Rapid COVID-19 Research Articles

Marburg virus reaches Rwanda: how close are we to a vaccine solution?

Marburg virus disease (MVD) is a highly virulent and often fatal disease caused by the Marburg virus, a member of the Filoviridae family, closely related to the Ebola virus. Historically, outbreaks have been sporadic but lethal across various African countries, with high case fatality rates (CFRs). In 2023, significant outbreaks occurred in Tanzania and Equatorial Guinea, with CFRs of 62.5% and 75%, respectively. In 2024, Rwanda faced its first outbreak, starting on September 27, 2024. By November 8, 2024, Rwanda had conducted 7,408 tests, confirming 66 cases, 15 of which were fatal, and 51 recoveries. Although no approved vaccine currently exists for MVD, global health authorities are prioritizing the development of effective vaccines. Drawing on insights from the rapid COVID-19 vaccine development, several promising candidates are under exploration, with the cAd3-MARV showing notable potential. This paper examines the current MVD outbreak in Rwanda and the progress toward developing a long-term vaccine solution.

Analyzing usage patterns from video data through deep learning: The case of an urban park

Rapid urbanization, urban density, and COVID-19 effects have highlighted the need for high-quality urban parks within walking distance. A high-quality urban park maximizes a neighborhood's spatial, safety, and social potential, which are key factors to the well-being of its residents. Most studies evaluating urban parks rely on questionnaires, observations, interviews, and post-occupancy methods. These traditional methods are limited regarding the spatial and temporal dimensions as well as the size of the sample under investigation. In this paper, we demonstrate a new approach to evaluating urban parks by focusing on individuals' activity patterns, using big data extracted from city cameras by utilizing deep learning and computer vision. Our case study is a small urban park, Katznelson Garden, located in Or Yehuda, Israel. The imagery data is analyzed in relation to the gender of the parks' users, along with spatial and temporal analysis. Thus, activities during different hours of the day, days of the week, and in various parts of the urban park are identified. The results of our study revealed that females' and males' activity patterns are different and depend on the hour of the day and the type of park characteristics. Moreover, we found that activity levels and patterns varied according to the day of the week. As many cities seek to design better urban parks tailored to their residents' needs, these study findings can contribute to planning decisions by paving the way to customizing the design of urban parks in accordance with the revealed behavior.

Harnessing AI for advancing pathogenic microbiology: a bibliometric and topic modeling approach.

The integration of artificial intelligence (AI) in pathogenic microbiology has accelerated research and innovation. This study aims to explore the evolution and trends of AI applications in this domain, providing insights into how AI is transforming research and practice in pathogenic microbiology. We employed bibliometric analysis and topic modeling to examine 27,420 publications from the Web of Science Core Collection, covering the period from 2010 to 2024. These methods enabled us to identify key trends, research areas, and the geographical distribution of research efforts. Since 2016, there has been an exponential increase in AI-related publications, with significant contributions from China and the USA. Our analysis identified eight major AI application areas: pathogen detection, antibiotic resistance prediction, transmission modeling, genomic analysis, therapeutic optimization, ecological profiling, vaccine development, and data management systems. Notably, we found significant lexical overlaps between these areas, especially between drug resistance and vaccine development, suggesting an interconnected research landscape. AI is increasingly moving from laboratory research to clinical applications, enhancing hospital operations and public health strategies. It plays a vital role in optimizing pathogen detection, improving diagnostic speed, treatment efficacy, and disease control, particularly through advancements in rapid antibiotic susceptibility testing and COVID-19 vaccine development. This study highlights the current status, progress, and challenges of AI in pathogenic microbiology, guiding future research directions, resource allocation, and policy-making.

