Accuracy of routine laboratory tests to predict mortality and deterioration to severe or critical COVID-19 in people with SARS-CoV-2.

BACKGROUND: Identifying patients with COVID-19 disease who will deteriorate can be useful to assess whether they should receive intensive care, or whether they can be treated in a less intensive way or through outpatient care. In clinical care, routine laboratory markers, such as C-reactive protein, are used to assess a person's health status. OBJECTIVES: To assess the accuracy of routine blood-based laboratory tests to predict mortality and deterioration to severe or critical (from mild or moderate) COVID-19 in people with SARS-CoV-2. SEARCH METHODS: On 25 August 2022, we searched the Cochrane COVID-19 Study Register, encompassing searches of various databases such as MEDLINE via PubMed, CENTRAL, Embase, medRxiv, and ClinicalTrials.gov. We did not apply any language restrictions. SELECTION CRITERIA: We included studies of all designs that produced estimates of prognostic accuracy in participants who presented to outpatient services, or were admitted to general hospital wards with confirmed SARS-CoV-2 infection, and studies that were based on serum banks of samples from people. All routine blood-based laboratory tests performed during the first encounter were included. We included any reference standard used to define deterioration to severe or critical disease that was provided by the authors. DATA COLLECTION AND ANALYSIS: Two review authors independently extracted data from each included study, and independently assessed the methodological quality using the Quality Assessment of Prognostic Accuracy Studies tool. As studies reported different thresholds for the same test, we used the Hierarchical Summary Receiver Operator Curve model for meta-analyses to estimate summary curves in SAS 9.4. We estimated the sensitivity at points on the SROC curves that corresponded to the median and interquartile range boundaries of specificities in the included studies. Direct and indirect comparisons were exclusively conducted for biomarkers with an estimated sensitivity and 95% CI of ≥ 50% at a specificity of ≥ 50%. The relative diagnostic odds ratio was calculated as a summary of the relative accuracy of these biomarkers. MAIN RESULTS: We identified a total of 64 studies, including 71,170 participants, of which 8169 participants died, and 4031 participants deteriorated to severe/critical condition. The studies assessed 53 different laboratory tests. For some tests, both increases and decreases relative to the normal range were included. There was important heterogeneity between tests and their cut-off values. None of the included studies had a low risk of bias or low concern for applicability for all domains. None of the tests included in this review demonstrated high sensitivity or specificity, or both. The five tests with summary sensitivity and specificity above 50% were: C-reactive protein increase, neutrophil-to-lymphocyte ratio increase, lymphocyte count decrease, d-dimer increase, and lactate dehydrogenase increase. Inflammation For mortality, summary sensitivity of a C-reactive protein increase was 76% (95% CI 73% to 79%) at median specificity, 59% (low-certainty evidence). For deterioration, summary sensitivity was 78% (95% CI 67% to 86%) at median specificity, 72% (very low-certainty evidence). For the combined outcome of mortality or deterioration, or both, summary sensitivity was 