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The COVID-19 pandemic has presented a serious challenge to the hepatology community, particularly healthcare professionals and patients. While the rapid development of safe and effective vaccines and treatments has improved the clinical landscape, the emergence of the omicron variant has presented new challenges. Thus, it is timely that the European Association for the Study of the Liver provides a summary of the latest data on the impact of COVID-19 on the liver and issues guidance on the care of patients with chronic liver disease, hepatobiliary cancer, and previous liver transplantation, as the world continues to deal with the consequences of the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

Illustration of the assembly, distribution, and point-of-care use of a rapidly-deployable, cell-free COVID-19 biosensor: 1) Assemble: Assembling CFPS reagents by mixing E. coli lysate, murine RNase Inhibitor (mRI), energy sources, cofactors, and toehold switch riboregulator plasmid. 2) Print: aliquoting CFPS reagents onto paper substrates housed in a plastic test cassette. 3) Dehydrate: lyophilizing CFPS reagents on paper substrates. 4) Distribute. 5) Saliva sample: applying saliva samples onto cassette without pretreatments. 6) Reaction: bioluminescent protein expression in presence of target RNA (+), or ribosome detachment in absence of target RNA (-). 7) Visual result: bioluminescent output in the presence of target RNA and NanoLuc luciferase expression. [Display omitted] • Progress towards a rapid, low-cost, point-of-care Covid-19 biosensor. • Engineered toehold switches respond to saliva enriched with SARS-CoV-2 RNA. • mRI enables robust paper-based cell-free protein synthesis in the presence of saliva. • Plastic cassette houses paper-based diagnostic test for simple distribution and use. The COVID-19 pandemic has illustrated the global demand for rapid, low-cost, widely distributable and point-of-care nucleic acid diagnostic technologies. Such technologies could help disrupt transmission, sustain economies and preserve health and lives during widespread infection. In contrast, conventional nucleic acid diagnostic procedures require trained personnel, complex laboratories, expensive equipment, and protracted processing times. In this work, lyophilized cell-free protein synthesis (CFPS) and toehold switch riboregulators are employed to develop a promising paper-based nucleic acid diagnostic platform activated simply by the addition of saliva. First, to facilitate distribution and deployment, an economical paper support matrix is identified and a mass-producible test cassette designed with integral saliva sample receptacles. Next, CFPS is optimized in the presence of saliva using murine RNase inhibitor. Finally, original toehold switch riboregulators are engineered to express the bioluminescent reporter NanoLuc in response to SARS-CoV-2 RNA sequences present in saliva samples. The biosensor generates a visible signal in as few as seven minutes following administration of 15 μL saliva enriched with high concentrations of SARS-CoV-2 RNA sequences. The estimated cost of this test is less than 0.50 USD, which could make this platform readily accessible to both the developed and developing world. While additional research is needed to decrease the limit of detection, this work represents important progress toward developing a diagnostic technology that is rapid, low-cost, distributable and deployable at the point-of-care by a layperson. [ABSTRACT FROM AUTHOR]

[Display omitted] • A novel ChF/ZnO/CNT nano-hybrid was fabricated for detection of COVID-19. • Paper based aptasensor with colorimetric detection approach was developed. • Oxidation of TMB substrate by biosensor was detectable by naked eye sensitively. • The LOD of method was 0.05 pg/mL in colorimetric and 8 pg/mL in paper-based platform. Corona Virus Disease 2019 (COVID-19) as the infectious disease caused the pandemic disease around the world through infection by SARS-CoV-2 virus. The common diagnosis approach is Quantitative RT-PCR (qRT-PCR) which is time consuming and labor intensive. In the present study a novel colorimetric aptasensor was developed based on intrinsic catalytic activity of chitosan film embedded with ZnO/CNT (ChF/ZnO/CNT) on 3,3′,5,5′-tetramethylbenzidine (TMB) substrate. The main nanocomposite platform was constructed and functionalized with specific COVID-19 aptamer. The construction subjected with TMB substrate and H 2 O 2 in the presence of different concentration of COVID-19 virus. Separation of aptamer after binding with virus particles declined the nanozyme activity. Upon addition of virus concentration, the peroxidase like activity of developed platform and colorimetric signals of oxidized TMB decreased gradually. Under optimal conditions the nanozyme could detect the virus in the linear range of 1–500 pg mL and LOD of 0.05 pg mL. Also, a paper-based platform was used for set up the strategy on applicable device. The paper-based strategy showed a linear range between 50 and 500 pg mL with LOD of 8 pg mL. The applied paper based colorimetric strategy showed reliable results for sensitive and selective detection of COVID-19 virus with the cost-effective approach. [ABSTRACT FROM AUTHOR]