A Comparison of Clinical and Laboratory Features in Neonatal Proven Sepsis and COVID-19

Background: The clinical manifestations of COVID-19 in neonates are generally mild and commonly require only supportive treatment. However, it is important to note that they can sometimes present with symptoms like bacterial sepsis, which can lead to confusion in diagnosis. In this study, our objective was to compare laboratory data and clinical manifestations between 2 groups to identify opportunities for reducing the unnecessary use of antibiotics. Methods: The study was conducted as a cross-sectional study between January 2020 and 2023 on neonates who were admitted to the neonatal intensive care unit or the neonatal ward of Children’s Medical Center in Tehran, Iran. We specifically compared the laboratory data and clinical characteristics of neonates who tested positive for either a blood culture or a reverse transcription polymerase chain reaction for COVID-19. Results: Sixty-seven neonates in COVID-19 group and 68 neonates in the bacterial sepsis group entered. Prominent symptoms in the bacterial sepsis group include vomiting, seizure, apnea, mottling, increased need for ventilation and laboratory findings showing elevated levels of C-reactive protein and thrombocytopenia. In the COVID-19 group, patient exhibit symptoms such as cough, diarrhea, fever and laboratory findings that indicate neutropenia and leukopenia. Symptoms of nervous involvement were rare in this group. Conclusion: It is crucial to carefully assess the symptoms, laboratory results and overall condition of the patient before deciding on antibiotic initiation. By combining rapid COVID-19 testing and clinical variables, it is possible to identify low-risk infants who are unlikely to have bacterial infections.

Novel metal–organic framework biosensing platform for detection of COVID-19 RNA

The latest pandemic resulting from the novel SARS-CoV-2 coronavirus has significantly affected public health, the worldwide economy, and social life. Metal organic frameworks (MOFs) are currently being implemented in biosensors for rapid and accurate detection of viruses thanks to their exceptional properties. This research aims to develop a Zeolitic Imidazolate Framework-8 (ZIF-8) based fluorescent biosensor for facile and rapid COVID-19 RNA sequence detection. ZIF-8 was characterized using several tests, such as FT-IR, TGA, and PXRD, to examine the MOF’s crystalline structure and thermal stability. The results demonstrated high crystallinity and thermal stability up to a temperature of 550 °C. The experimental study showed that ZIF-8 is an excellent fluorescence quencher, with 78.39% quenching efficiency. Analyzing the adsorption mechanism of probe DNA into ZIF-8 revealed that they can form electrostatic and π–π stacking interactions, forming a P-DNA@ZIF-8 complex and that PET is more dominant than FRET in the quenching mechanism. This ZIF-8 biosensing platform showed high sensitivity towards COVID-19 RNA with an ultra-low limit of detection of 6.24 pM, a rapid detection time of 8 min, and high selectivity to COVID-19 RNA. Indeed, ZIF-8 experienced much lower fluorescence recovery when tested on two mismatched RNAs. The experimental results show the potential use of ZIF-8 as a novel biosensor for a rapid and sensitive COVID-19 diagnosis.

STI Rates Among High-Risk Youth Undeterred During Early COVID-19 In A HIV Care Clinic