70% (95% CI 49% to 85%) at median specificity, 60% (very low-certainty evidence). For mortality, summary sensitivity of an increase in neutrophil-to-lymphocyte ratio was 69% (95% CI 66% to 72%) at median specificity, 63% (very low-certainty evidence). For deterioration, summary sensitivity was 75% (95% CI 59% to 87%) at median specificity, 71% (very low-certainty evidence). For mortality, summary sensitivity of a decrease in lymphocyte count was 67% (95% CI 56% to 77%) at median specificity, 61% (very low-certainty evidence). For deterioration, summary sensitivity of a decrease in lymphocyte count was 69% (95% CI 60% to 76%) at median specificity, 67% (very low-certainty evidence). For the combined outcome, summary sensitivity was 83% (95% CI 67% to 92%) at median specificity, 29% (very low-certainty evidence). For mortality, summary sensitivity of a lactate dehydrogenase increase was 82% (95% CI 66% to 91%) at median specificity, 60% (very low-certainty evidence). For deterioration, summary sensitivity of a lactate dehydrogenase increase was 79% (95% CI 76% to 82%) at median specificity, 66% (low-certainty evidence). For the combined outcome, summary sensitivity was 69% (95% CI 51% to 82%) at median specificity, 62% (very low-certainty evidence). Hypercoagulability For mortality, summary sensitivity of a d-dimer increase was 70% (95% CI 64% to 76%) at median specificity of 56% (very low-certainty evidence). For deterioration, summary sensitivity was 65% (95% CI 56% to 74%) at median specificity of 63% (very low-certainty evidence). For the combined outcome, summary sensitivity was 65% (95% CI 52% to 76%) at median specificity of 54% (very low-certainty evidence). To predict mortality, neutrophil-to-lymphocyte ratio increase had higher accuracy compared to d-dimer increase (RDOR (diagnostic Odds Ratio) 2.05, 95% CI 1.30 to 3.24), C-reactive protein increase (RDOR 2.64, 95% CI 2.09 to 3.33), and lymphocyte count decrease (RDOR 2.63, 95% CI 1.55 to 4.46). D-dimer increase had higher accuracy compared to lymphocyte count decrease (RDOR 1.49, 95% CI 1.23 to 1.80), C-reactive protein increase (RDOR 1.31, 95% CI 1.03 to 1.65), and lactate dehydrogenase increase (RDOR 1.42, 95% CI 1.05 to 1.90). Additionally, lactate dehydrogenase increase had higher accuracy compared to lymphocyte count decrease (RDOR 1.30, 95% CI 1.13 to 1.49). To predict deterioration to severe disease, C-reactive protein increase had higher accuracy compared to d-dimer increase (RDOR 1.76, 95% CI 1.25 to 2.50). The neutrophil-to-lymphocyte ratio increase had higher accuracy compared to d-dimer increase (RDOR 2.77, 95% CI 1.58 to 4.84). Lastly, lymphocyte count decrease had higher accuracy compared to d-dimer increase (RDOR 2.10, 95% CI 1.44 to 3.07) and lactate dehydrogenase increase (RDOR 2.22, 95% CI 1.52 to 3.26). AUTHORS' CONCLUSIONS: Laboratory tests, associated with hypercoagulability and hyperinflammatory response, were better at predicting severe disease and mortality in patients with SARS-CoV-2 compared to other laboratory tests. However, to safely rule out severe disease, tests should have high sensitivity (> 90%), and none of the identified laboratory tests met this criterion. In clinical practice, a more comprehensive assessment of a patient's health status is usually required by, for example, incorporating these laboratory tests into clinical prediction rules together with clinical symptoms, radiological findings, and patient's characteristics.

