of two rapid antigen tests compared to quantitative real-time polymerase chain reaction (qRT-PCR) are 82.0%/100% and 84.7%/85.7%, respectively; moreover, sensitivity correlates directly with viral load. Based on COVID-19 data from three regions in the United States and São José do Rio Preto, Brazil, we show that high frequency, strategic population-wide rapid testing, even at varied accuracy levels, diminishes COVID-19 infections, hospitalizations, and deaths at a fraction of the cost of nucleic acid detection via qRT-PCR. We propose large-scale antigen-based surveillance as a viable strategy to control SARS-CoV-2 spread and to enable societal re-opening.

High frequency screening of populations has been proposed as a strategy in facilitating control of the COVID-19 pandemic. Here we develop a model to evaluate the impact of rapid testing on COVID-19 spread and outcomes, inspired by our clinically validated direct antigen rapid test (DART) for detection of SARS-CoV-2 spike glycoprotein. Using patient nasopharyngeal swab specimens we demonstrate that the DART sensitivity and specificity are 84.7% and 85.7%, respectively; moreover, sensitivity increases proportionally with higher viral loads. Based on surveillance data on COVID-19 from the United States and Sao Jose do Rio Preto, Brazil we show that frequent and strategic population-wide rapid testing, even at varied accuracy levels, is more effective than virus detection via polymerase chain reaction at reducing COVID-19 infections, hospitalizations, and deaths. While current policy emphasizes testing accuracy, we propose large-scale antigen-based surveillance as a vital strategy to control SARS-CoV-2 spread and to enable societal re-opening.