Sudden road conditions can trigger drivers' psychological stress, increasing the risk of traffic accidents. Music, as an emotion regulation tool, effectively alleviates stress and enhances psychological health. However, the effects of different genres of music on drivers' stress remain understudied.

To address this, the present study collected 120 EEG recordings from 60 drivers in a standardized simulated driving environment and developed a classification model based on EEG signals to recognize emotions. By integrating time-frequency domain features (mean, variance, skewness, kurtosis, and power spectral density) with classification algorithms, the model accurately identified slight, moderate, and severe stress states in drivers, achieving an accuracy of 90%.

Furthermore, the study evaluated the intervention effects of four types of music (joyful, sorrowful, exhilarating, and gentle) on stress using EEG signals and subjective stress ratings. The results showed that gentle music had the best stress-relieving effect in both slight and severe stress states, reducing stress by 41.67% and 45%, respectively, whereas joyful music was most effective in relieving moderate stress, reducing moderate stress by 50%. In contrast, exhilarating and sorrowful music had weaker effects. Additionally, the asymmetry of frontal pole EEG signals was found to be significantly negatively correlated with stress levels.

This finding further supports the accuracy of the emotion recognition model and the potential effectiveness of the music intervention strategy. The study demonstrates that personalized music intervention strategies can help alleviate drivers' stress, thereby improving psychological health, enhancing driving safety, and increasing driving comfort.

NCT06170320 (retrospectively registered on December 21, 2023).

This paper explores various aspects of microbiology and immunology, with a particular focus on the epidemiology and molecular characterisation of infectious diseases in the Caribbean and South America. Key areas of investigation include tuberculosis (TB), experimental vaccines, and bloodborne pathogens. A retrospective study conducted in Jamaica highlights the significance of early HIV screening, timely diagnosis, and inte-grated care. The paper also examines the challenges posed by nosocomial infections, particularly those caused by antibiotic-resistant Gram-negative bacteria and methicillin-resistant Staphylococcus aureus (MRSA), emphasising the critical importance of infection control measures. Additionally, it explores the regional microbiome, the global response to infectious diseases, and immune responses in patients with immunodeficiency disorders such as severe combined immunodeficiency (SCID) and chronic granulomatous disease (CGD), underscoring their heightened susceptibility to a wide range of infections.

This study aims to analyze the diagnostic readiness to Covid-19 and the genomic surveillance of SARS-CoV-2 in Brasília, the capital of Brazil. This is a retrospective, cross-sectional study, with data from: cases/deaths-Ministry of Health; RT-PCR analyses Brasília Central Public Health Laboratory (LACEN); genomics-Global Initiative on Sharing All Influenza Data (GISAID). It was found that in March 2021, with the Gamma variant was predominant, RT-PCR diagnostic tests administered by LACEN reached their peak, followed by a reduction, possibly due to the start of vaccination. New peaks were observed in September 2021 and January 2022. The average time for releasing RT-PCR results was reduced from eight days (July 2020), to around eight hours in 2023. The participation of private laboratories was evident in sequencing the SARS-CoV-2 variants of concern in Brasília (n = 1,897). LACEN sequenced 50% of the samples received (571). A decrease in the incidence of cases and deaths due to Covid-19 was noted in the years 2022 to 2023, following the national trend. LACEN maintained RT-PCR diagnostic tests administered satisfactorily throughout the period. Regarding the genomic surveillance of SARS-CoV-2, the vast majority of samples were sequenced by private laboratories when compared to the public laboratory.

The overuse of antibiotics has led to the global dissemination of Acinetobacter baumannii, an increasingly challenging nosocomial pathogen. This review explores the medical significance along with the diverse resistance ability of A. baumannii. Intensive care units (ICUs) serve as a breeding ground for A. baumannii, as these settings harbour vulnerable patients and facilitate the spread of opportunistic microorganisms. A. baumannii belongs to the ESKAPE group of bacterial pathogens that are major contributors to antibiotic-resistant infections. The pathogenic nature of A. baumannii is particularly evident in seriously ill patients, causing pneumonia, wound infections, and other healthcare-associated infections. Historically considered benign, A. baumannii is a global threat due to its propensity for rapid acquisition of multidrug resistance phenotypes. The genus Acinetobacter was formally recognized in 1968 following a comprehensive survey by Baumann et al., highlighting the relationship between previously identified species and consolidating them under the name Acinetobacter. A. baumannii is characterized by its Gram-negative nature, dependence on oxygen, positive catalase activity, lack of oxidase activity, inability to ferment sugars, and non-motility. The DNA G+C content of Acinetobacter species falls within a specific range. For diagnostic purposes, A. baumannii can be cultured on specific agar media, producing distinct colonies. The genus Acinetobacter comprises numerous species those are associated with bloodstream infections with high mortality rates. Therefore, A. baumannii poses a significant challenge to global healthcare due to its multidrug resistance and ability to cause various infections. A comprehensive understanding of the mechanisms underlying its resistance acquisition and pathogenicity is essential for combating this healthcare-associated pathogen effectively.

This descriptive and cross-sectional study investigated the individual factors that affect procedural pain and discomfort in individuals who had nasopharyngeal swabs by nurses.

A total of 193 participants in two COVID-19 test centers located in a city in Southeastern Türkiye between April and May 2022 were included in this study. Personal information form was used to collect data. The visual analog scale was used to assess the pain and discomfort. Risk factors related to pain and discomfort were investigated through a logistic regression model.

During the nasopharyngeal swabbing, it was determined that pain was stronger in women and those who considered nasopharyngeal swabbing as a painful procedure (p < .05). Also, discomfort was stronger in women and those who considered nasopharyngeal swabbing as an uncomfortable procedure (p < .05). It was determined that the participants' discomfort scores were higher than their pain scores.

Women and individuals with negative opinions about the procedure experienced more pain and discomfort during the nasopharyngeal swabbing. Most of the participants complained more about discomfort than pain. It is recommended to apply alternate test methods and conduct nurse-led information studies to reduce the anticipation of procedural pain/discomfort.

Dexamethasone is currently administered for Coronavirus disease 2019(COVID-19); however, there are concerns about its effect on specific antibodies' production. The aim of this study was to evaluate whether specific antibodies were affected by COVID-19 severity and corticosteroid treatment.

Of 251 confirmed COVID-19 patients admitted to our hospital between January 26 and August 10, 2020, the early period of the pandemic, 75 patients with sera within 1 month of onset and 1 month or longer were included in the research. A total of 253 serum samples from these patients were collected. The levels of specific antibodies for severe acute respiratory syndrome coronavirus 2(SARS-CoV-2), immunoglobulin G (IgG) and M (IgM), were measured retrospectively. The results were compared separately of each COVID-19 severity, and with or without corticosteroid treatment.