Comprehensive Review of COVID-19: Epidemiology, Pathogenesis, Advancement in Diagnostic and Detection Techniques, and Post-Pandemic Treatment Strategies.

At present, COVID-19 remains a public health concern due to the ongoing evolution of SARS-CoV-2 and its prevalence in particular countries. This paper provides an updated overview of the epidemiology and pathogenesis of COVID-19, with a focus on the emergence of SARS-CoV-2 variants and the phenomenon known as 'long COVID'. Meanwhile, diagnostic and detection advances will be mentioned. Though many inventions have been made to combat the COVID-19 pandemic, some outstanding ones include multiplex RT-PCR, which can be used for accurate diagnosis of SARS-CoV-2 infection. ELISA-based antigen tests also appear to be potential diagnostic tools to be available in the future. This paper also discusses current treatments, vaccination strategies, as well as emerging cell-based therapies for SARS-CoV-2 infection. The ongoing evolution of SARS-CoV-2 underscores the necessity for us to continuously update scientific understanding and treatments for it.

Evaluation of Self-collected Saliva Samples Without Viral Transport Media for SARS-CoV-2 Testing via RT-PCR and Comparison of Amplicon Sequences Against Commonly Used Primers in Diagnostic Assays.

INTRODUCTION: Mass screening for SARS-CoV-2 using nasopharyngeal swabs (NPS) is costly, uncomfortable for patients, and increases the chance of virus exposure to health care workers. Therefore, this study focused on determining if self-collected unpreserved saliva can be an effective alternative to NPS collection in COVID-19 surveillance. MATERIALS AND METHODS: In this study, patients being tested for SARS-CoV-2 using NPS were asked to provide a saliva sample to compare their results. NPS samples were evaluated for SARS-CoV-2 using BioFire® FilmArray® Torch® or Cepheid® GeneXpert® systems while saliva samples were evaluated using an in-house developed reverse transcriptase polymerase chain reaction (RT-PCR) which targeted the Envelope (E) and Nucleocapsid (N) genes. RESULTS: Detection of SARS-CoV-2 using self-collected saliva was found to be only slightly less accurate (<5%) than testing using NPS. In addition, initial saliva RT-PCR identified 27 positive subjects, 18 of which provided amplicons sufficient for confirmatory sequencing. The sequencing data showed a genetic shift in the virus within our population sometime between 22 June and July 8, 2021 from Alpha to Delta variant. CONCLUSIONS: The saliva sample collection method identifies the E gene in SARS COVID-2 samples which provides an alternative specimen source to the NPS. This identifies the S gene and ORF1ab. Saliva collection is more convenient to the patient, yields comparable results to NPS collection, and potentially increases Covid-19 surveillance.

Effect of testing criteria for infectious disease surveillance: The case of COVID-19 in Norway.

During the COVID-19 pandemic in Norway, the testing criteria and capacity changed numerous times. In this study, we aim to assess consequences of changes in testing criteria for infectious disease surveillance. We plotted the proportion of positive PCR tests and the total number of PCR tests for different periods of the pandemic in Norway. We fitted regression models for the total number of PCR tests and the probability of positive PCR tests, with time and weekday as explanatory variables. The regression analysis focuses on the time period until 2021, i.e. before Norway started vaccination. There were clear changes in testing criteria and capacity over time. In particular, there was a marked difference in the testing regime before and after the introduction of self-testing, with a drastic increase in the proportion of positive PCR tests after the introduction of self-tests. The probability of a PCR test being positive was higher for weekends and public holidays than for Mondays-Fridays. The probability for a positive PCR test was lowest on Mondays. This implies that there were different testing criteria and/or different test-seeking behaviour on different weekdays. Though the probability of testing positive clearly changed over time, we cannot in general conclude that this occurred as a direct consequence of changes in testing policies. It is natural for the testing criteria to change during a pandemic. Though smaller changes in testing criteria do not seem to have large, abrupt consequences for the disease surveillance, larger changes like the introduction and massive use of self-tests makes the test data less useful for surveillance.

A cost-sensitive decision model for efficient pooled testing in mass surveillance of infectious diseases like COVID-19.

The COVID-19 pandemic has imposed significant challenges on global health, emphasizing the persistent threat of large-scale infectious diseases in the future. This study addresses the need to enhance pooled testing efficiency for large populations. The common approach in pooled testing involves consolidating multiple test samples into a single tube to efficiently detect positivity at a lower cost. However, what is the optimal number of samples to be grouped together in order to minimize costs? i.e. allocating ten individuals per group may not be the most cost-effective strategy. In response, this paper introduces the hierarchical quotient space, an extension of fuzzy equivalence relations, as a method to optimize group allocations. In this study, we propose a cost-sensitive multi-granularity intelligent decision model to further minimize testing costs. This model considers both testing and collection costs, aiming to achieve the lowest total cost through optimal grouping at a single layer. Building upon this foundation, two multi-granularity models are proposed, exploring hierarchical group optimization. The experimental simulations were conducted using MATLAB R2022a on a desktop with Intel i5-10500 CPU and 8G RAM, considering scenarios with a fixed number of individuals and fixed positive probability. The main findings from our simulations demonstrate that the proposed models significantly enhance the efficiency and reduce the overall costs associated with pooled testing. For example, testing costs were reduced by nearly half when the optimal grouping strategy was applied, compared to the traditional method of grouping ten individuals. Additionally, the multi-granularity approach further optimized the hierarchical groupings, leading to substantial cost savings and improved testing efficiency.

Nanobody-based strategy for rapid and accurate pathogen detection: A case of COVID-19 testing.

