COVID-19 Diagnostics Research Articles

Innovative COVID-19 Point-of-Care Diagnostics Suitable for Tuberculosis Diagnosis: A Scoping Review.

Rapid and accurate point-of-care (POC) tuberculosis (TB) diagnostics are crucial to bridge the TB diagnostic gap. Leveraging recent advancements in COVID-19 diagnostics, we explored adapting commercially available POC SARS-CoV-2 tests for TB diagnosis in line with the World Health Organization (WHO) target product profiles (TPPs). A scoping review was conducted following PRISMA-ScR guidelines to systematically map POC antigen and molecular SARS-CoV-2 diagnostic tests potentially meeting the TPPs for TB diagnostic tests for peripheral settings. Data were gathered from PubMed/MEDLINE, bioRxiv, medRxiv, publicly accessible in vitro diagnostic test databases, and developer websites up to 23 November 2022. Data on developer attributes, operational characteristics, pricing, clinical performance, and regulatory status were charted using standardized data extraction forms and evaluated with a standardized scorecard. A narrative synthesis of the data is presented. Our search yielded 2003 reports, with 408 meeting eligibility criteria. Among these, we identified 66 commercialized devices: 22 near-POC antigen tests, 1 POC molecular test, 31 near-POC molecular tests, and 12 low-complexity molecular tests potentially adaptable for TB. The highest-scoring SARS-CoV-2 diagnostic tests were the near-POC antigen platform LumiraDx (Roche, Basel, Switzerland), the POC molecular test Lucira Check-It (Pfizer, New York, NY, USA), the near-POC molecular test Visby (Visby, San Jose, CA, USA), and the low-complexity molecular platform Idylla (Biocartis, Lausanne, Switzerland). We highlight a diverse landscape of commercially available diagnostic tests suitable for potential adaptation to peripheral TB testing. This work aims to bolster global TB initiatives by fostering stakeholder collaboration, leveraging SARS-CoV-2 diagnostic technologies for TB, and uncovering new commercial avenues to tackle longstanding challenges in TB diagnosis.

Unraveling COVID-19 Diagnostics: A Roadmap for Future Pandemic

Unraveling COVID-19 Diagnostics: A Roadmap for Future Pandemic

Numerical analysis of an advanced infrared-based metasurface surface plasmon resonance sensor for COVID-19 detection

The SARS-CoV-2 pandemic has highlighted the critical need for rapid and precise diagnostic methodologies. Conventional testing approaches often exhibit limitations in terms of speed, accessibility, and sensitivity. To address these constraints, we propose an advanced graphene-based biosensing platform for SARS-CoV-2 detection. This sensor integrates advanced nanophotonic principles, metamaterial physics, and two-dimensional material properties to achieve enhanced sensitivity through the detection of refractive index perturbations induced by SARS-CoV-2 biomolecules. Electromagnetic simulations were conducted to optimize the sensor design. The resulting configuration demonstrates a sensitivity of 1800 nmRIU−1 and a detection limit of 0.007 RIU. The sensor exhibits multi-wavelength sensing capabilities at 3.942 μm, 4.018 μm, 4.088 μm, and 4.201 μm, with a high figure of merit of 104.167 RIU−1 and quality factors ranging from 65.766 to 251. 750.The sensor's multilayer architecture, comprising tungsten, graphene, and strontium titanate synergistically enhances both sensitivity and selectivity. Its compact form factor and capacity for real-time analysis render it a promising candidate for point-of-care COVID-19 diagnostics.

Unveiling the Quest: Crafting an Enzyme-Linked Immunosorbent Assay (ELISA) Technique to Uncover COVID-19 Antibodies.