Among the 75 patients, 47, 18, and 10 had mild, moderate, and severe disease, respectively. The median age was 53.0 years and 22 (29%) were women. The most common comorbidities were hypertension and dyslipidemia. Corticosteroids were administered to 20 (27%) and 10 (53%), patients with moderate and severe disease, respectively. The positivity rates IgM increased first, and IgG was almost always positive after day 16, regardless of the severity of COVID-19. On days 6-10, both IgG and IgM positivity rates were higher in patients with moderate disease than in those with mild or severe disease. In patients with moderate disease, IgG positivity was similar over time, regardless of corticosteroid treatment.

In COVID-19 patients, specific IgG is positive and maintained for a long period of time, even after corticosteroid treatment. The effect of corticosteroid treatment in a COVID-19 epidemiological study using specific IgG antibodies was considered minor. COVID-19 patients were more likely to receive oxygen if IgM was positive 1 week after onset, but not mechanical ventilation. IgM measurement 1 week after onset may predict COVID-19 severity.

Numerous commercial tests for the serological diagnosis of COVID-19 have been produced in recent years. However, it is important to note that these tests exhibit significant variability in their sensitivity, specificity, and accuracy of results. Therefore, the objective of this study was to utilize bioinformatics tools to map SARS-CoV-2 peptides, with the goal of developing a new serological diagnostic test for COVID-19. Two peptides from the S protein and one from the N protein were selected and characterized in silico, chemically synthesized, and used as a serological diagnostic tool to detect IgM, IgG, and IgA anti-SARS-CoV-2 antibodies through the ELISA technique, confirmed as positive and negative samples by RT-qPCR or serology by ELISA. The results showed a sensitivity, specificity, Positive Predictive Value and Negative Predictive Value of 100% (p < 00001, 95% CI) for the proposed test. Although preliminary, this study brings proof-of-concept results that are consistent with the high-performance rates of the ELISA test when compared to other well-established methods for diagnosing COVID-19.

Aims/Background: The coronavirus disease 2019 (COVID-19) pandemic has highlighted the need for accurate and efficient diagnostic methods. This study aims to improve COVID-19 detection by integrating chest X-ray (CXR) and computerized tomography (CT) images using deep learning techniques, further improving diagnostic accuracy by using a combined imaging approach. Methods: The study used two publicly accessible databases, COVID-19 Questionnaires for Understanding the Exposure (COVID-QU-Ex) and Integrated Clinical and Translational Cancer Foundation (iCTCF), containing CXR and CT images, respectively. The proposed system employed convolutional neural networks (CNNs) for classification, specifically EfficientNet and ResNet architectures. The data underwent preprocessing steps, including image resizing, Gaussian noise addition, and data augmentation. The dataset was divided into training, validation, and test sets. Gradient-weighted Class Activation Mapping (Grad-CAM) was used for model interpretability. Results: The EfficientNet-based models outperformed the ResNet-based models across all metrics. The highest accuracy achieved was 99.44% for CXR images and 99.81% for CT images with EfficientNetB5. The models also demonstrated high precision, recall, and F1 scores. For statistical significance, the p-values were less than 0.05, indicating that the results are significant. Conclusion: Integrating CXR and CT images using deep learning significantly improves the accuracy of COVID-19 diagnosis. The EfficientNet-based models, with their superior feature extraction capabilities, show better performance than ResNet models. Grad-CAM Visualizations provide insights into the model's decision-making process, potentially reducing diagnostic errors and accelerating diagnosis processes. This approach can improve patient care and support healthcare systems in managing the pandemic more effectively.

Among immunocompromised hosts, leukemia patients, and hematopoietic cell transplant recipients are particularly vulnerable, facing challenges in balancing coronavirus disease 2019 (COVID-19) management with their underlying conditions. In this How I Treat article, we discuss how we approach severe acute respiratory syndrome coronavirus 2 infections in daily clinical practice, considering the existing body of literature and for topics where the available data are not sufficient to provide adequate guidance, we provide our opinion based on our clinical expertise and experience. Diagnostic approaches include nasopharyngeal swabs for polymerase chain reaction testing and chest computed tomography scans for symptomatic patients at risk of disease progression. Preventive measures involve strict infection control protocols and prioritizing vaccination for both patients and their families. Decisions regarding chemotherapy or hematopoietic cell transplantation in leukemia patients with COVID-19 require careful consideration of factors such as COVID-19 severity and treatment urgency. Treatment protocols include early initiation of antiviral therapy, with nirmatrelvir/ritonavir or remdesivir. For cases of prolonged viral shedding, distinguishing between viable and non-viable viruses remains challenging but is crucial for determining contagiousness and guiding management decisions. Overall, individualized approaches considering immune status, clinical presentation, and viral kinetics are essential for effectively managing COVID-19 in leukemia patients.

SARS-CoV-2 serology plays a crucial role in assessing COVID-19 vaccine immunogenicity and antibody responses to SARS-CoV-2 infection. Tube type and anticoagulant may influence serology results. Thus, understanding the influence of these variables in test results is key. We evaluated the influence of serum collection tube type and anticoagulant on anti-SARS-CoV-2 spike antibody levels detected by enzyme-linked immunosorbent assays (ELISAs) and Luminex multiplex assays (11-plex) in serum and plasma samples. Anti-spike IgG avidity was also evaluated in both sample types. No significant differences were found between serology assay results using different blood (serum) collection tube types. However, significantly lower antibody concentrations (p < 0.05) were observed in tubes with the anticoagulants sodium citrate and acid citrate dextrose (ACD) in the ELISA and Multiplex assays (n = 29), compared to expected concentrations. These differences mostly disappeared after adjusting for the dilution factor caused by the anticoagulant volume, indicating that anticoagulant does not significantly impact the assay results, while anticoagulant volume does. There was a significant difference (p < 0.05) in IgG avidity (M) of plasma samples (p < 0.05) compared to serum, but anticoagulant type had no effect. Overall, these findings indicate that the choice of collection tube may introduce subtle variations in assay results if the volumes of anticoagulants are not taken into consideration. Additionally, differences between serum and anticoagulant-treated plasma matrices were observed in avidity ELISAs, indicating that these samples are not interchangeable for these assays; a finding that requires further investigation.