Antibody pairs-based immunoassay platforms served as essential and effective tools in the field of pathogen detection. However, the cumbersome preparation and limited detection sensitivity of antibody pairs challenge in establishment of a highly sensitive detection platform. In this study, using COVID-19 testing as a case, we utilized readily accessible nanobodies as detection antibodies and further proposed an accurate design concept with a more scientific and efficient screening strategy to obtain ultrasensitive antibody pairs. We employed nanobodies capable of binding different antigenic epitopes of the nucleocapsid (NP) or receptor-binding domain (RBD) antigens sandwich as substitutes for monoclonal antibodies (mAbs) sandwich in fast detection formats and utilized time-resolved fluorescence (TRF) microspheres as the signal probe. Consequently, we developed a multi-epitope nanobody sandwich-based fluorescence lateral flow immunoassay (FLFA) strip. Our results suggest that the NP antigen had a detection limit of 12.01pg/mL, while the RBD antigen had a limit of 6.51 pg/mL using our FLFA strip. Based on double mAb sandwiches, the values presented herein demonstrated 4 to 32-fold enhancements in sensitivity, and 32 to 256-fold enhancements compared to commercially available antigen lateral flow assay kits. Furthermore, we demonstrated the excellent characteristics of the proposed test strip, including its specificity, stability, accuracy, and repeatability, which underscores its the prospective utility. Indeed, these findings indicate that our established screening strategy along with the multi-epitope nanobody sandwich mode provides an optimized strategy in the field of pathogen detection.

Enhancing efficiency in detection of COVID-19 through AI-driven colorimetric isothermal detection with multiplex primers.

COVID-19 has afflicted millions of lives worldwide. Although there are many rapid methods to detect it based on colorimetric loop-mediated isothermal amplification, there remains room for improvement. This study aims to 1) integrate multiple primers into a singleplex assay to enhance the diagnostic sensitivity, and 2) utilize a high-throughput smartphone-operatable AI-driven color reading tool to enable a rapid result analysis. This setup can improve the sensitivity by 10-100 times and can analyze approximately 6700 samples per minute. The assay is simpler than RT-qPCR, with a turnaround time of less than 75 min. It can detect various types of SARS-CoV-2 by targeting 3 genes, increasing the likelihood that it will remain effective even if the virus undergoes mutations in any single target gene. In summary, it affords potential for adaptation to detection of new/re-emerging diseases with the visual readout for maximum assay simplicity and AI-operated mode for large-scale testing.

SARS-CoV-2 Dynamics in the Premier League Testing Program, United Kingdom.

During 2020-2022, players and staff in the English Premier League in the United Kingdom were tested regularly for SARS-CoV-2 with the aim of creating a biosecure bubble for each team. We found that prevalence and reinfection estimates were consistent with those from other studies and with community infection trends.

Surveillance of SARS-CoV-2 prevalence from repeated pooled testing: application to Swiss routine data.

Surveillance of SARS-CoV-2 through reported positive RT-PCR tests is biased due to non-random testing. Prevalence estimation in population-based samples corrects for this bias. Within this context, the pooled testing design offers many advantages, but several challenges remain with regards to the analysis of such data. We developed a Bayesian model aimed at estimating the prevalence of infection from repeated pooled testing data while (i) correcting for test sensitivity; (ii) propagating the uncertainty in test sensitivity; and (iii) including correlation over time and space. We validated the model in simulated scenarios, showing that the model is reliable when the sample size is at least 500, the pool size below 20, and the true prevalence below 5%. We applied the model to 1.49 million pooled tests collected in Switzerland in 2021-2022 in schools, care centres, and workplaces. We identified similar dynamics in all three settings, with prevalence peaking at 4-5% during winter 2022. We also identified differences across regions. Prevalence estimates in schools were correlated with reported cases, hospitalizations, and deaths (coefficient 0.84 to 0.90). We conclude that in many practical situations, the pooled test design is a reliable and affordable alternative for the surveillance of SARS-CoV-2 and other viruses.

External Quality Assessment Program for SARS-COV-2 Molecular Detection in Pakistan.