The COVID-19 pandemic, caused by the novel coronavirus SARS-CoV-2, has had a profound impact on global health. Rapid and accurate diagnostic tools are crucial for effective disease control and management. The enzyme-linked immunosorbent assay (ELISA) has emerged as a reliable and widely used method for detecting COVID-19 antibodies in patients, which develop in response to SARS-CoV-2 infection. While the ELISA technique is effective in identifying the presence of antibodies and thus confirming exposure to the virus, its role in predicting the clinical course and severity of the disease is limited. ELISA primarily confirms prior exposure to the virus or vaccination status, but it does not directly correlate antibody levels with the severity or progression of the disease. The variability in clinical outcomes is influenced by factors such as viral load, patient co-morbidities, genetic predispositions, and the timing of the immune response. ELISA has diverse applications in epidemiology, vaccination assessment, and therapeutic development. It determines antibody prevalence, aids in surveillance, and evaluates vaccine effectiveness and antibody protection duration. ELISA quantitatively measures antibody levels, providing insights into the immune response and treatment efficacy. Challenges include specialized facilities and personnel, cross-reactivity, and false results. Multiplex assays and integration with other diagnostics are future directions. In summary, ELISA is an essential tool in COVID-19 diagnostics, enabling precise assessment of the immune response and contributing to effective strategies. The development of point-of-care devices that integrate ELISA technology could enable rapid and accessible testing in various settings. Additionally, integrating ELISA with other diagnostic platforms could enhance the overall diagnostic capabilities for COVID-19. Despite challenges, ongoing advancements in ELISA technology, and its integration with other diagnostic approaches, hold promise for further improving COVID-19 diagnostics and management strategies.

Surface Plasmon Resonance Immunosensor for Direct Detection of Antibodies against SARS-CoV-2 Nucleocapsid Protein.

The strong immunogenicity of the SARS-CoV-2 nucleocapsid protein is widely recognized, and the detection of specific antibodies is critical for COVID-19 diagnostics in patients. This research proposed direct, label-free, and sensitive detection of antibodies against the SARS-CoV-2 nucleocapsid protein (anti-SCoV2-rN). Recombinant SARS-CoV-2 nucleocapsid protein (SCoV2-rN) was immobilized by carbodiimide chemistry on an SPR sensor chip coated with a self-assembled monolayer of 11-mercaptoundecanoic acid. When immobilized under optimal conditions, a SCoV2-rN surface mass concentration of 3.61 ± 0.52 ng/mm2 was achieved, maximizing the effectiveness of the immunosensor for the anti-SCoV2-rN determination. The calculated KD value of 6.49 × 10-8 ± 5.3 × 10-9 M confirmed the good affinity of the used monoclonal anti-SCoV2-rN antibodies. The linear range of the developed immunosensor was from 0.5 to 50 nM of anti-SCoV2-rN, where the limit of detection and the limit of quantification values were 0.057 and 0.19 nM, respectively. The immunosensor exhibited good reproducibility and specificity. In addition, the developed immunosensor is suitable for multiple anti-SCoV2-rN antibody detections.

Magnetic N-doped carbon derived from mixed ligands MOF as effective electrochemiluminescence coreactor for performance enhancement of SARS-CoV-2 immunosensor

COVID-19 as an infectious disease with rapid transmission speed is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), so, early and accurate diagnostics of COVID-19 is quite challenging. In this work, the selective and sensitive self-enhanced ECL method to detect of SARS-CoV-2 protein was designed with magnetic N-doped carbon derived from dual-ligand metal-organic frameworks (MOF) (CoO@N–C) with the primary and tertiary amino groups as a novel coreactant that covalently combined with Ru(bpy)2(phen-NH2)2+ as electrochemiluminescence (ECL) emitter. Mixed-ligand strategy and selected nitrogen-containing ligands, 4,4′,4′′-((1,3,5-triazine-2,4,6-triyl) tris-(azanediyl)) tribenzoic acid (H3TATAB) with 2-aminoterephthalic acid (BDC-NH2) were used for synthesis of the proposed MOF. Also, magnetic CoO@N–C with high synergistically charge transfer kinetics and good stability can be used as an effective platform/coreactor on the ITO electrode which load more Ru-complex as signal producing compound and SARS-CoV-2 N protein antibody to increase the sensitivity of the immunosensor. Furthermore, (CoO@N–C) as coreactor improved the ECL signal of the Ru (II)-complex more than 2.1 folds compared to tripropylamine. In view of these competences, the novel “on-off” ECL biosensor performed with great stability and repeatability for detection of SARS-CoV-2 protein, which exhibited a broad linearity from 8 fg. mL−1 to 4 ng. mL−1 (6 order of magnitude) and an ultra-low limit of detection 1.6 fg. mL−1. Finally, this proposed method was successfully applied to detect of SARS-CoV-2 N protein in serum sample with satisfactory results, indicating the proposed immunosensor has the potential for quick analysis of SARS-CoV-2.