Objectives This study aimed to assess the relationship between illness severity and mortality among COVID-19 patients along with the cycle threshold (Ct) value measured by viral load. Methods A cross-sectional study was conducted based on records of the emergency room at Rashid Hospital located in Dubai, United Arab Emirates. This research was carried out on all of the appropriate records of patients who were hospitalized at Rashid Hospital in Dubai between May 2020 and January 2021. Clinical and laboratory data were used as severity indicators, and in-hospital death was designated as the outcome. Results A total of 1,633 cases were included in the analysis. The percentage of deceased patients was higher in patients with a low Ct value (11.6%) than in patients with a high Ct value (6.9%) (p-value = 0.003). Logistic analysis revealed a statistically significant correlation (OR=2.046; p-value=0.002) between mortality and viral load, as measured by the Ct value. Patients with low Ct values and aberrant laboratory findings had a higher frequency of respiratory problems and required oxygen therapy, according to clinical and laboratory markers. Conclusions A correlation was found between viral load and mortality. Advanced age, history of chronic disease, and abnormal clinical and laboratory findings were all independently linked to a greater mortality rate in COVID-19 patients, indicating that they might be utilized as predictive and prognostic factors along with the viral load.

Respiratory syncytial virus (RSV) is the major cause of bronchiolitis among children under 5 years of age worldwide, accounting for a prevalence of 25%-88% in Saudi Arabia. Although no effective treatment for the virus exists, passive immunoprophylaxis reduced RSV hospitalizations in high-risk children. With recent advances in immunization, the Saudi Initiative of Bronchiolitis Diagnosis, Management, and Prevention panel screened recent relevant international guidelines, locally published data, and expert consensus to update guidelines for RSV prevention, taking into consideration the resources, timing, varying health profiles, and RSV burden in Saudi Arabia. The panel updated its recommendations to include immunization of infants, mothers, and older adults. Practical guidelines were prepared to facilitate the administration of the short-acting and newly developed long-acting RSV monoclonal antibodies (mAb) during the regular follow-ups of high-risk infants in specialized clinics. In addition, long-acting mAb was highlighted as all-infant protection in the routine immunization calendar.

Public Health Emergencies (PHE) have had repercussions on health systems on a global scale, and timely access to new health technologies is a challenge for health policy. The national regulatory authorities (NRA) play a key role in the evaluation and regulation of these technologies. The present study aims to analyze the main strategies and regulatory instruments used to deal with the challenges of regulating new technologies necessary for the health system's effective response during a PHE. This research, based on WHO and Brazilian NRA norms and documents, considered dimensions related to strategies for strengthening regulatory activities and regulatory instruments used to accelerate access to technologies, especially during PHEs. International cooperation between the NRA and the WHO were important strategies for strengthening the NRA, with emphasis on the use of reliance, regionalization, accelerated assessments, and work/information sharing, as well as the processes of regulatory harmonization and convergence. In addition to the use of existing regulatory instruments, efforts were also identified in order to implement new ones.

Objective To survey the epidemiology of respiratory pathogens during the coronavirus disease 2019 (COVID-19) pandemic using multiplex polymerase chain reaction (PCR). Methods Specimens were assayed using multiplex nested PCR. Materials Specimens were obtained from outpatients who presented with symptoms of upper respiratory tract infection and asymptomatic outpatients who had contact with patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection at Tohoku Medical and Pharmaceutical University Hospital in Sendai, Japan, from November 1, 2020, to May 31, 2023. The analysis included multiple specimens collected from the same patients at different time-points. Data were collected from the electronic records after testing. Results This study included 8,335 patients (4,311 men) with a median age of 59 years old, and 11,741 total specimens were collected. At least 1 positive SARS-CoV-2 result was obtained for 1,710 (14.6%) specimens. Furthermore, 15 pathogens were identified in the positive specimens, and rhinovirus/enterovirus was detected more frequently than other viruses. We identified a larger number of SARS-CoV-2-positive specimens in patients ≥10 years old. In contrast, in patients 0-9 years old, we identified a larger number of specimens positive for rhinovirus/enterovirus than for other viruses. Conclusion In this study, we examined the epidemiology of circulating respiratory pathogens during the COVID-19 pandemic era.

Respiratory syncytial virus (RSV) circulation dropped markedly early in the COVID-19 pandemic, followed by a resurgence with heightened case counts. The "immunity debt" hypothesis proposes that the RSV-naїve pediatric population increased during the period of low transmission. However, the evidence supporting this hypothesis is limited, and the role of changing testing practices in the perceived surge has not been comprehensively evaluated.

We conducted a multicenter, retrospective analysis of 342 530 RSV encounters and 980 546 RSV diagnostic tests occurring at 32 US pediatric hospitals in 2013-2023. We used interrupted time series analysis to estimate pandemic-associated changes in RSV patient and test volume and to quantify changes in the proportions of patients requiring hospitalization, intensive care, or mechanical ventilation. We quantified the fraction of the shifts in case counts and in the age of diagnosed patients attributable to changes in testing.

RSV patient volume increased 2.4-fold (95% confidence interval [CI]: 1.7, 3.5) in 2021-2023 relative to the pre-pandemic phase and was accompanied by an 18.9-fold increase (95% CI: 15.0, 23.9) in RSV test volume. Shifts in patient volume and in patient age were largely attributable to increased testing. The proportions of patients with RSV that required hospitalization, intensive care, or mechanical ventilation declined significantly across all patient age groups.

A surge in RSV testing, rather than in viral circulation, likely underlies the increased case counts observed in 2021-2023. These findings warrant a critical assessment of the immunity debt hypothesis and highlight the importance of considering the testing denominator when surveillance strategies are dynamic.

We consider the problem of targeted mass screening of heterogeneous populations under limited testing capacity. Mass screening is an essential tool that arises in various settings, e.g., ensuring a safe supply of blood, reducing prevalence of sexually transmitted diseases, and mitigating the spread of infectious disease outbreaks. The goal of mass screening is to classify whole population groups as positive or negative for an infectious disease as efficiently and accurately as possible. Under limited testing capacity, it is not possible to screen the entire population and hence administrators must reserve testing and target those among the population that are most in need or most susceptible. This paper addresses this decision problem by taking advantage of accessible population-level risk information to identify the optimal set of sub-populations to target for screening. We conduct a comprehensive analysis that considers the two most commonly adopted schemes: Individual testing and Dorfman group testing. For both schemes, we formulate an optimization model that aims to minimize the number of misclassifications under a testing capacity constraint. By analyzing the formulations, we establish key structural properties which we use to construct efficient and accurate solution techniques. We conduct a case study on COVID-19 in the United States using geographic-based data. Our results reveal that the considered proactive targeted schemes outperform commonly adopted practices by substantially reducing misclassifications. Our case study provides important managerial insights with regards to optimal allocation of tests, testing designs, and protocols that dictate the optimality of schemes. Such insights can inform policy-makers with tailored and implementable data-driven recommendations.