Abstract Background In recent years, the United States has observed increasing rates of sexually transmitted infections (STIs). Rates are highest amongst the teen and young adult age groups. In addition to the immense healthcare costs associated with STIs, long-term sequelae can be severe on the individual level. The risk of infertility is particularly high for those with repeated or prolonged infection. Upon entering the COVID-19 pandemic, it was unclear if the widespread behavioral changes and disruptions in routine care practices to minimize the further spread of COVID-19 would cause an increase or decrease in the United States’ STI rates. This study sought to determine if there was a change in the incidence of STIs during the first year of the COVID-19 pandemic compared to the year prior in a population at high risk for STIs. Methods A retrospective chart review was performed for 330 patients aged 12 to 41 years (mean 20.2 years, median 20 years, standard deviation 3.75 years) with human immunodeficiency virus (HIV) or on pre-exposure prophylaxis (PrEP) to prevent the acquisition of HIV, who presented for preventative and acute care appointments at a multidisciplinary pediatric and young adult HIV Clinic in the year prior to and during the first year of the COVID-19 pandemic (March 22, 2019-March 21, 2021). Utilizing telehealth, rapid COVID-19 screening, and multimodal patient communication, increased efforts were made in this clinic during the pandemic to maintain appropriate STI screening, testing, treatment, and rescheduling of routine visits when appropriate to minimize COVID-19 exposure and spread. Comparisons were made between the two time periods, which evaluated the incidences of individual and overall STIs diagnosed per person-years, STIs per total tests performed, and time to treatment initiation. Results Between one year prior to and the first year during the COVID-19 pandemic, this clinic experienced no statistically significant rate changes of sexually transmitted infections. A non-significant decreased incidence of chlamydia (22 cases per 100 person-years and 18 cases per 100 person-years, respectively) and unchanged rates of gonorrhea (22 cases per 100 person-years and 22 cases per 100 person-years, respectively) and syphilis (16 cases per 100 person-years and 15 cases per 100 person-years, respectively) were observed. The median times to treatment remained largely unchanged. Conclusion This HIV care clinic experienced a decreased chlamydia infection rate, a trend similar to the CDC United States STI data during this time period. In contrast to the nationally reported increased rates of gonorrhea and syphilis, this clinic experienced unchanged rates. The lack of change in our cohort could reflect that the benefits of a multidisciplinary HIV care model persist despite a pandemic that disrupted routine medical care and behavior practices.

Lessons from Covid-19 and the potential benefit of the implementation of Axon’s personal electronic health records (PEHR) into aesthetic care, plastic and reconstructive surgery

BackgroundCovid-19 pandemic highlighted the need for implementing Personal Electronic Health Records (PEHR) for patients’ data management. Furthermore, this pandemic underscored the relevance for integrated and interoperable Electronic Health Records (EHR) to support disease surveillance, hospital capacity planning and resource management (Peek N, Sujan M, Scott P (2020) Digital health and care in pandemic times: impact of COVID-19. BMJ Health Care Inf 27(1):e100166. https://doi.org/10.1136/bmjhci-2020-100166). Due to the lack of comprehensive patients’ record in plastic, reconstructive and aesthetic surgery, Axon’s myHealth app offers a break-through patient-centric design allowing patients to be in control of their records and updating them in real-time for their plastic and aesthetic care providers to have a clearer understanding of patients’ history and progress from pre-op to post-op.MethodsThe Axon Dublin survey took place during Covid-19 pandemic in two phases: Phase 1 aimed to assess the feasibility of patients integrating the Axon myHealth application into their clinical visits. Testing occurred in a clinical environment, where patients were encouraged to download and use the Axon system with a health practitioner (HP) present. Phase 2 focused on home testing, evaluating patients’ willingness to manage their health remotely with HP assistance. This phase included self-testing activities such as performing rapid Covid-19 antigen tests, recording medical history, and measuring blood pressure at home.ResultsThe Axon Dublin Study aimed to assess patient engagement, clinical impact, and cost-effectiveness of the Axon myHealth application. Over 85% of patients showed interest in owning a Personal Electronic Health Record. Notably, 36% continuously monitored chronic conditions. Clinical decisions, informed by patient data, saw 61.9% compliance. Noteworthy, 23% of hypertensive participants required immediate medication changes. Patient self-capture of data reduced consultation time. Public health implications were significant, with 39% vaccinated and 31% reporting complications. High user satisfaction (97%) demonstrated the app’s effectiveness in infection control and chronic care.ConclusionsOffering patients the ability to update and control their data is a growing interest, with a clear need in plastic and aesthetic surgery to have a better understanding of a patient’s medical past and progress throughout the surgical process and period. This platform, which is time and cost efficient, can only facilitate personalised care and improve outcomes while maintaining patient’s confidentiality.Level of evidenceNot gradable.