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

Impact of the COVID-19 pandemic on the real-world diagnostic infrastructure for tuberculosis-An ESGMYC collaborative study.

We determined the impact of the COVID-19 pandemic on mycobacterial diagnostic services. 40 laboratories from 22 countries completed an online questionnaire covering the redeployment of the laboratory infrastructure and/or staff for SARS-CoV-2 testing, staff shortages and supply chain disruptions. 28 laboratories reported monthly numbers of samples processed for mycobacterial investigations and monthly numbers of M. tuberculosis complex (MTBC) PCRs performed between October 1st 2018 and October 31st 2020. More than half (23/40) of the participating TB laboratories reported having performed COVID-19 diagnostics in the early phase of the pandemic, in part with negative impact on the mycobacterial service activities. All participating laboratories reported shortages of consumables and laboratory equipment due to supply chain issues. Average monthly sample numbers decreased by 24% between January 2020 and October 2020 compared to pre-pandemic averages. At the end of the study period, most participating laboratories had not returned to pre-pandemic average MTBC PCR throughput.

Sensitivity studies and optimization of an impedance-based biosensor for point-of-care applications

In this study, we examined the relationship between the sensitivity of interdigitated electrode (IDE) impedimetric biosensors and the gap between the IDEs. Our aim is to find an optimal design to maximize sensitivity. A three-dimensional COMSOL model was constructed for determining the effects of electrode gap, width, and height on impedance sensitivity, revealing a singular linear correlation with the inner gap. Considering both the simulation results and fabrication processes, we have developed three IDE prototype chips with electrode gaps of 3 μm, 4 μm, and 5 μm, respectively. For empirical validation, human anti-SARS-CoV-2 monoclonal antibody (mAb) was utilized, with immobilization of the SARS-CoV-2 spike protein on the chip's surface for mAb capture. This interaction, further amplified by Protein G conjugation, induced shifts in the impedance spectrum. The sensitivity of each prototype chip was evaluated across mAb concentrations ranging from 50 ng/mL to 500 ng/mL. The 3 μm configuration emerged as the most sensitive, demonstrating the ability to detect mAb concentrations as low as 50 ng/mL, a threshold unattainable by the other designs. This outcome underscores the critical influence of reduced inter-electrode gap on enhancing biosensor detection limits. The findings from this investigation offer a foundational approach for advancing biosensor sensitivity via electrode geometric optimization, with broad potential applications extending beyond COVID-19 diagnostics to a wide spectrum of clinical and research contexts.

Pooling of samples to optimise SARS-CoV-2 detection in nasopharyngeal swabs and gargle lavage self-samples for covid-19 diagnostics and surveillance

Background Testing of pooled samples is an effective strategy for increasing testing capacity while saving resources and time. This study aimed to validate pooled testing and gather real-life data on its use for Covid-19 surveillance with a gargle lavage (GL) self-sampling strategy. Methods Two-stage pooled testing with pools of 6 and 12 samples was used for preventive testing of an asymptomatic population and Covid-19 surveillance in Czech schools. Both GL and nasopharyngeal swabs were used for sampling. Results In total, 61,111 samples were tested. The use of pooled testing for large-scale Covid-19 surveillance reduced consumable costs by almost 75% and increased testing capacity up to 3.8-fold compared to standard methods. RT-PCR experiments revealed a minimal loss of sensitivity (0–2.2%) when using pooled samples, enabling the detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genes with Ct values >35. The minor loss of sensitivity was counterbalanced by a significantly increased throughput and the ability to substantially increase testing frequencies. Conclusions Pooled testing is considerably more cost-effective and less time-consuming than standard testing for large-scale Covid-19 surveillance even when the prevalence of SARS-CoV-2 is fluctuating. Gargle lavage self-sampling is a non-invasive technique suitable for sample collection without a healthcare worker’s assistance.

COVID-19 prophylaxis, diagnostics, and treatment in patients with rheumatic diseases. The Polish experts panel opinion.

As severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) evolves, infection management in vulnerable populations requires formalized guidance. Although low-virulence variants of SARS-CoV-2 remain predominant, they pose an increased risk of severe illness in adults with rheumatic and musculoskeletal diseases (RMDs). Several disease-specific (chronic long-grade inflammation, concomitant immunosuppression) and individual (advanced age, multimorbidity, pregnancy, vaccination status) factors contribute to excess risk in RMD populations. Various post-COVID-19 manifestations are also increasingly reported and appear more commonly than in the general population. At a pathogenetic level, complex interplay involving innate and acquired immune dysregulation, viral persistence, and genetic predisposition shapes a unique susceptibility profile. Moreover, incident cases of SARS-CoV-2 infection as a trigger factor for the development of autoimmune conditions have been reported. Vaccination remains a key preventive strategy, and encouraging active education and awareness will be crucial for rheumatologists in the upcoming years. In patients with RMDs, COVID-19 vaccines' benefits outweigh the risks. Derivation of specialized diagnostic and therapeutic protocols within a comprehensive COVID-19 care plan represents an ideal scenario for healthcare system organization. Vigilance for symptoms of infection and rapid diagnosis are key for introducing antiviral treatment in patients with RMDs in a timely manner. This review provides updated guidance on optimal immunization, diagnosis, and antiviral treatment strategies.

How to Develop a Qualitative Evaluation Plan for a Complex National Intervention: Key Steps and Reflections from the RADx-UP Program

This article describes the formative process of developing and implementing a Qualitative Evaluation Plan (QEP) for a large-scale, National Institute of Health (NIH) supported program: Rapid Acceleration of Diagnostics — Underserved Populations (RADx-UP). RADx-UP includes over 137 projects in the United States that aim to ensure that all Americans have access to timely, accurate diagnostics for COVID-19, with a specific focus on populations the pandemic disproportionately affects. As part of a comprehensive, mixed-methods strategic evaluation plan, our team developed the QEP. We employed qualitative methods to understand RADx-UP academic and community partners’ experiences implementing community-engaged research strategies, and to understand how projects addressed COVID-19 outreach, testing, and response efforts in-depth. This paper describes how our evaluation team developed the QEP in three phases. Within these phases, we describe our processes related to planning the QEP, sampling from a diverse frame of projects, creating interview guides, collecting interview data, analyzing data, and disseminating findings. We provide our key takeaways and lessons learned from creating a QEP for a large-scale research initiative that other researchers may consider when creating similar evaluation plans.

Advances and Challenges in SARS-CoV-2 Detection: A Review of Molecular and Serological Technologies.

The urgent need for accurate COVID-19 diagnostics has led to the development of various SARS-CoV-2 detection technologies. Real-time reverse transcriptase polymerase chain reaction (RT-qPCR) remains a reliable viral gene detection technique, while other molecular methods, including nucleic acid amplification techniques (NAATs) and isothermal amplification techniques, provide diverse and effective approaches. Serological assays, detecting antibodies in response to viral infection, are crucial for disease surveillance. Saliva-based immunoassays show promise for surveillance purposes. The efficiency of SARS-CoV-2 antibody detection varies, with IgM indicating recent exposure and IgG offering prolonged detectability. Various rapid tests, including lateral-flow immunoassays, present opportunities for quick diagnosis, but their clinical significance requires validation through further studies. Challenges include variations in specificity and sensitivity among testing platforms and evolving assay sensitivities over time. SARS-CoV-2 antigens, particularly the N and S proteins, play a crucial role in diagnostic methods. Innovative approaches, such as nanozyme-based assays and specific nucleotide aptamers, offer enhanced sensitivity and flexibility. In conclusion, ongoing advancements in SARS-CoV-2 detection methods contribute to the global effort in combating the COVID-19 pandemic.

Re-testing as a method of implementing external quality assessment program for COVID-19 real time PCR testing in Uganda.