According to a recent World Health Organization estimate, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, which originated in China in 2019, has spread globally, infecting nearly 100 million people worldwide by January 2021. Patients with chronic liver diseases (CLD), particularly cirrhosis, hepatobiliary malignancies, candidates for liver transplantation, and immunosuppressed individuals after liver transplantation appear to be at increased risk of infections in general, which in turn translates into increased mortality. This is also the case for SARS-CoV-2 infection, where patients with cirrhosis, in particular, are at high risk of a severe COVID-19 course. Therefore, vaccination against various pathogens including SARS-CoV-2, administered as early as possible in patients with CLD, is an important protective measure. However, due to impaired immune responses in these patients, the immediate and long-term protective response through immunisation may be incomplete. The current SARS-CoV-2 pandemic has led to the exceptionally fast development of several vaccine candidates. A small number of these SARS-CoV-2 vaccine candidates have already undergone phase III, placebo-controlled, clinical trials in healthy individuals with proof of short-term safety, immunogenicity and efficacy. However, although regulatory agencies in the US and Europe have already approved some of these vaccines for clinical use, information on immunogenicity, duration of protection and long-term safety in patients with CLD, cirrhosis, hepatobiliary cancer and liver transplant recipients has yet to be generated. This review summarises the data on vaccine safety, immunogenicity, and efficacy in this patient population in general and discusses the implications of this knowledge on the introduction of the new SARS-CoV-2 vaccines. [ABSTRACT FROM AUTHOR]

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has become pandemic, reaching almost one million death worldwide. At present standard treatment for coronavirus disease 2019 (COVID-19) is not well defined because the evidence, either from randomized or observational studies, with conflicting results, has led to rapid changes in treatment guidelines. Our aim was to narratively summarize the available literature on the management of COVID-19 in order to combine current evidence and interpretation of the data by experts who are treating patients in the frontline setting. The panel conducted a detailed review of the literature and eventual press releases from randomized clinical trials for each possible available treatment. Inductive PubMed search waws performed for publications relevant to the topic, including all clinical trials conducted. The result was a flowchart with treatment indications for patients with COVID-19. After 6 months of a pandemic situation and before a possible second coronavirus wave descends on Europe, it is important to evaluate which drugs proved to be effective while also considering that results from many randomized clinical trials are still awaited. Indeed, among treatments for COVID-19, only glucocorticoids have resulted in an association with a significant decrease in mortality in published randomized controlled trials. New therapeutic strategies are urgently needed. [ABSTRACT FROM AUTHOR]

[Display omitted] • A rotational paper-based analytical device was designed for differential detection of SARS-CoV-2 and influenza A H1N1 virus. • The tetrahedral DNA framework could fix aptamer in a straightforward direction and well-defined spacing. • The strong affinity of aptamer toward target S protein and H1N1 ensured the specificity of this strategy. • The developed platform exhibited excellent analysis performance in terms of simple, rapid, low cost, disposability and high sensitivity. Coronavirus disease 2019 (COVID-19) and influenza A are two respiratory infectious diseases with similar clinical manifestations. Because of the complex global epidemic situation of COVID-19, the distinction and diagnosis of COVID-19 and influenza A infected persons is crucial for epidemic prevention and control. In this study, tetrahedral DNA framework (TDF) was combined with a rotational paper-based analytical device, and the color change generated by the reaction between horseradish peroxidase (HRP) and 3,3′5,5′-tetramethylbenzidine (TMB)–H 2 O 2 was used for grayscale signal analysis by ImageJ software. The quantitative detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and influenza A H1N1 virus were realized simultaneously. Under the optimal conditions, the paper-based analytical device showed a good linear relationship between the two viruses in the range of 10-14-10-8g/mL, and the two viruses were not affected by cross reaction. This sensor provides a convenient and reliable method for clinical rapid differentiation and diagnosis of COVID-19 and influenza A. [ABSTRACT FROM AUTHOR]