INTRODUCTION: Amid coronavirus disease 2019 (COVID-19) pandemic, accurate detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is critical for diagnosis management and breaking down transmission chains. We designed a national external quality assessment panel (EQAP) for SARS-CoV-2 molecular detection comprising working laboratories nationwide. METHODS: A molecular diagnostic EQA panel that consists of five samples for SARS CoV-2 testing was distributed to 141 public and private sector laboratories across country. These samples contain different concentrations of SARS-CoV-2 to evaluate the sensitivity of commercial kits available. RESULTS: Sensitivity among public and private sector laboratories was variable, particularly lower SARS-CoV-2 concentrations significantly increased the risk of false-negative tests, whereas Ct values of accurately tested SARS-CoV-2 specimens increased as concentration decreased. These findings highlighted that performance of used commercial kits was not significantly correlated to various extraction or PCR methods. CONCLUSION: This study highlights the need for a national external quality assessment panel (EQAP) in the country to improve the quality of the healthcare system while ensuring the accuracy and reliability of results. Furthermore, EQAPs can help laboratories meet accreditation and regulatory requirements. However, continued participation in EQAP is recommended for quality enhancement of laboratories.

Cost-effectiveness of COVID rapid diagnostic tests for patients with severe/critical illness in low- and middle-income countries: A modeling study.

BACKGROUND: Rapid diagnostic tests (RDTs) for coronavirus disease (COVID) are used in low- and middle-income countries (LMICs) to inform treatment decisions. However, to date, it is unclear when this use is cost-effective. Existing analyses are limited to a narrow set of countries and uses. The aim of this study is to assess the cost-effectiveness of COVID RDTs to inform the treatment of patients with severe illness in LMICs, considering real world practice. METHODS AND FINDINGS: We assessed the cost-effectiveness of COVID testing across LMICs using a decision tree model, differentiating results by country income level, Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) prevalence, and testing scenario (none, RDTs, polymerase chain reaction tests-PCRs and combinations). LMIC experts defined realistic care pathways and treatment options. Using a healthcare provider perspective and net monetary benefit approach, we assessed both intended (COVID symptom alleviation) and unintended (treatment side effects) health and economic impacts for each testing scenario. We included the side effects of corticosteroids, which are often the only available treatment for COVID. Because side effects depend both on the treatment and the patient's underlying illness (COVID or COVID-like illnesses, such as influenza), we considered the prevalence of COVID-like illnesses in our analyses. We found that SARS-CoV-2 testing of patients with severe COVID-like illness can be cost-effective in all LMICs, though only in some circumstances. High influenza prevalence among suspected COVID cases improves cost-effectiveness, since incorrectly provided corticosteroids may worsen influenza outcomes. In low- and some lower-middle-income countries, only patients with a high index of suspicion for COVID should be tested with RDTs, while other patients should be presumed to not have COVID. In some lower-middle-income and upper-middle-income countries, suspected severe COVID cases should almost always be tested. Further, in these settings, negative test results in patients with a high initial index of suspicion should be confirmed through PCR and, during influenza outbreaks, positive results in patients with a low initial index of suspicion should also be confirmed with a PCR. The use of interleukin-6 receptor blockers, when supported by testing, may also be cost-effective in higher-income LMICs. The cost at which they would be cost-effective in low-income countries ($162 to $406 per treatment course) is below current prices. The primary limitation of our analysis is substantial uncertainty around some of the parameters in our model due to limited data, most notably on current COVID mortality with standard of care, and insufficient evidence on the impact of corticosteroids on patients with severe influenza. CONCLUSIONS: COVID testing can be cost-effective to inform treatment of LMIC patients with severe COVID-like disease. The optimal algorithm is driven by country income level and health budgets, the level of suspicion that the patient may have COVID, and influenza prevalence. Further research to better characterize the unintended effects of corticosteroids, particularly on influenza cases, could improve decision making around the treatment of those with COVID-like symptoms in LMICs.

Effects of serial swabs on the nasopharyngeal mucosa: our experience in SARS-CoV2 screening.