The protein-L-utilizing Förster resonance energy transfer (LFRET) assay enables mix-and-read antibody detection, as demonstrated for sera from patients with, e.g., severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Zika virus, and orthohantavirus infections. In this study, we compared paired serum and whole blood (WB) samples of COVID-19 patients and SARS-CoV-2 vaccine recipients. We found that LFRET also detects specific antibodies in WB samples. In 44 serum-WB pairs from patients with laboratory-confirmed COVID-19, LFRET showed a strong correlation between the sample materials. By analyzing 89 additional WB samples, totaling 133 WB samples, we found that LFRET results were moderately correlated with enzyme-linked immunosorbent assay results for samples collected 2 to 14 months after receiving COVID-19 diagnosis. However, the correlation decreased for samples >14 months after receiving a diagnosis. When comparing the WB LFRET results to neutralizing antibody titers, a strong correlation emerged for samples collected 1 to 14 months after receiving a diagnosis. This study also highlights the versatility of LFRET in detecting antibodies directly from WB samples and suggests that it could be employed for rapidly assessing antibody responses to infectious agents or vaccines.

The range of clinical manifestations associated with the infection by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) encompasses a broad spectrum, ranging from flu-like symptoms to the occurrence of multiple organ failure and death. The severity of the coronavirus disease 2019 (COVID-19) is categorized based on clinical presentation and is divided into three distinct levels of severity identified as non-severe, severe, and critical. Although individuals of all age groups are susceptible to SARS-CoV-2 infection, middle-aged and older adults are more frequently impacted, with the latter being more likely to develop severe illness. Various laboratory characteristics observed in hospitalized COVID-19 patients have been correlated with adverse outcomes. These include elevated levels of D-dimer, liver enzymes, lactate dehydrogenase, C-reactive protein, ferritin, prothrombin time, and troponin, as well as decreased lymphocyte and platelets counts. This review investigated the relationship between baseline clinical characteristics, initial laboratory parameters upon hospital admission, and the severity of illness and mortality rates among COVID-19 patients. Although the COVID-19 pandemic has concluded, understanding the laboratory predictors of virus severity and mortality remains crucial, and examining these predictors can have long-term effects. Such insights can help healthcare systems manage resources more effectively and deliver timely and appropriate care by identifying and targeting high-risk individuals. This knowledge can also help us better prepare for future pandemics. By examining these predictors, we can take steps to protect public health and mitigate the impact of future pandemics.

Ribonucleic acids (RNA) play active roles within cells or viruses by catalyzing biological reactions, controlling gene expression, and communicating responses to cellular signals. Rapid monitoring RNA variation has become extremely important for appropriate clinical decisions and frontier biological research. However, the most widely used method for RNA detection, nucleic acid amplification, is restricted by a mandatory temperature cycling period of ≈1 h required to reach target detection criteria. Herein, a direct detection approach via single-atom site integrated surface-enhanced Raman scattering (SERS) monitoring nucleic acid pairing reaction, can be completed within 3 min and reaches high sensitivity and extreme reproducibility for COVID-19 and two other influenza viruses' detection. The mechanism is that a single-atom site on SERS chip, enabled by positioning a single-atom oxide coordinated with a specific complementary RNA probe on chip nanostructure hotspots, can effectively bind target RNA analytes to enrich them at designed sites so that the binding reaction can be detected through Raman signal variation. This ultrafast, sensitive, and reproducible single-atom site SERS chip approach paves the route for an alternative technique of immediate RNA detection. Moreover, single-atom site SERS is a novel surface enrichment strategy for SERS active sites for other analytes at ultralow concentrations.

Confirmed COVID-19 diagnoses underestimate the total number of infections. Blood donors can provide representative seroprevalence estimates, which can be leveraged into reasonable estimates of total infection counts and infection fatality rate (IFR).

Blood donors who donated after each of three epidemic waves (Beta, Delta and first Omicron waves) were tested for anti-SARS-CoV-2 nucleocapsid antibodies using the Roche Elecsys anti-SARS-CoV-2 total immunoglobulin assay. Roche Elecsys anti-spike antibody testing was done for the post-Omicron sampling. Prevalence of antibodies was estimated by age, sex, race and province and compared to official case reporting. Province and age group-specific IFRs were estimated using external excess mortality estimates.

The nationally weighted anti-nucleocapsid seroprevalence estimates after the Beta, Delta and Omicron waves were 47% (46.2%-48.6%), 71% (68.8%-73.5%) and 87% (85.5%-88.4%), respectively. There was no variation by age and sex, but there were statistically and epidemiologically significant differences by province (except at the latest time point) and race. There was a 13-fold higher seroprevalence than confirmed case counts at the first time point. Age-dependent IFR roughly doubled for every 10 years of age increase over 6 decades from 0.014% in children to 6.793% in octogenarians.

Discrepancies were found between seroprevalence and confirmed case counts. High seroprevalence rates found among Black African donors can be ascribed to historical inequities. Our IFR estimates were useful in refining previous large disagreements about the severity of the epidemic in South Africa. Blood donor-based serosurveys provided a valuable and efficient way to provide near real-time monitoring of the ongoing SARS-CoV-2 outbreak.

The incidence of respiratory syncytial virus (RSV) dropped markedly early in the COVID-19 pandemic, followed by a resurgence with heightened case counts. The "immunity debt" hypothesis proposes that the RSV-naive pediatric population increased during the period of low transmission, resulting in a subsequent increased risk of infection. However, the evidence supporting this hypothesis is limited, and no studies have comprehensively evaluated the role of changing respiratory viral testing practices in the perceived surge.

We conducted a multicenter, retrospective analysis of 342,530 RSV encounters and 980,546 RSV diagnostic tests occurring at 32 United States pediatric hospitals between 2013 and 2023. We used interrupted time series analysis to estimate pandemic-associated changes in RSV patient and testing volume, and to quantify changes in the proportions of patients admitted from the emergency department (ED), admitted to the intensive care unit (ICU), and receiving mechanical ventilation. We quantified the fraction of the observed shifts in case counts and in the age of diagnosed patients attributable to changes in RSV testing practices. Finally, we analyzed 524,404 influenza virus encounters and 1,768,526 influenza diagnostic tests to address the specificity of the findings to RSV.

RSV patient volume increased 2.4-fold (95% CI: 1.7, 3.5) in 2021-2023 relative to the pre-pandemic phase, and was accompanied by an 18.9-fold increase (95% CI: 15.0, 23.9) in RSV test volume. Over two-thirds of the apparent shifts in patient volume and in patient age were attributable to increased testing, which was concentrated among older pediatric patients. The proportions of patients with RSV requiring hospitalization, intensive care, or mechanical ventilation declined significantly across all patient age groups. These declines were not observed for patients with influenza virus.

A surge in RSV testing, rather than in viral circulation, likely underlies the increased case counts observed in 2021-2023. We identify expected consequences of increased testing, including the diagnosis of less severe cases and a shift in the patient age distribution. These findings warrant a critical assessment of the immunity debt hypothesis, while highlighting the importance of considering the testing denominator when surveillance strategies are dynamic.