COVID-19 is a highly diffuse respiratory infection caused by severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2). Currently, quantitative real-time polymerase chain reaction (qRT-PCR) technology is commonly used in clinical diagnosis of COVID-19. However, this method is time-consuming and labor-intensive, which is limited in clinical application. Here, we propose a new method for the ultrasensitive and visual detection of SARS-CoV-2 viral nucleic acid. The assay integrates with a paper device and highly efficient isothermal amplification technology - Netlike rolling circle amplification (NRCA), which can reach a limit of detection of 4.12 aM. The paper-based NRCA owns advantages of specificity, portability, visualization and low-cost. Therefore, this method can effectively meet the requirements of point-of-care testing, providing a novel molecular detection technology for clinical diagnosis of COVID-19 and promoting the development of NRCA devices. [Display omitted] ● A paper biosensor was used for ultrasensitive and visual detection of SARS-CoV-2. ● Amplified analysis has been achieved by netlike rolling circle amplification. ● The paper-based NRCA owns advantages of portability, visualization and low-cost. ● The assay can effectively meet the requirements of point-of-care diagnosis of COVID-19. [ABSTRACT FROM AUTHOR]

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a serious threat to human health. Current methods such as reverse transcription polymerase chain reaction (qRT-PCR) are complex, expensive, and time-consuming. Rapid, and simple screening methods for the detection of SARS-CoV-2 are critically required to fight the current pandemic. In this work we present a proof of concept for, a simple optical sensing method for the screening of SARS-CoV-2 through its spike protein subunit S1. The method utilizes a target-specific extractor chip to bind the protein from the biological specimens. The disulfide bonds of the protein are then reduced into a biothiol with sulfhydryl (SH) groups that react with a blue-colored benzothiazole azo dye-Hg complex (BAN-Hg) and causes the spontaneous change of its blue color to pink which is observable by the naked eye. A linear relationship between the intensity of the pink color and the logarithm of reduced S1 protein concentration was found within the working range 130 ng.mL−1-1.3 pg mL−1. The lowest limit of detection (LOD) of the assay was 130 fg mL−1. A paper based optical sensor was fabricated by loading the BAN-Hg sensor onto filter paper and used to screen the S1 protein in spiked saliva and patients' nasopharyngeal swabs. The results obtained by the paper sensor corroborated with those obtained by qRT-PCR. The new paper-based sensing method can be extended to the screening of many viruses (e.g. the human immunodeficiency virus, the human polyomavirus, the human papilloma virus, the adeno associated viruses, the enteroviruses) through the cysteine residues of their capsid proteins. The new method has strong potential for screening viruses at pathology labs and in remote areas that lacks advanced scientific infrastructure. Further clinical studies are warranted to validate the new sensing method. [Display omitted] • A proof of concept on an optical sensor for screening viruses through the capsid proteins. • The sensor was used to detect SARS-CoV-2 through the S1 protein. • The free cysteine of the protein causes the sensor color to change spontaneously. • The sensor detected the protein in biological specimens down to 130 fg mL−1 • The sensing method is rapid when compared to qRT-PCR. [ABSTRACT FROM AUTHOR]

As the COVID-19 epidemic continues, concerns about long-term health impacts, specifically long COVID, persist. While the prevalence and symptomatology of long COVID have been explored in various global contexts, large-scale cohort studies in Japan remain limited, especially after the advent of the Omicron variant. In this observational study, 4,047 residents with a history of COVID-19 living in Toyonaka City, Osaka Prefecture, were assessed for long COVID symptoms using the VOICE mobile application and a paper survey. Respondents provided demographic and health information, as well as information regarding COVID-19 infection and subsequent symptoms. A Cox proportional hazard regression model was used to estimate the multivariable-adjusted hazard ratios and 95 % confidence intervals for overall morbidity of long COVID symptoms. The survey found that 5.2 % of participants reported the persistence of one or more symptoms at 30 days post-onset. Fatigue was the most commonly reported symptom (1.75 %), followed by hair loss (1.41 %), and cough (1.28 %). Factors associated with an increased risk of experiencing long COVID symptoms included BMI, severe illness during the acute phase, and infection with certain COVID-19 variant strains, including Alpha, Delta, and Omicron. However, the incidence rate of long COVID appears to be decreasing with the dominance of the Omicron variant. This large-scale study from Toyonaka City suggests a 5.2 % prevalence rate for persistent COVID-19 symptoms 4 weeks post-infection, potentially indicating a lower prevalence of long COVID in Japanese populations after the rise of the Omicron variant. [ABSTRACT FROM AUTHOR]