Significant milestones have been made in the development of COVID19 diagnostics Technologies. Government of the republic of Uganda and the line Ministry of Health mandated Uganda Virus Research Institute to ensure quality of COVID19 diagnostics. Re-testing was one of the methods initiated by the UVRI to implement External Quality assessment of COVID19 molecular diagnostics. participating laboratories were required by UVRI to submit their already tested and archived nasopharyngeal samples and corresponding meta data. These were then re-tested at UVRI using the WHO Berlin protocol, the UVRI results were compared to those of the primary testing laboratories in order to ascertain performance agreement for the qualitative & quantitative results obtained. Ms Excel window 12 and GraphPad prism ver 15 was used in the analysis. Bar graphs, pie charts and line graphs were used to compare performance agreement between the reference Laboratory and primary testing Laboratories. Eleven (11) Ministry of Health/Uganda Virus Research Institute COVID19 accredited laboratories participated in the re-testing of quality control samples. 5/11 (45%) of the primary testing laboratories had 100% performance agreement with that of the National Reference Laboratory for the final test result. Even where there was concordance in the final test outcome (negative or positive) between UVRI and primary testing laboratories, there were still differences in CT values. The differences in the Cycle Threshold (CT) values were insignificant except for Tenna & Pharma Laboratory and the UVRI(p = 0.0296). The difference in the CT values were not skewed to either the National reference Laboratory(UVRI) or the primary testing laboratory but varied from one laboratory to another. In the remaining 6/11 (55%) laboratories where there were discrepancies in the aggregate test results, only samples initially tested and reported as positive by the primary laboratories were tested and found to be false positives by the UVRI COVID19 National Reference Laboratory. False positives were detected from public, private not for profit and private testing laboratories in almost equal proportion. There is need for standardization of molecular testing platforms in Uganda. There is also urgent need to improve on the Laboratory quality management systems of the molecular testing laboratories in order to minimize such discrepancies.

Genetic Analysis and Epidemiological Impact of SARS-CoV-2: A Multinational Study of 1000 Samples Using RT-PCR

The ongoing global public health challenge posed by the COVID-19 pandemic necessitates continuous research and surveillance efforts. In this study, we comprehensively analyzed over 1000 COVID-19 RT-PCR tests conducted on a cohort of 1200 patients in Saudi Arabia. Our primary goal was to investigate mutations in specific genes RdRp, N, and E different infection and recovery stages in Saudi patients with SARS-CoV-2. We also extended our analysis to include patients of various nationalities residing in Saudi Arabia, with the overarching objective of assessing these genes as markers for COVID-19 presence and progression. To diagnose and investigate potential genetic variations in COVID-19, we engaged RT-PCR. Our study primarily focused on detecting mutations in the RdRp, N, and E genes in Saudi patients with SARS-CoV-2, as well as individuals from various national residing in Saudi Arabia. This molecular technique provided valuable insights into the virus’s genetic makeup during infection and recovery. In our analysis of 671 positive COVID-19 cases, diverse gene involvement patterns were observed. Specifically, 55.91% had mutations in all three genes (RdRp, N, and E), 62.33% in both N and E genes, and 67.16% in RdRp and N genes. Additionally, 30.75% exhibited mutations exclusively in the RdRp gene, and 51.58% had mutations in the N gene. The N gene, in particular, showed high sensitivity as a marker for identifying active viral circulation. Regarding the temporal dynamics of the disease, the median duration between a positive and a subsequent negative COVID-19 RT-PCR test result was approximately 33.86 days for 44% of cases, 14.31 days for 30%, and 22.67 days for 4%. The insights from this study hold significant implications for managing COVID-19 patients during the ongoing pandemic. The N gene shows promise as a marker for detecting active viral circulation, potentially improving patient care and containment strategies. Establishing a defined positive threshold for diagnostic methods and correlating it with a low risk of infection remains a challenge. Further research is needed to address these complexities and enhance our understanding of COVID-19 epidemiology and diagnostics.

Engineered two-dimensional nanomaterials based diagnostics integrated with internet of medical things (IoMT) for COVID-19.