National Institutes of Health & Howard Hughes Medical Institute.

Rapid, sensitive, inexpensive point-of-care molecular diagnostics are crucial for the efficient control of spreading viral diseases and biosecurity of global health. However, the gold standard, polymerase chain reaction (PCR) is time-consuming and expensive and needs specialized testing laboratories. Here, we report a low-cost yet fast, selective, and sensitive Plasmonic Optical Wells-Based Enhanced Rate PCR: POWER-PCR. We optimized the efficient optofluidic design of 3D plasmonic optical wells via the computational simulation of light-to-heat conversion and thermophoretic convection in a self-created plasmonic cavity. The POWER-PCR chamber with a self-passivation layer can concentrate incident light to accumulate molecules, generate rapid heat transfer and thermophoretic flow, and minimize the quenching effect on the naked Au surface. Notably, we achieved swift photothermal cycling of nucleic acid amplification in POWER-PCR on-a-chip in 4 min 24 s. The POWER-PCR will provide an excellent solution for affordable and sensitive molecular diagnostics for precision medicine and preventive global healthcare.

COVID-19 made explicit the need for rethinking the way in which we conduct testing for epidemic emergencies. During the COVID-19 pandemic, the dependence on centralized lab facilities and resource-intensive methodologies (e.g., RT-qPCR methods) greatly limited the deployment of widespread testing efforts in many developed and underdeveloped countries. Here, we illustrate the development of a simple and portable diagnostic kit that enables self-diagnosis of COVID-19 at home from saliva samples. We describe the development of a do-it-yourself (DIY) incubator for Eppendorf tubes that can be used to conduct SARS-CoV-2 detection with competitive sensitivity and selectivity from saliva at home. In a proof-of-concept experiment, we assembled Eppendorf-tube incubators at our home shop, prepared a single-tube mix of reagents and LAMP primers in our lab, and deployed these COVID-19 detection kits using urban delivery systems (i.e., Rappifavor or Uber) to more than 15 different locations in Monterrey, México. This straightforward strategy enabled rapid and cost-effective at-home molecular diagnostics of SARS-CoV-2 from real saliva samples with a high sensitivity (100%) and high selectivity (87%).

To carry out effective and quick identification of SARS-CoV-2 from nasopharyngeal swabs and contain outbreaks, reliable and rapid tools are needed. Herein, we compared a rapid antigen test based on active microfluidic technology to an RT-qPCR assay in pediatric and young adult patients admitted to the Pediatric Emergency Unit of a Children's Hospital. Nasopharyngeal swabs collected from patients with suspected COVID-19 disease and from those without COVID-19 related symptoms, but requiring hospitalization, were performed with both antigen test and RT-qPCR assays. We included 375 patients with a median age of 5 years in the study, with an estimated overall prevalence of 7.2%. Overall, we observed a specificity of 97.4% (95% CI: 94.9-98.7) and a sensitivity of 66.6% (95% CI: 46.0-82.7) with a positive likelihood ratio (LR+) of 25.8 (95% CI: 12.8-51.8). In the subgroup of symptomatic patients, the specificity and the sensitivity were 95.2% (95% CI: 89.4-98.0) and 80.0% (95% CI: 44.2-96.5) respectively; LR+ was 16.6 (95% CI: 7.19-38.6). In the asymptomatic subset, the performance showed a specificity of 98.7% (95% CI: 95.8-99.7), a sensitivity of 58.8% (95% CI: 33.5-80.6), and an LR+ of 43.7 (95% CI: 13.3-144.0). Compared to RT-qPCR, the new microfluidic-based antigen test showed higher specificity (>95%) in the pediatric population, thus representing a suitable point-of-care testing (POCT) in a clinical setting with low prevalence of COVID-19.

Healthcare-associated influenza is frequently encountered in healthcare settings with significant morbidity and mortality among vulnerable patients, absenteeism among healthcare personnel (HCP), and interruption of healthcare services. Numerous investigations indicate that nosocomial outbreaks are often traced to HCP. Despite the international and national endorsements, seasonal influenza vaccine acceptance among HCP continues suboptimal worldwide. Infection control is the major objective for healthcare risk management in order to guarantee patient safety, limit the cost of hospitalization and assurance health management in controlling influenza seasons. Vigilance and anticipation are required as globally we are moving from a reactive COVID-19 pandemic response phase to one of planning for the co-circulation of viral respiratory infections. Declining to understand HCP perception of influenza risk and acceptance of vaccination might have impact patient safety as well as healthcare services.

Systematic review of SARS-CoV-2 seroprevalence studies undertaken in the WHO European Region to measure pre-existing and cumulative seropositivity prior to the roll out of vaccination programmes.

A systematic review of the literature.

We searched MEDLINE, EMBASE and the preprint servers MedRxiv and BioRxiv in the WHO 'COVID-19 Global literature on coronavirus disease' database using a predefined search strategy. Articles were supplemented with unpublished WHO-supported Unity-aligned seroprevalence studies and other studies reported directly to WHO Regional Office for Europe and European Centre for Disease Prevention and Control.

Studies published before the widespread implementation of COVID-19 vaccination programmes in January 2021 among the general population and blood donors, at national and regional levels.

At least two independent researchers extracted the eligible studies; a third researcher resolved any disagreements. Study risk of bias was assessed using a quality scoring system based on sample size, sampling and testing methodologies.

In total, 111 studies from 26 countries published or conducted between 1 January 2020 and 31 December 2020 across the WHO European Region were included. A significant heterogeneity in implementation was noted across the studies, with a paucity of studies from the east of the Region. Sixty-four (58%) studies were assessed to be of medium to high risk of bias. Overall, SARS-CoV-2 seropositivity prior to widespread community circulation was very low. National seroprevalence estimates after circulation started ranged from 0% to 51.3% (median 2.2% (IQR 0.7-5.2%); n=124), while subnational estimates ranged from 0% to 52% (median 5.8% (IQR 2.3%-12%); n=101), with the highest estimates in areas following widespread local transmission.

The low levels of SARS-CoV-2 antibody in most populations prior to the start of vaccine programmes underlines the critical importance of targeted vaccination of priority groups at risk of severe disease, while maintaining reduced levels of transmission to minimise population morbidity and mortality.