Coronavirus disease 2019 (COVID-19) has been recognized as a global pandemic outbreak, opening the most severe socio-economic crisis since World War II. Different scientific activities have been emerged in this global scenario, including the development of innovative analytical tools to measure nucleic acid, antibodies, and antigens in the nasopharyngeal swab, serum, and saliva for prompt identification of COVID-19 patients and to evaluate the immune response to the vaccine. The detection of SARS-CoV-2 in saliva remains a challenge for the lack of sufficient sensitivity. To address this issue, we developed a novel paper-based immunoassay using magnetic beads to support the immunological chain and 96-well wax-printed paper plate as a platform for color visualization by using a smartphone combined with Spotxel free-charge app. To assess the reliability of the measurement of SARS-CoV-2 in saliva, untreated saliva was used as a specimen and the calibration curve demonstrated a dynamic range up to 10 μg/mL, with a detection limit equal to 0.1 μg/mL. The effectiveness of this sustainable analytical tool in saliva was evaluated by comparing the data with the nasopharyngeal swab specimens sampled by the same patients and tested with Real-Time PCR reference method, founding 100% of agreement, even in the case of high Cycle Threshold (CT) numbers (low viral load). Furthermore, the positive saliva samples were characterized by the next-generation sequencing method, demonstrating the capability to detect the Delta variant, which is actually (July 2021) the most relevant variant of concern. • Colorimetric smartphone-assisted immunosensor for detection of SARS-CoV-2 in saliva. • Multiplex detection by paper-based immunosensor based on 96-well wax-printed paper. • Capability to detect the Delta variant, positive samples characterized by the NGS method. [ABSTRACT FROM AUTHOR]

Respiratory viruses, especially coronaviruses, have resulted in worldwide pandemics in the past couple of decades. Saliva-based paper microfluidic assays represent an opportunity for noninvasive and rapid screening, yet both the sample matrix and test method come with unique challenges. In this work, we demonstrated the rapid and sensitive detection of SARS-CoV-2 from saliva samples, which could be simpler and more comfortable for patients than existing methods. Furthermore, we systematically investigated the components of saliva samples that affected assay performance. Using only a smartphone, an antibody-conjugated particle suspension, and a paper microfluidic chip, we made the assay user-friendly with minimal processing. Unlike the previously established flow rate assays that depended solely on the flow rate or distance, this unique assay analyzes the flow profile to determine infection status. Particle-target immunoagglutination changed the surface tension and subsequently the capillary flow velocity profile. A smartphone camera automatically measured the flow profile using a Python script, which was not affected by ambient light variations. The limit of detection (LOD) was 1 fg/μL SARS-CoV-2 from 1% saliva samples and 10 fg/μL from simulated saline gargle samples (15% saliva and 0.9% saline). This method was highly specific as demonstrated using influenza A/H1N1. The sample-to-answer assay time was <15 min, including <1-min capillary flow time. The overall accuracy was 89% with relatively clean clinical saline gargle samples. Despite some limitations with turbid clinical samples, this method presents a potential solution for rapid mass testing techniques during any infectious disease outbreak as soon as the antibodies become available. [ABSTRACT FROM AUTHOR]

Real-time reverse transcriptase-polymerase chain reaction (RT-PCR)-based assays are the gold standard for virus diagnosis. Point-of-care (POC) technologies have shown great progress during this period. Herein, we propose a novel fuchsine dye-loaded polymersome for a colorimetric paper-based dot blot spike protein diagnostic assay for COVID-19 via smartphone-assisted sensing. The prepared platform aimed to create an adaptable tool that competes with traditional nanoparticle-based assays employing gold and silver. Analytical characterization and application of the testing platform showed high sensitivity (10 times better than gold nanoparticles), stability, fast turnaround, and reproducibility. The potential and possibilities demonstrated by the current platform could be observed in its adaptability for different markers and pathologies. In addition, smartphone-assisted sensing emphasizes the ability to use the tool at home by common peoples which can lower the burden on the healthcare facilities and reach more underdeveloped regions. • Facile, quick, and sensitive colorimetric paper-based biosensor for COVID-19. • Platform is based on functionalized dye-loaded polymersome. • Polymersomes were more sensitive than silver-enhanced gold nanoparticles. • Higher stability, repeatability, and reproducibility. • The biosensor is adjustable for other diseases. [ABSTRACT FROM AUTHOR]