Pandemic-induced Migration From Campus to Digital Mode: Experiences From Social Work Students and Teachers in India and Sweden

The article explores the rapid COVID-19 pandemic-induced migration from campus to digital modes of education in 2020–2021. The process of this migration offers an opportunity to examine some important issues related to digital teaching, learning, and education during the pandemic. Based on our study of the School of Social Work at Tata Institute of Social Sciences in Mumbai, India, and the School of Social Work at Lund University, Sweden, we explore and compare the social component in the experiences of students and teachers at the two institutions. The data collection draws on focus group sessions and interviews complemented by various relevant institutional documents and our own experiences at our respective institutions. The core argument we put forth in the article is that the Swedish student and teacher response to the pandemic-induced crisis and the migration to digital classes was a case of ‘trusting the state’, as they were passively waiting for top-down initiatives and instructions. On the other hand, the response at the Indian institution was a case of ‘trusting ourselves’, not waiting for top-down instructions and support but creating bottom-up solutions within the internal community of teachers and students. We also highlight the different perceptions and the impact of teaching and studying from home on physical and emotional levels. While we present the differences and specificity around the expectations of teachers and students at the two institutions, we also elucidate their patience, perseverance and innovation while engaging with the realities of work and studying from home while being kept away from campus.

The Relationship between Family Support and Patient Anxiety when Undergoing Rapid Screening Tests COVID-19 in Hospitals

The Relationship between Family Support and Patient Anxiety when Undergoing Rapid Screening Tests COVID-19 in Hospitals

Implementation of Rapid COVID-19 Testing in Criminal Justice Residential Reentry Sites.

The goal was to study the implementation of rapid BINAX COVID-19 testing at criminal justice reentry sites, focusing on framework-guided implementation outcomes. We implemented rapid COVID-19 testing at nine reentry sites in four states (Massachusetts, New Hampshire, Rhode Island, and New York) and collected test results to measure the (1) adoptability and (2) implementability of COVID-19 testing at reentry sites. We collected data on the acceptability, appropriateness, and feasibility of the implementation of COVID-19 testing using an anonymous employee Qualtrics survey. Testing was available to symptomatic and exposed residents and employees. COVID-19 testing results were collected from October 2021 to March 2022. Guided by the Expert Recommendations in Implementing Change (ERIC) framework, we chose nine implementation strategies to address barriers during the implementation process. Acceptability, appropriateness, and feasibility outcomes were captured from employees using validated measures. A total of 302 BINAX COVID-19 tests were used and 26 positive cases were identified. Forty-seven percent of employees participated in the survey. More than half of respondents either agreed or completely agreed with statements about the acceptability, appropriateness, or feasibility of COVID-19 testing. Funding and attention toward COVID-19 testing at reentry sites should be provided to help prevent the spread of COVID-19 in these sites.

Early and Rapid COVID-19 Diagnosis Using a Symptom-Based Machine Learning Model

The COVID-19 pandemic has resulted in a significant global health crisis, claiming over 6.3 million lives. Rapid and accurate detection of COVID-19 symptoms is essential for effective public health responses. This study utilizes machine learning algorithms to enhance the speed and accuracy of COVID-19 diagnosis based on symptom data. By employing the Spearman feature selection algorithm, we identified the most predictive features, thereby improving model performance and reducing the number of features required. The decision tree algorithm proved to be the most effective, achieving an accuracy of 98.57%, perfect sensitivity of 1, and high specificity of 0.97. Our results indicate that combining various symptoms with AI-based machine learning techniques can accurately detect COVID-19 patients. These findings surpass previous studies, demonstrating superior performance across multiple evaluations. The integration of feature selection with advanced machine learning models offers a practical and efficient tool for early COVID-19 diagnosis, improving patient management and public health responses. This approach holds significant promise for enhancing pandemic management and healthcare delivery.