Background Cell-mediated immunity (CMI), or specifically T-cell-mediated immunity, is proven to remain largely preserved against the variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), including Omicron. The persistence of cell-mediated immune response in individuals longitudinally followed up for an extended period remains largely unelucidated. To address this, the current study was planned to study whether the effect of cell-mediated immunity persists after an extended period of convalescence or vaccination. Methods Whole blood specimens of 150 selected participants were collected and tested for Anti-SARS-CoV-2 Interferon-gamma (IFN-γ) response. Ex vivo SARS-CoV-2-specific interferon-gamma Enzyme-linked Immunospot (IFN-γ ELISpot) assay was carried out to determine the levels of virus-specific IFN-γ producing cells in individual samples. Findings Out of all the samples tested for anti-SARS-CoV-2 T-cell-mediated IFN-γ response, 78.4% of samples were positive. The median (interquartile range) spots forming units (SFU) per million levels of SARS-CoV-2-specific IFN-γ producing cells of the vaccinated and diagnosed participants was 336 (138-474) while those who were vaccinated but did not have the disease diagnosis was 18 (0-102); the difference between the groups was statistically significant. Since almost all the participants were vaccinated, a similar pattern of significance was observed when the diagnosed and the never-diagnosed participants were compared, irrespective of their vaccination status. Interpretations Cell-mediated immunity against SARS-CoV-2 persisted, irrespective of age and sex of the participant, for more than six months of previous exposure. Participants who had a history of diagnosed COVID-19 infection had better T-cell response compared to those who had never been diagnosed, in spite of being vaccinated.

The COVID-19 pandemic has had a significant impact on human health management. A rapid diagnosis of SARS-CoV2 at the point-of-care (POC) is critical to prevent disease spread. As a POC device for remote settings, a LFIA should not require cold-chain maintenance and should be kept at normal temperatures. Antigen stability can be enhanced by addressing instability issues when dealing with fragile components, such as proteinaceous capture antigens. This study used immunologically guided protein engineering to enhance the capture nucleocapsid (NP) antigen stability of SARS-CoV2. A search of the IEDB database revealed that antibodies detecting epitopes are almost uniformly distributed over NP1-419. In contrast, N-terminal stretches of NP1-419 are theoretically more unstable than C-terminal stretches. We identified NP250-365 as a NP stretch with a low instability index and B-cell epitopes. Apart from NP1-419, two other variants (NP121-419 and NP250-365) were cloned, expressed, and purified. The degradation pattern of the proteins was observed on SDS-PAGE after three days of stability studies at -20 °C, 4 °C, and 37 °C. NP1-419 was the most degraded while NP250-365 exhibited the least degradation. Also, NP1-419, NP250-365, and NP121-419 reacted with purified antibodies from COVID-19 patient serum. Our results suggest that NP250-365 may be used as a stable capture antigen in LFIA devices to detect COVID-19.

To evaluate the cost-effectiveness ratio and economic impact of the Rapid Antigen Test (TR-Ag) to replace RT-PCR for the detection of the new Coronavirus in the Unified Health System (SUS).

This is a cost-effectiveness analysis. Clinical protocols were used for the diagnosis of COVID-19 at the São José Municipal Hospital, located in the city of Itaberá-SP. The Incremental Cost-Effectiveness Ratio (ICER) was divided into two scenarios. In the first, the accuracy reported by the test manufacturers was included, and in the second, the cost resulting from a systematic review. Both were compared with the performance of the RT-PCR test. The increase in diagnoses was chosen as a health outcome and absenteeism was used as a criterion for assessing the economic impact.

The analysis resulted in incremental cost-effectiveness ratios of R$ 42,136.67 and R$ 68,329.73 for every thousand tests, according to the accuracy of the manufacturers' TR-Ag tests and what is reported in the literature in relation to RT-PCR, respectively. The average value found for the RT-PCR test (R$ 202.87) represents an increase of 165.32% in cost in relation to the value found for the TR-Ag. 4,305 tests were performed between April 2020 and December 2021 at the referral hospital. Also, maintaining the use of RT-PCR as the first choice for diagnosing COVID-19 and regulating absenteeism in the economically active population could have an impact of up to R$ 1,022,779.68 on municipal management.

It is concluded that the TR-Ag are configured as a cost-effective alternative for the SUS in the detection of the new Coronavirus. The strategy becomes economically favorable for the expansion of testing, combating the COVID-19 pandemic and reducing the impact on the local economy. However, studies are needed to validate the accuracy of the tests so that economic evaluations on the subject are more assertive.

During the global pandemic crisis, various detection methods of COVID-19-positive cases based on self-reported information were introduced to provide quick diagnosis tools for effectively planning and managing healthcare resources. These methods typically identify positive cases based on a particular combination of symptoms, and they have been evaluated using different datasets.

This paper presents a comprehensive comparison of various COVID-19 detection methods based on self-reported information using the University of Maryland Global COVID-19 Trends and Impact Survey (UMD-CTIS), a large health surveillance platform, which was launched in partnership with Facebook.

Detection methods were implemented to identify COVID-19-positive cases among UMD-CTIS participants reporting at least one symptom and a recent antigen test result (positive or negative) for six countries and two periods. Multiple detection methods were implemented for three different categories: rule-based approaches, logistic regression techniques, and tree-based machine-learning models. These methods were evaluated using different metrics including F1-score, sensitivity, specificity, and precision. An explainability analysis has also been conducted to compare methods.

Fifteen methods were evaluated for six countries and two periods. We identify the best method for each category: rule-based methods (F1-score: 51.48% - 71.11%), logistic regression techniques (F1-score: 39.91% - 71.13%), and tree-based machine learning models (F1-score: 45.07% - 73.72%). According to the explainability analysis, the relevance of the reported symptoms in COVID-19 detection varies between countries and years. However, there are two variables consistently relevant across approaches: stuffy or runny nose, and aches or muscle pain.

Regarding the categories of detection methods, evaluating detection methods using homogeneous data across countries and years provides a solid and consistent comparison. An explainability analysis of a tree-based machine-learning model can assist in identifying infected individuals specifically based on their relevant symptoms. This study is limited by the self-report nature of data, which cannot replace clinical diagnosis.

The Danish national SARS-CoV-2 mass test system was among the most ambitious worldwide. We describe its set-up and analyse differences in patterns of testing per demography and time period in relation to the three waves of SARS-CoV-2 transmission in Denmark.

We included all reported PCR- and rapid antigen-tests performed between 27 February 2020 and 10 March 2022 among all residents aged 2 years or above. Descriptive statistics and Poisson regression models were used to analyse characteristics of individuals tested for SARS-CoV-2 using a national cohort study design.

A total of 63.7 million PCR-tests and 60.0 million rapid antigen-tests were performed in the study period, testing 90.9% and 78.8% of the Danish population at least once by PCR or antigen, respectively. Female sex, younger age, Danish heritage and living in the capital area were all factors positively associated with the frequency of PCR-testing. The association between COVID-19 vaccination and PCR-testing changed from negative to positive over time.