The importance of user-friendly, inexpensive, sensitive, and selective detection of viruses has been highlighted again due to the recent Coronavirus disease 2019 (COVID-19) pandemic. Among the analytical tools, paper-based devices (PADs) have become a leading alternative for point-of-care (POC) testing. In this review, we discuss the recent development strategies and applications in nucleic acid-based, antibody/antigen-based and other affinity-based PADs using optical and electrochemical detection methods for sensing viruses. In addition, advantages and drawbacks of presented PADs are identified. Current state and insights towards future perspectives are presented regarding developing POC diagnosis platform for COVID-19. This review considers state-of-the-art technologies for further development and improvement in PADs performance for virus detection. [Display omitted] • Reviewed developments in PADs for optical and electrochemical detection of viruses. • Highlighted recent applications in antibody/antigen-, nucleic acid-, aptamer- and CRISPR-based PADs for viral detection. • Emphasized low-cost POC diagnostic tools to control the global COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

During the height of the global COVID-19 pandemic, the test-negative design (TND) was extensively used in many countries to evaluate COVID-19 vaccine effectiveness (VE). Typically, the TND involves the recruitment of care-seeking individuals who meet a common clinical case definition. All participants are then tested for an infection of interest. To review and describe the variation in TND methodology, and disclosure of potential biases, as applied to the evaluation of COVID-19 VE during the early vaccination phase of the pandemic. We conducted a systematic review by searching four biomedical databases using defined keywords to identify peer-reviewed articles published between January 1, 2020, and January 25, 2022. We included only original articles that employed a TND to estimate VE of COVID-19 vaccines in which cases and controls were evaluated based on SARS-CoV-2 laboratory test results. We identified 96 studies, 35 of which met the defined criteria. Most studies were from North America (16 studies) and targeted the general population (28 studies). Outcome case definitions were based primarily on COVID-19-like symptoms; however, several papers did not consider or specify symptoms. Cases and controls had the same inclusion criteria in only half of the studies. Most studies relied upon administrative or hospital databases assembled for a different (non-evaluation) clinical purpose. Potential unmeasured confounding (20 studies), misclassification of current SARS-CoV-2 infection (16 studies) and selection bias (10 studies) were disclosed as limitations by some studies. We observed potentially meaningful deviations from the validated design in the application of the TND during the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is emerging as a global pandemic outbreak. To date, approximately one million deaths and over 32 million cases have been reported. This ongoing pandemic urgently requires an accurate testing device that can be used in the field in a fast manner. Serological assays to detect antibodies have been proven to be a great complement to the standard method of reverse transcription-polymerase chain reaction (RT-PCR), particularly after the second week of infection. We have developed a specific and sensitive immunosensor for immunoglobulin detection produced against SARS-CoV-2. Unlike other lateral flow-based assays (LFAs) involving the utilization of multiple antibodies, we have reported a label-free paper-based electrochemical platform targeting SARS-CoV-2 antibodies without the specific requirement of an antibody. The presence of SARS-CoV-2 antibodies will interrupt the redox conversion of the redox indicator, resulting in a decreased current response. This electrochemical sensor was proven effective in real clinical sera from patients with satisfactory results. In addition, the proposed format was also extended to antigen detection (the spike protein of SARS-CoV-2), which presents new possibilities for diagnosing COVID-19. • Electrochemical sensor for COVID-19 diagnostic. • Serological assay for SARS-CoV-2 antibodies was demonstrated. • Sensitivity enhancement compared to the traditional LFA devices. • Applicable to real clinical sera with satisfactory results. [ABSTRACT FROM AUTHOR]