INTRODUCTION: The purpose of the study was to analyze the effect of swabs on nasal mucosa. METHODOLOGY: Since May 2020, our department was responsible for screening coronavirus disease 2019 (COVID-19) among the employees of a company that continued its activity during the pandemic. The screening protocol consisted of two swabs per week. The samples were analyzed through objective endoscopic and subjective clinical evaluations with sino-nasal outcome test (SNOT Test) at three time points (T0, T1 - three months, T2 - six months). RESULTS: 23.76% of patients showed an increase in the SNOT score at T1, and the score decreased at T2. This could be due to the phenomenon of "adaptation" of the nasal mucosa. Endoscopic control showed that at T1, secretion, hyperemia, and edema are the most common signs. At T2, however, the crusts accounted for 52.94% of all damage. It is evident that at T1 the endoscopically detected signs of "acute" damage were more represented than at T2, while the signs of "chronic" damage increased as the number of swabs increased. CONCLUSIONS: We demonstrated that mucosal damage and perceived symptoms were absolutely acceptable compared to the diagnostic advantage obtained with serial screening.

Comparative Analysis of the Clinical Presentation of Individuals Who Test Positive or Negative for SARS-CoV-2: Results from a Test Street Study.

The common cold, the flu, and the 2019 coronavirus disease (COVID-19) have many symptoms in common. As such, without testing for severe-acute-respiratory-syndrome-related coronavirus 2 (SARS-CoV-2), it is difficult to conclude whether or not one is infected with SARS-CoV-2. The aim of the current study was to compare the presence and severity of COVID-19-related symptoms among those who tested positive or negative for the beta variant of SARS-CoV-2 (B.1.351) and identify the clinical presentation with the greatest likelihood of testing positive for SARS-CoV-2. n = 925 individuals that were tested for SARS-CoV-2 at Dutch mass testing sites (i.e., test streets) were invited to complete a short online survey. The presence and severity of 17 COVID-19-related symptoms were assessed. In addition, mood, health correlates, and quality of life were assessed for the week before the test. Of the sample, n = 88 tested positive and n = 837 tested negative for SARS-CoV-2. Individuals who tested positive for SARS-CoV-2 reported experiencing a significantly greater number, as well as greater overall symptom severity, compared to individuals who tested negative for SARS-CoV-2. A binary logistic regression analysis revealed that increased severity levels of congestion, coughing, shivering, or loss of smell were associated with an increase in the odds of testing positive for SARS-CoV-2, whereas an increase in the severity levels of runny nose, sore throat, or fatigue were associated with an increase in the odds of testing negative for SARS-CoV-2. No significant differences in mood or health correlates were found between those who tested positive or negative for SARS-CoV-2, except for a significantly higher stress score among those who tested negative for SARS-CoV-2. In conclusion, individuals that tested positive for SARS-CoV-2 experienced a significantly greater number and more severe COVID-19-related symptoms compared to those who tested negative for SARS-CoV-2. Experiencing shivering and loss of smell may be the best indicators for increased likelihood of testing positive for SARS-CoV-2.

Cost-consequence analysis of a combined COVID-19/influenza rapid diagnostic test in the Brazilian private healthcare setting.

Combination COVID-19/influenza rapid tests provide a way to quickly and accurately differentiate between the two infections. The goal of this economic evaluation was to assess the cost and health benefits of a combination COVID-19/influenza Rapid Diagnostic Test (RDT) vs. current standard-of-care in the Brazilian private healthcare setting. A dual decision tree model was developed to estimate the impact of rapid differentiation of COVID-19 and influenza in a hypothetical cohort of 1,000 adults with influenza-like illness in an ambulatory healthcare setting. The model compared the use of a combination COVID-19/influenza RDT to Brazil standard diagnostic practice of a COVID-19 RDT and presumptive influenza diagnosis. Different levels of influenza prevalence were modeled with co-infection estimated as a function of the COVID-19 prevalence. Outcomes included accuracy of diagnosis, antiviral prescriptions and healthcare resource use (hospital bed days and ICU occupancy). Depending on influenza prevalence, considering 1,000 patients with influenza-like illness, a combination RDT compared to standard practice was estimated to result in between 88 and 149 fewer missed diagnoses of influenza (including co-infection), 161 to 185 fewer cases of over-diagnosis of influenza; a 24 to 34% reduction in hospital bed days and a 16 to 26% reduction in ICU days. In the base case scenario (20% influenza, 5% COVID-19), the combination RDT was estimated to result in cohort cost savings of $99. Based upon a de novo economic model, this analysis indicates that use of a combination RDT could positively impact influenza antiviral prescriptions and lower healthcare resource use.