We provide details of the widely available, free-of-charge, national SARS-CoV-2 test system, which served to identify infected individuals, assist isolation of infectious individuals and contact tracing, and thereby mitigating the spread of SARS-CoV-2 in the Danish population. The test system was utilized by nearly the entire population at least once, and widely accepted across different demographic groups. However, demographic differences in the test uptake did exist and should be considered in order not to cause biases in studies related to SARS-CoV-2, e.g., studies of transmission and vaccine effectiveness.

The study of the mechanisms of transmission of the SARS-CoV-2 virus is the basis for building a strategy for anti-epidemic measures in the context of the COVID-19 pandemic. Understanding in what time frame a patient can spread SARS-CoV-2 is just as important as knowing the transmission mechanisms themselves. This information is necessary to develop effective measures to prevent infection by breaking the chains of transmission of the virus. The aim of the work is to identify the infectious SARS-CoV-2 virus in patient samples in the course of the disease and to determine the duration of virus shedding in patients with varying severity of COVID-19.

In patients included in the study, biomaterial (nasopharyngeal swabs) was subjected to analysis by quantitative RT-PCR and virological determination of infectivity of the virus.

We have determined the timeframe of maintaining the infectivity of the virus in patients hospitalized with severe and moderate COVID-19. Based on the results of the study, we made an analysis of the relationship between the amount of detected SARS-CoV-2 RNA and the infectivity of the virus in vitro in patients with COVID-19. The median time of the infectious virus shedding was 8 days. In addition, a comparative analysis of different protocols for the detection of the viral RNA in relation to the identification of the infectious virus was carried out.

The obtained data make it possible to assess the dynamics of SARS-CoV-2 detection and viral load in patients with COVID-19 and indicate the significance of these parameters for the subsequent spread of the virus and the organization of preventive measures.

This study aimed to evaluate the performance characteristics of a rapid antigen test developed to detect SARS-CoV-2 (COVID-19), influenza A virus (IAV), and influenza B virus (IBV) (flu) compared with those of the real-time reverse transcription-polymerase chain reaction (rRT-PCR) method. One hundred SARS-CoV-2, one hundred IAV, and twenty-four IBV patients whose diagnoses were confirmed by clinical and laboratory methods were included in the patient group. Seventy-six patients, who were negative for all respiratory tract viruses, were included as the control group. The Panbio™ COVID-19/Flu A&B Rapid Panel test kit was used in the assays. The sensitivity values of the kit were 97.5%, 97.9%, and 33.33% for SARS-CoV-2, IAV, and IBV, respectively, in samples with a viral load below 20 Ct values. The sensitivity values of the kit were 16.7%, 36.5%, and 11.11% for SARS-CoV-2, IAV, and IBV, respectively, in samples with a viral load above 20 Ct. The kit's specificity was 100%. In conclusion, this kit demonstrated high sensitivity to SARS-CoV-2 and IAV for viral loads below 20 Ct values, but the sensitivity values were not compatible with PCR positivity for lower viral loads over 20 Ct values. Rapid antigen tests may be preferred as a routine screening tool in communal environments, especially in symptomatic individuals, when diagnosing SARS-CoV-2, IAV, and IBV with high caution.

Background RSNA consensus guidelines for COVID-19-related chest CT are widely used but, to the knowledge of the authors, their rate of true-positive findings for COVID-19 pneumonia in vaccinated patients has not been assessed. Purpose To assess the rate of true-positive findings of typical appearance for COVID-19 at chest CT by using RSNA guidelines in fully vaccinated patients with polymerase chain reaction (PCR)-confirmed COVID-19 infection compared with unvaccinated patients. Materials and Methods Included were patients with COVID-19 who had typical appearance on chest CT images and one PCR test for COVID-19 with a positive result or two tests with negative results within 7 days of undergoing chest CT between January 2021 and January 2022 at a quaternary academic medical center. True-positive findings were defined as chest CT images interpreted as COVID-19 typical appearance and PCR-confirmed COVID-19 infection within 7 days. Logistic regression models were constructed to quantify the association between PCR results and vaccination status, vaccination status and COVID-19 variants, and vaccination status and number of months. Results Included were 652 patients (median age, 59 years; IQR, 48-72 years; 371 men [57%]) with CT scans classified as typical appearance. Of those patients, 483 (74%) were unvaccinated and 169 (26%) were fully vaccinated. The overall rate of true-positive findings on CT images rated as typical appearance was lower in vaccinated versus unvaccinated patients (70 of 169 [41%; 95% CI: 34, 49] vs 352 of 483 [73%; 95% CI: 69, 77]; odds ratio [OR], 3.8 [95% CI: 2.6, 5.5]; P < .001). Unvaccinated patients were more likely to have true-positive findings on CT images compared with fully vaccinated patients during the peaks of COVID-19 variants Alpha (OR, 16; 95% CI: 6, 42; P < .001) and Delta (OR, 8; 95% CI: 4, 16; P < .001), but no statistical differences were found during the peak of the Omicron variant (OR, 1.7; 95% CI: 0.3, 11; P = .56). Conclusion Fully vaccinated patients with confirmed COVID-19 breakthrough infections had lower rates of true-positive findings of COVID-19 typical appearance at chest CT. © RSNA, 2022 Supplemental material is available for this article.

Fast, precise, and low-cost diagnostic testing to identify persons infected with SARS-CoV-2 virus is pivotal to control the global pandemic of COVID-19 that began in late 2019. The gold standard method of diagnostic recommended is the RT-qPCR test. However, this method is not universally available, and is time-consuming and requires specialized personnel, as well as sophisticated laboratories. Currently, machine learning is a useful predictive tool for biomedical applications, being able to classify data from diverse nature. Relying on the artificial intelligence learning process, spectroscopic data from nasopharyngeal swab and tracheal aspirate samples can be used to leverage characteristic patterns and nuances in healthy and infected body fluids, which allows to identify infection regardless of symptoms or any other clinical or laboratorial tests. Hence, when new measurements are performed on samples of unknown status and the corresponding data is submitted to such an algorithm, it will be possible to predict whether the source individual is infected or not. This work presents a new methodology for rapid and precise label-free diagnosing of SARS-CoV-2 infection in clinical samples, which combines spectroscopic data acquisition and analysis via artificial intelligence algorithms. Our results show an accuracy of 85% for detection of SARS-CoV-2 in nasopharyngeal swab samples collected from asymptomatic patients or with mild symptoms, as well as an accuracy of 97% in tracheal aspirate samples collected from critically ill COVID-19 patients under mechanical ventilation. Moreover, the acquisition and processing of the information is fast, simple, and cheaper than traditional approaches, suggesting this methodology as a promising tool for biomedical diagnosis vis-à-vis the emerging and re-emerging viral SARS-CoV-2 variant threats in the future.