• Detection of cytokine storm biomarkers with mobile biosensors. • Immunosensors are made solely of cellulose modified with antibody-decorated nanoparticles. • Turnaround time under 10 min. • Detection of biomarkers in respiratory samples allows monitoring local inflammation. • Compatible with decentralized health care schemes. Decentralizing COVID-19 care reduces contagions and affords a better use of hospital resources. We introduce biosensors aimed at detecting severe cases of COVID-19 in decentralized healthcare settings. They consist of a paper immunosensor interfaced with a smartphone. The immunosensors have been designed to generate intense colorimetric signals when the sample contains ultralow concentrations of IL-6, which has been proposed as a prognosis biomarker of COVID-19. This is achieved by combining a paper-based signal amplification mechanism with polymer-filled reservoirs for dispensing antibody-decorated nanoparticles and a bespoken app for color quantification. With this design we achieved a low limit of detection (LOD) of 10−3 pg mL-1 and semi-quantitative measurements in a wide dynamic range between 10−3 and 102 pg mL-1 in PBS. The assay time is under 10 min. The low LOD allowed us to dilute blood samples and detect IL-6 with an LOD of 1.3 pg mL-1 and a dynamic range up to 102 pg mL-1. Following this protocol, we were able to stratify COVID-19 patients according to different blood levels of IL-6. We also report on the detection of IL-6 in respiratory samples (bronchial aspirate, BAS) from COVID-19 patients. The test could be easily adapted to detect other cytokines such as TNF-α and IL-8 by changing the antibodies decorating the nanoparticles accordingly. The ability of detecting cytokines in blood and respiratory samples paves the way for monitoring local inflammation in the lungs as well as systemic inflammation levels in the body. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has highlighted the need for diversity in the market and alternative materials for personal protective equipment (PPE). Paper has high coatability for tunable barrier performance, and an agile production process, making it a potential substitute for polyolefin-derived PPE materials. Bleached and newsprint papers were laminated with polyethylene (PE) coatings of different thicknesses, and characterised for their potential use as medical gowns for healthcare workers and COVID-19 patients. Thicker PE lamination improved coating homogeneity and water vapour resistance. 49 GSM bleached paper with 16 GSM PE coating showed high tensile and seam strength, and low water vapour transmission rate (WVTR). Phi-X174 bacteriophage testing revealed that paper laminated with 15 GSM coating hinders virus penetration. This research demonstrates that PE laminated paper is a promising material for low cost viral protective gowns. [Display omitted] • Polyethylene (PE) laminated bleached paper was assessed as a medical gown material. • High tensile and seam strength were achieved for the laminate composites. • Viral penetration was hindered by a 49 GSM paper sheet with a 15 GSM PE coating. • The laminated paper met medical gown material testing standards. • Prototypes were praised by medical professionals when worn in a clinical setting. [ABSTRACT FROM AUTHOR]

COVID-19 has evolved into a global pandemic. Early and rapid detection is crucial to control of the SARS-CoV-2 transmission. While representing the gold standard for early diagnosis, nucleic acid tests for SARS-CoV-2 are often complicated and time-consuming. Serological rapid antibody tests are characterized by high rates of false-negative diagnoses, especially during early infection. Here, we developed a novel nanozyme-based chemiluminescence paper assay for rapid and sensitive detection of SARS-CoV-2 spike antigen, which integrates nanozyme and enzymatic chemiluminescence immunoassay with the lateral flow strip. The core of our paper test is a robust Co–Fe@hemin-peroxidase nanozyme that catalyzes chemiluminescence comparable with natural peroxidase HRP and thus amplifies immune reaction signal. The detection limit for recombinant spike antigen of SARS-CoV-2 was 0.1 ng/mL, with a linear range of 0.2-100 ng/mL. Moreover, the sensitivity of test for pseudovirus could reach 360 TCID 50 /mL, which was comparable with ELISA method. The strip recognized SARS-CoV-2 antigen specifically, and there was no cross reaction with other coronaviruses or influenza A subtypes. This testing can be completed within 16 min, much shorter compared to the usual 1-2 h required for currently used nucleic acid tests. Furthermore, signal detection is feasible using the camera of a standard smartphone. Ingredients for nanozyme synthesis are simple and readily available, considerably lowering the overall cost. In conclusion, our paper test provides a high-sensitive point-of-care testing (POCT) approach for SARS-CoV-2 antigen detection, which should greatly facilitate early screening of SARS-CoV-2 infections, and considerably lower the financial burden on national healthcare resources. • Point-of-care antigen tests for screening of SARS-CoV-2 infection were established. • Chemiluminescence improves sensitivity of paper test and benefits early screening. • Nanozyme with high peroxidase activity and stability catalyzes chemiluminescence. • Nanozyme chemiluminescence paper test brings high efficiency and low cost. [ABSTRACT FROM AUTHOR]