Test accuracy of rapid diagnostic tests and reverse-transcription polymerase chain reaction against virus isolation in cell culture for assessing SARS-CoV-2 infectivity: Systematic review and meta-analysis.

We aimed to assess the performance of Ag-RDT and RT-qPCR with regard to detecting infectious SARS-CoV-2 in cell cultures, as their diagnostic test accuracy (DTA) compared to virus isolation remains largely unknown. We searched three databases up to 15 December 2021 for DTA studies. The bivariate model was used to synthesise the estimates. Risk of bias was assessed using QUADAS-2/C. Twenty studies (2605 respiratory samples) using cell culture and at least one molecular test were identified. All studies were at high or unclear risk of bias in at least one domain. Three comparative DTA studies reported results on Ag-RDT and RT-qPCR against cell culture. Two studies evaluated RT-qPCR against cell culture only. Fifteen studies evaluated Ag-RDT against cell culture as reference standard in RT-qPCR-positive samples. For Ag-RDT, summary sensitivity was 93% (95% CI 78; 98%) and specificity 87% (95% CI 70; 95%). For RT-qPCR, summary sensitivity (continuity-corrected) was 98% (95% CI 95; 99%) and specificity 45% (95% CI 28; 63%). In studies relying on RT-qPCR-positive subsamples (n = 15), the summary sensitivity of Ag-RDT was 93% (95% CI 92; 93%) and specificity 63% (95% CI 63; 63%). Ag-RDT show moderately high sensitivity, detecting most but not all samples demonstrated to be infectious based on virus isolation. Although RT-qPCR exhibits high sensitivity across studies, its low specificity to indicate infectivity raises the question of its general superiority in all clinical settings. Study findings should be interpreted with caution due to the risk of bias, heterogeneity and the imperfect reference standard for infectivity.

Diagnostic Accuracy of the Abbott BinaxNOW COVID-19 Antigen Card Test, Puerto Rico.

BACKGROUND: The COVID-19 pandemic underscored the need for rapid and accurate diagnostic tools. In August 2020, the Abbott BinaxNOW COVID-19 Antigen Card test became available as a timely and affordable alternative for SARS-CoV-2 molecular testing, but its performance may vary due to factors including timing and symptomatology. This study evaluates BinaxNOW diagnostic performance in diverse epidemiological contexts. METHODS: Using RT-PCR as reference, we assessed performance of the BinaxNOW COVID-19 test for SARS-CoV-2 detection in anterior nasal swabs from participants of two studies in Puerto Rico from December 2020 to May 2023. Test performance was assessed by days post symptom onset, collection strategy, vaccination status, symptomatology, repeated testing, and RT-PCR cycle threshold (Ct) values. RESULTS: BinaxNOW demonstrated an overall sensitivity of 84.1% and specificity of 98.8%. Sensitivity peaked within 1-6 days after symptom onset (93.2%) and was higher for symptomatic (86.3%) than asymptomatic (67.3%) participants. Sensitivity declined over the course of infection, dropping from 96.3% in the initial test to 48.4% in testing performed 7-14 days later. BinaxNOW showed 99.5% sensitivity in participants with low Ct values (≤ 25) but lower sensitivity (18.2%) for participants with higher Cts (36-40). CONCLUSIONS: BinaxNOW demonstrated high sensitivity and specificity, particularly in early-stage infections and symptomatic participants. In situations where test sensitivity is crucial for clinical decision-making, nucleic acid amplification tests are preferred. These findings highlight the importance of considering clinical and epidemiological context when interpreting test results and emphasize the need for ongoing research to adapt testing strategies to emerging SARS-CoV-2 variants.

Rapid, Portable, and Electricity-free Sample Extraction Method for Enhanced Molecular Diagnostics in Resource-Limited Settings.