Teaching Visual Arts Using Virtual Exhibitions: An Investigation of Student Usage and Impact on Learning

Amid the imperative call for using digital artwork images and e-learning activities in planning and delivering the art curriculum heightened by rapid technological development and COVID-19, we propose a visual arts teacher–curator pedagogy and investigate its effectiveness in Hong Kong’s primary and secondary schools. The pedagogy is set out to empower visual arts teachers to assume the role of “digital museum curators” and to facilitate student learning using virtual exhibitions. Design-based research was the methodology adopted for the study. Six teachers and 331 students participated in the study in the 2021–2022 academic year. The study, which examined the effectiveness of the proposed pedagogy, revealed a substantial improvement in student learning, including (1) motivating students toward self-directed and active learning, (2) stimulating artmaking ideas and skills, and (3) enhancing students’ confidence through peer learning.

Impact of the Rapid COVID-19 Polymerase Chain Reaction Test on Length of Emergency Room Stay

Impact of the Rapid COVID-19 Polymerase Chain Reaction Test on Length of Emergency Room Stay

Persistent hiccups after acute COVID-19 successfully treated with chlorpromazine: a case report

IntroductionHiccups are among the rare complications of COVID-19 infections. There are several published reports of persistent hiccups presenting during the acute COVID-19 period. However, there are very few published reports of persistent hiccups occurring in the post-acute COVID-19 period. Consequently, most clinicians may not be aware of this rare presentation. This case highlights an atypical presentation of persistent hiccups that manifested during the post-acute COVID -19 period that clinicians need to be aware of. The caseadds to the ever increasing body of knowledge about symptoms and signs associated with Severe Acute Respiratory Syndrome Corona Virus type 2 (SARS CoV-2) infection.Case presentationA 27 year old male black Zambian patient presented to the emergency department of our hospital with persistent hiccup, 35 days after the initial acute episode of COVID-19. This was associated with breathlessness. There were no other symptoms. He had no history of pulmonary, gastrointestinal, neurological disease or malignancy. He did not take any alcohol or smoke. He had never used any recreational drugs. He was employed as a monitoring and evaluation officer at one of the main COVID centres in the capital. On examination, the patient was anxious. Blood pressure was 141/82, pulse rate was 95 beats per minute, respiratory rate was 26 breaths per minute, temperature was 36.8C and oxygen saturation was 97% on room air. Systemic examination was normal. Chest X-ray and abdominal ultrasonography were normal. A rapid COVID-19 antigen test, and COVID-19 Polymerase Chain Reaction (PCR) test that were done the following day were negative. All other haematological and biochemical tests, including D-dimer and C-reactive protein (CRP), were also normal. A diagnosis of post-acute COVID-19 associated hiccups was made. The patient responded well to treatment with chlorpromazine 25 mg 8 hourly. The hiccups disappeared completely after the fourth dose of chlorpromazine.ConclusionThis is one of the few published cases of COVID-19 associated persistent hiccups, occurring more than a month after the initial presentation. Most of the published cases report hiccups occurring in the acute COVID-19 period. Consequently, hiccups occurring in the post-acute COVID-19 period may not be attributable to COVID-19. This case has highlighted the need to consider post-acute COVID-19 in the differential diagnosis of persistent hiccup.

Covid-19 Disease Detector Using X-Rays Based On Deep Learning

This study presents an automated deep learning approach for the rapid detection of COVID-19 using chest X-ray images. Given the urgent need for efficient disease diagnostics, we utilize convolutional neural networks (CNNs) to develop a ResNet-based classification model. Our dataset includes ten images, five depicting COVID-19 cases and five standard X-ray images, chosen for their rapidity and low radiation dose. The model demonstrates high accuracy, successfully classifying all images. Transfer learning techniques further enhance performance, indicating the potential for broader application and improved diagnostic capabilities. This research addresses the current knowledge gap in automated COVID-19 diagnostics, offering a reliable method for swift and accurate detection, with implications for enhancing disease management strategies. Highlights: Rapid COVID-19 detection using deep learning. High accuracy with convolutional neural networks. Quick results with low radiation in chest X-rays. Keywords: COVID-19, deep learning, chest X-ray, automated diagnosis, convolutional neural networks