This prospective study aimed to evaluate the performance of the InstaView COVID-19 (coronavirus diseases 2019) Antigen Home Test (InstaView AHT) which detects severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antigens. In this test kit, surface-enhanced Raman spectroscopy was used, a stacking pad was inserted, and nasal swab and salivary swab samples were used simultaneously to improve performance. The clinical performance of the InstaView AHT was compared to that of RT-PCR using nasopharyngeal samples. The participants without any prior training were recruited and performed the sample collection, testing, and interpretation of the results by themselves. Of the 91 PCR-positive patients, 85 had positive InstaView AHT results. The sensitivity and specificity of the InstaView AHT were 93.4% (95% confidence interval [CI]: 86.2-97.5) and 99.4% (95% CI: 98.2-99.9). The sensitivity of the InstaView AHT was above 90% for all samples obtained from patients with Ct ≤ 20, 20 < Ct ≤ 25, and 25 < Ct ≤ 30 (100%, 95.1%, and 92.0%, respectively). The InstaView AHT can be used as an alternative to RT-PCR testing because of its relatively high sensitivity and specificity, especially when SARS-CoV-2 prevalence is high, and the availability of RT-PCR testing is limited.

Development and validation of rapid and easy-to-perform diagnostics continue to be a high priority during the current COVID-19 pandemic. Although vaccines are now widely available, early detection and consistent transmission control provide ideal means to mitigate the spread of SARS-CoV-2. Nucleic acid-based real-time PCR tests are widely acknowledged as the gold standard for reliable diagnosis of COVID-19 infection. These tests are based on detecting viable or nonviable viral nucleic acids. SARS-CoV-2 spike protein is an alternative and ideal target for SARS-CoV-2 diagnosis in the early phase of infection, but point-of-care kits to detect the SARS-CoV-2 spike protein are limited. Here we describe a rapid and convenient method based on Lateral Flow Immunoassay (LFIA) to detect SARS-CoV-2 spike proteins, including SARS-CoV-2 variants (A.23.1, B.1.1.1, 1.617.2, B.1.1.7, B.1.351, P.1, N501Y, R.1, P681H, P3, UK, and South African) within 5 to 10 minutes. We generated highly specific monoclonal antibodies (mAbs) against rationally designed SARS-CoV-2 spike protein. Matched pair mAbs were selected by epitope mapping and employed as antigen capture reagents by spotting onto a nitrocellulose membrane and as detector reagents by conjugation with colloidal gold nanoparticles. We evaluated the performance of the LFIA using recombinant spike proteins of SARS-CoV-2 and several SARS-CoV-2 variants. The specificity of the LFIA was assessed using heat-inactivated SARS-CoV-2 and related human coronaviruses (HCoV-OC43, HCoV-229E, HCoV-HKU1, and HCoV-NL63) and an FDA-approved respiratory pathogens (RP) panel. The assay exhibited 98% specificity and acceptable performance with respect to the minimum limit of detection (25 ng/test) in validation tests. This new LFIA provides improved performance for the early diagnosis of SARS-CoV-2, particularly for home monitoring and in situations with limited access to molecular methods.

The COVID-19 pandemic has highlighted the urgent need for sensitive, affordable, and widely accessible testing at the point of care. Here we demonstrate a new, universal LFA platform technology using M13 phage conjugated with antibodies and HRP enzymes that offers high analytical sensitivity and excellent performance in a complex clinical matrix. We also report its complete integration into a sensitive chemiluminescence-based smartphone-readable lateral flow assay for the detection of SARS-CoV-2 nucleoprotein. We screened 84 anti-nucleoprotein monoclonal antibody pairs in phage LFA and identified an antibody pair that gave an LoD of 25 pg mL-1 nucleoprotein in nasal swab extract using a FluorChem gel documentation system and 100 pg mL-1 when the test was imaged and analyzed by an in-house-developed smartphone reader. The smartphone-read LFA signals for positive clinical samples tested (N = 15, with known Ct) were statistically different (p < 0.001) from signals for negative clinical samples (N = 11). The phage LFA technology combined with smartphone chemiluminescence imaging can enable the timely development of ultrasensitive, affordable point-of-care testing platforms for SARS-CoV-2 and beyond.

Human antibodies are produced due to the activation of immune system components upon exposure to an external agent or antigen. Human antibody G, or immunoglobin G (IgG), accounts for 75% of total serum antibody content. IgG controls several infections by eradicating disease-causing pathogens from the body through complementary interactions with toxins. Additionally, IgG is an important diagnostic tool for certain pathological conditions, such as autoimmune hepatitis, hepatitis B virus (HBV), chickenpox and MMR (measles, mumps, and rubella), and coronavirus-induced disease 19 (COVID-19). As an important biomarker, IgG has sparked interest in conducting research to produce robust, sensitive, selective, and economical biosensors for its detection. To date, researchers have used different strategies and explored various materials from macro- to nanoscale to be used in IgG biosensing. In this review, emerging biosensors for IgG detection have been reviewed along with their detection limits, especially electrochemical biosensors that, when coupled with nanomaterials, can help to achieve the characteristics of a reliable IgG biosensor. Furthermore, this review can assist scientists in developing strategies for future research not only for IgG biosensors but also for the development of other biosensing systems for diverse targets.

Due to the high transmissibility of SARS-CoV-2, accurate diagnosis is essential for effective infection control, but the gold standard, real-time reverse transcriptase-polymerase chain reaction (RT-PCR), is costly, slow, and test capacity has at times been insufficient. We compared the accuracy of clinician diagnosis of COVID-19 against RT-PCR in a general adult population.

COVID-19 diagnosis data by 30th September 2021 for participants in an ongoing population-based cohort study of adults in Western Sweden were retrieved from registers, based on positive RT-PCR and clinician diagnosis using recommended ICD-10 codes. We calculated accuracy measures of clinician diagnosis using RT-PCR as reference for all subjects and stratified by age, gender, BMI, and comorbidity collected pre-COVID-19.

Of 42,621 subjects, 3,936 (9.2%) and 5705 (13.4%) had had COVID-19 identified by RT-PCR and clinician diagnosis, respectively. Sensitivity and specificity of clinician diagnosis against RT-PCR were 78% (95%CI 77-80%) and 93% (95%CI 93-93%), respectively. Positive predictive value (PPV) was 54% (95%CI 53-55%), while negative predictive value (NPV) was 98% (95%CI 98-98%) and Youden's index 71% (95%CI 70-72%). These estimates were similar between men and women, across age groups, BMI categories, and between patients with and without asthma. However, while specificity, NPV, and Youden's index were similar between patients with and without chronic obstructive pulmonary disease (COPD), sensitivity was slightly higher in patients with (84% [95%CI 74-90%]) than those without (78% [95%CI 77-79%]) COPD.

The accuracy of clinician diagnosis for COVID-19 is adequate, regardless of gender, age, BMI, and asthma, and thus can be used for screening purposes to supplement RT-PCR.