The COVID-19 pandemic has highlighted the need for rapid and reliable diagnostics that are accessible in resource-limited settings. To address this pressing issue, we have developed a rapid, portable, and electricity-free method for extracting nucleic acids from respiratory swabs (i.e. nasal, nasopharyngeal and buccal swabs), successfully demonstrating its effectiveness for the detection of SARS-CoV-2 in residual clinical specimens. Unlike traditional approaches, our solution eliminates the need for micropipettes or electrical equipment, making it user-friendly and requiring little to no training. Our method builds upon the principles of magnetic bead extraction and revolves around a low-cost plastic magnetic lid, called SmartLid, in combination with a simple disposable kit containing all required reagents conveniently prealiquoted. Here, we clinically validated the SmartLid sample preparation method in comparison to the gold standard QIAamp Viral RNA Mini Kit from QIAGEN, using 406 clinical isolates, including 161 SARS-CoV-2 positives, using the SARS-CoV-2 RT-qPCR assays developed by the US Centers for Disease Control and Prevention (CDC). The SmartLid method showed an overall sensitivity of 95.03% (95% CI: 90.44-97.83%) and a specificity of 99.59% (95% CI: 97.76-99.99%), with a positive agreement of 97.79% (95% CI: 95.84-98.98%) when compared to QIAGEN's column-based extraction method. There are clear benefits to using the SmartLid sample preparation kit: it enables swift extraction of viral nucleic acids, taking less than 5 min, without sacrificing significant accuracy when compared to more expensive and time-consuming alternatives currently available on the market. Moreover, its simplicity makes it particularly well-suited for the point-of-care where rapid results and portability are crucial. By providing an efficient and accessible means of nucleic acid extraction, our approach aims to introduce a step-change in diagnostic capabilities for resource-limited settings.

Testing behaviour change with an artificial intelligence chatbot in a randomized controlled study.

Chatbots can effect large-scale behaviour change because they are accessible through social media, flexible, scalable, and gather data automatically. Yet research on the feasibility and effectiveness of chatbot-administered behaviour change interventions is sparse. The effectiveness of established behaviour change interventions when implemented in chatbots is not guaranteed, given the unique human-machine interaction dynamics. We pilot-tested chatbot-based behaviour change through information provision and embedded animations. We evaluated whether the chatbot could increase understanding and intentions to adopt protective behaviours during the pandemic. Fifty-nine culturally and linguistically diverse participants received a compassion intervention, an exponential growth intervention, or no intervention. We measured participants' COVID-19 testing intentions and measured their staying-home attitudes before and after their chatbot interaction. We found reduced uncertainty about protective behaviours. The exponential growth intervention increased participants' testing intentions. This study provides preliminary evidence that chatbots can spark behaviour change, with applications in diverse and underrepresented groups.

Recapitulating COVID-19 detection methods: RT-PCR, sniffer dogs and electronic nose.

In December 2019, a number of subjects presenting with an unexplained pneumonia-like illness were suspected to have a link to a seafood market in Wuhan, China. Subsequently, this illness was identified as the 2019-novel coronavirus (2019-nCoV) or severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by the World Committee on Virus Classification. Since its initial identification, the virus has rapidly sperad across the globe, posing an extraordinary challenge for the medical community. Currently, the Reverse Transcriptase Polymerase Chain Reaction (RT-PCR) is considered the most reliable method for diagnosing SARS-CoV-2. This procedure involves collecting oro-pharyngeal or nasopharyngeal swabs from individuals. Nevertheless, for the early detection of low viral loads, a more sensitive technique, such as droplet digital PCR (ddPCR), has been suggested. Despite the high effectiveness of RT-PCR, there is increasing interest in utilizing highly trained dogs and electronic noses (eNoses) as alternative methods for screening asymptomatic individuals for SARS-CoV-2. These dogs and eNoses have demonstrated high sensitivity and can detect volatile organic compounds (VOCs), enabling them to distinguish between COVID-19 positive and negative individuals. This manuscript recapitulates the potential, advantages, and limitations of employing trained dogs and eNoses for the screening and control of SARS-CoV-2.