Safeguarding the Environment: A Review of Functional Coating Systems for Rapid COVID-19 Inactivation

The COVID-19 pandemic was a worldwide disaster in the health industry, millions of human deaths were recorded. The spread of the virus led to the shutting down of the world economy. The most prevalent is people communicating in close contact. Measures such as the use of nose masks and social distancing help to reduce the infection rate. The second is infection from substrates like tables, automated teller machine buttons, staircase rails, door nubs, etc. This paper is poised to review how surface-infected (substrates) platforms can be inactivated using modified functional coating systems. These coating composite systems are prepared by functionalizing the polymer matrix with suitable nanoparticles that could inactivate the SARS-CoV-2 virus. Furthermore, this piece discusses the challenges and future directions in the development of advanced coating technologies, aiming to enhance their effectiveness and applicability in diverse settings, including healthcare facilities and public spaces. This review serves as a valuable resource for scientists, engineers, and policymakers involved in the ongoing efforts to combat the COVID-19 pandemic.

Dynamics of respiratory infectious diseases under rapid urbanization and COVID-19 pandemic in the subcenter of Beijing during 2014–2022

ObjectiveThe study analyzed the impact of urbanization on epidemiological characteristics of respiratory infectious disease in Tongzhou District, Beijing during 2014–2022 to provide reference for prevention and control priorities of respiratory infectious diseases during the innovative urbanization process in China. MethodsThe incidence data of notifiable respiratory infectious diseases (NRIDs) in Tongzhou Beijing during 2014–2022 were summarized. The trend of incidence rate was analyzed by Joinpoint regression model, and entropy method was performed to construct the comprehensive index of urbanization (CIU) and generalized linear model was used to analyze the influence of CIU on the incidence rate of respiratory infectious diseases. ResultsTotally 72616 NRIDs cases were reported in Tongzhou District during 2014–2022, and the incidence rate of NRIDs was higher during 2017–2019 (153/100 000) than during 2014–2016 (930/100 000) and during 2020–2022 (371/100 000), respectively (both P < 0.001). The CIU constantly increased with slight fluctuation in 2016 and 2018, respectively. The incidence rate of NRIDs showed an increase along with the CIU during 2014–2019 (r = 0.95, P = 0.004), while the incidence rate's tendency was interrupted by COVID-19 during 2020 with slight decrease in 2020–2021 and rebounded in 2022. For the patients aged <15 years, the incidence rate of NRIDs revealed a very sharp rise at the urbanization period without COVID-19 pandemic compared with that under pre-urbanization period (RR = 7.93, 95 % CI 7.63−8.24), and dropped off to the similar level as of pre-urbanization period when COVID-19 pandemic spread. ConclusionsUrbanization process may increase the incidence of NRIDs but constrained by COVID-19. Certain measures should be taken to prevent and control the effects by urbanization process, such as good natural environment with less population density, ecological environment with good air quality, promoted hand hygiene, mask wearing, keeping interpersonal distance, vaccination, media publicity for NRIDs’ prevention and control.

Automated Classification of COVID-19 Chest X-ray Images Using Ensemble Machine Learning Methods

This study delves into the efficacy of ensemble machine learning techniques for classifying chest X-ray images into three distinct categories: Normal, COVID-19, and Lung Opacity. Employing the Random Forest Classifier and a rigorous k-5 cross-validation framework, we aimed to enhance diagnostic accuracy for one of the most urgent medical challenges today—rapid and reliable COVID-19 detection. The analysis revealed an average accuracy of 51%, with varying precision and recall across different folds. The F1-score remained consistently around 35%, indicating a need for improved balance between precision and recall. Visualizations such as performance metric trends and a confusion matrix provided further insight into the classifier's performance, highlighting a notable degree of misclassification. Despite moderate success in the automated classification of the images, our research illustrates the complexity of applying machine learning to medical imaging, especially in differentiating between diseases with overlapping radiographic features. The study’s findings emphasize the potential of machine learning models to support diagnostic processes and suggest the necessity of advanced pre-processing techniques and extended datasets for enhanced model training. The research contributes to the growing body of knowledge in computational diagnostics and underscores the importance of developing robust, accurate machine learning tools to aid in the global healthcare crisis precipitated by the pandemic.