More than four years have passed since an inimitable coronavirus disease (COVID-19) pandemic hit the globe in 2019 after an uncontrolled transmission of the severe acute respiratory syndrome (SARS-CoV-2) infection. The occurrence of this highly contagious respiratory infectious disease led to chaos and mortality all over the world. The peak paradigm shift of the researchers was inclined towards the accurate and rapid detection of diseases. Since 2019, there has been a boost in the diagnostics of COVID-19 via numerous conventional diagnostic tools like RT-PCR, ELISA, etc., and advanced biosensing kits like LFIA, etc. For the same reason, the use of nanotechnology and two-dimensional nanomaterials (2DNMs) has aided in the fabrication of efficient diagnostic tools to combat COVID-19. This article discusses the engineering techniques utilized for fabricating chemically active E2DNMs that are exceptionally thin and irregular. The techniques encompass the introduction of heteroatoms, intercalation of ions, and the design of strain and defects. E2DNMs possess unique characteristics, including a substantial surface area and controllable electrical, optical, and bioactive properties. These characteristics enable the development of sophisticated diagnostic platforms for real-time biosensors with exceptional sensitivity in detecting SARS-CoV-2. Integrating the Internet of Medical Things (IoMT) with these E2DNMs-based advanced diagnostics has led to the development of portable, real-time, scalable, more accurate, and cost-effective SARS-CoV-2 diagnostic platforms. These diagnostic platforms have the potential to revolutionize SARS-CoV-2 diagnosis by making it faster, easier, and more accessible to people worldwide, thus making them ideal for resource-limited settings. These advanced IoMT diagnostic platforms may help with combating SARS-CoV-2 as well as tracking and predicting the spread of future pandemics, ultimately saving lives and mitigating their impact on global health systems.

The Power of the Regulator: Regulatory Guidance and the Firms that Didn't Follow It During the Emergence of U.S. COVID-19 Diagnostics

The Power of the Regulator: Regulatory Guidance and the Firms that Didn't Follow It During the Emergence of U.S. COVID-19 Diagnostics

TRIPS Waiver Decision for Equitable Access to Medical Countermeasures in the Pandemic: COVID-19 Diagnostics and Therapeutics

TRIPS Waiver Decision for Equitable Access to Medical Countermeasures in the Pandemic: COVID-19 Diagnostics and Therapeutics

COVID-19 associated anosmia in pediatric patients: subject publications review.

Aim: To review the publications subject to the problem of COVID-19 associated anosmia incidence in pediatric patients as well as its pathogenesis, diagnostics, treatment and recovery. The peculiarity of pediatric COVID-19 anosmia is due to children accounting for very low percentage of COVID-19 patients (comparing to one in adults), mostly with milder course of the disease. Awareness of anosmia and its proper diagnostics is crucial in children and adolescents, considering it can be the only manifestation in COVID-19 positive pediatric patients. Materials and Methods: In order to achieve this goal a meta-analysis of information from databases followed by statistical processing and generalisation of the obtained data was carried out. Conclusions: Publications on COVID-19 anosmia in children and adolescents are less numerous than those concerning adult patients, so it is important to use every single trustworthy one. Anosmia/ageusia may be the only symptom, early identifier and the strongest predictor of COVID-19 infection in pediatric patients. Prospects for further scientific researches. Further researches regarding differential diagnostics of COVID-19 and other infections, including seasonal influenza, manifesting with both olfactory and taste dysfunction as well as anosmia diagnostics in children and adolescents with autistic spectrum and different types of mental disorders are possible.

Accurate COVID-19 detection using full blood count data and machine learning

COVID-19 has spread rapidly worldwide in the past three years, triggering partial and full lockdowns globally. The successful control of the COVID-19 pandemic on a global scale depended heavily upon the accurate detection of COVID-19. However, the main diagnostic tests for COVID-19 have some significant limitations, e.g. the major nucleic acid (RT-PCR) tests while having a high sensitivity are time-consuming and require expensive equipment with the shortage of test kits in many countries. Antigen lateral flow tests have a lower sensitivity and they cannot be used during the early pandemic as well as usually more expensive than the full or complete blood count test used in this paper which can be potentially performed using a finger blood sample. The last decade has seen rapid growth of AI, particularly deep learning, which has found wide applications in medical image analysis, with results comparable to and even surpassing human expert performance. There have been several machine learning models reported for COVID-19 diagnostics or prognosis predictions, most of them based on CT and X-ray images. In this paper we have applied traditional machine learning and convolutional neural networks (CNNs) based deep learning to the blood test data obtained from hematology analyzers and demonstrated that the AI models can be used to detect COVID-19 with a high degree of accuracy (>97%). The performance of different classifiers will be compared and discussed. The work should have potential applications in current COVID-19 and future pandemics.