The relevance of the country and sector effect in global equity returns around COVID-19 and developed and emerging markets

This study explores the historical and current explanatory power of country classification and Global Industry Classification Standard sector classification on global equity returns in the equally weighted MSCI All Country World Index. R2 is a crucial statistical tool for risk and portfolio management professionals because it serves as a measure of how much of a portfolio's movements can be explained by factors. Its significance lies in its ability to quantify how dependent a portfolio's risk is on those factors. The country classification's adjusted R2 is dominant in global equities, driven by its dominance within emerging markets (EM). Within developed markets (DM), the country effect's slight dominance over the sector effect has decreased over time — the two have become more balanced since 2015, with the sector effect having a slightly higher adjusted R2 value. There was a drop in the R2 for all classifications during the COVID-19 pandemic. This drop was most significant in the country classification, with a sharp decline to 8.3 per cent, well below its previous historical minimum of 12 per cent, before it rebounded to its historical range. This change drove further analysis into the country effect across EM and DM, where the large drop and rebound were primarily within EM. During this time, the sector effect dropped but remained within its historical range, implying a larger loss of diversification benefit in country effect than in sector effect. The impact of Chinese stocks on country effect within EM is also investigated. In 2018, there was a large influx of Chinese companies into the index, which caused a decline in country diversification and hence a reduction in explanatory power within EM. China's rapid and strict COVID-19 response, early tight monetary policy and regulatory crackdown have since caused it to become increasingly differentiated from the rest of EM, increasing country diversification within EM and causing the accentuated rebound in explanatory power of the country effect post-COVID-19. Risk managers can use these results to validate the use of sector and country classifications in portfolio construction.

Evaluation of CLINITEST® Rapid Covid-19 + Influenza antigen test in a cohort of symptomatic patients in an emergency department.

Rapid management of patients with respiratory tract infections in hospital emergency departments is one of the main objectives since the concurrent circulation of respiratory viruses following the SARS-CoV-2 pandemic. The use of new combined point-of-care antigen tests for detecting influenza A/B and SARS-CoV-2 represents an advantage in response time over the molecular tests. The objective was to evaluate the suitability of the CLINITEST® Rapid Covid-19 + Influenza Antigen test (Siemens Healthineers, Germany) (RCIA test) by measuring the sensitivity, specificity, Cohen's kappa, and cut-off values. Nasopharyngeal samples were collected from a randomised group of symptomatic patients of all ages at emergency department during January-February 2023. In parallel, these patients were screened for influenza A/B, and SARS-CoV-2 using RT-PCR. The Ct (cycle threshold) values were collected for positive [RT-PCR (+) /RCIA test (+)] and false negative [(RT-PCR (+) /RCIA test (-)] samples. A subanalysis was performed in the paediatric population (< 16 years-old). We included 545 patients (55.8% females) with a median age of 7 years-old (IQR: 1-66.5). The RCIA test showed a sensitivity of 59.7% [95%CI: 46.9-67.33] for influenza A, 65.6% [95%CI: 49.5-80.3] for influenza B, and 76.9% [95%CI: 45.8-84.8] for SARS-CoV-2. The specificity was between 90.7%-99.7% with a moderate/high level of agreement with RT-PCR (kappa score: 0.6-0.8) for the three respiratory viruses included in the RCIA test. The sensitivity of the RCIA test is insufficient for screening of patients, including patients with low Ct values (Ct > 20). Despite its good specificity and Cohen's kappa value, its use as a screening test is not comparable to RT-PCR systems in the ED environment with a high number of false negative results.