Passive immunotherapy with plasma derived from patients convalescent from SARS-CoV-2 infection can be a promising approach in the treatment of COVID-19 patients. It is important that Blood Establishments are prepared to satisfy requests for immune plasma by defining the requirements applicable to plasma donors and the standards for preparation, qualification, storage, distribution and control of use of the product. This position paper is aimed to give recommendations on biological characteristics of a plasma preparation from convalescent donors and to support the evaluation of this therapeutic approach in more rigorous investigations. [ABSTRACT FROM AUTHOR]

• In this article, an optimal evaluation of re-opening policies for COVID-19 is developed. • The method provides effective re-opening policies using agent-based models and the whale optimization algorithm. • Agent-based models simulate the transmission risk in scenarios that are impossible to evaluate in real conditions. • The whale optimization algorithm is used to find the best scenario where the lowest risk of infection is reached. • Experiments demonstrate that the proposed approach delivers realistic predictions to formulate re-opening policies. A new contagious disease or unidentified COVID-19 variants could provoke a new collapse in the global economy. Under such conditions, companies, factories, and organizations must adopt reopening policies that allow their operations to reduce economic effects. Effective reopening policies should be designed using mathematical models that emulate infection chains through individual interactions. In contrast to other modeling approaches, agent-based schemes represent a computational paradigm used to characterize the person-to-person interactions of individuals inside a system, providing accurate simulation results. To evaluate the optimal conditions for a reopening policy, authorities and decision-makers need to conduct an extensive number of simulations manually, with a high possibility of losing information and important details. For this reason, the integration of optimization and simulation of reopening policies could automatically find the realistic scenario under which the lowest risk of infection was attained. In this paper, the metaheuristic technique of the Whale Optimization Algorithm is used to find the solution with the minimal transmission risk produced by an agent-based model that emulates a hypothetical re-opening context. Our scheme finds the optimal results of different generical activation scenarios. The experimental results indicate that our approach delivers practical knowledge and essential estimations for identifying optimal re-opening strategies with the lowest transmission risk. [ABSTRACT FROM AUTHOR]

• Transmissibility of three variants was Omicron BA.2>Omicron BA.1 > Delta. • Omicron BA.2 variant has less pathogenicity than Omicron BA.1 and Delta variant. • Transmissibility in cycle threshold value should be discussed in further research. The Omicron BA.2 variant is probably the main epidemic strain worldwide at present. Comparing the epidemiological characteristics, transmissibility, and influencing factors of SARS-CoV-2, the results obtained in this paper will help to provide theoretical support for disease control. This study was a historical information analysis, using the R programming language and SPSS 24.0 for statistical analysis. The Geoda and Arc GIS were used for spatial autocorrelation analysis. Local spatial autocorrelations of the incidence rate were observed in Delta and Omicron BA.1 outbreaks, whereas Omicron BA.2 outbreaks showed a random distribution in incidence rate. The time-dependent reproduction number of Delta, Omicron BA.1, and Omicron BA.2 were 3.21, 4.29, and 2.96, respectively, and correspondingly, the mean serial interval were 4.29 days (95% confidence interval [CI]: 0.37-8.21), 3.84 days (95% CI: 0-8.37), and 2.77 days (95% CI: 0-5.83). The asymptomatic infection rate of cases in Delta, Omicron BA.1, and Omicron BA.2 outbreaks were 21.71%, 6.25%, and 4.35%, respectively. The Omicron BA.2 variant had the greatest serial interval, transmissibility, and transmission speed, followed by BA.1, and then Delta. Compared with Delta and Omicron BA.1 variants, the Omicron BA.2 variant may be less pathogenic and more difficult to control than Omicron BA.1 and Delta. [ABSTRACT FROM AUTHOR]

• While emerging diseases might be surprising and unpredictable; some could be foreseen. • Emerging diseases were the reason behind papers published by the WHO, and others, addressing likely pathogens causing future outbreaks. • Such announcements, as for coronaviruses, may be viewed as "warnings" and appeared since the SARS outbreak in the winter of 2002–2003. • Taking these warnings into consideration will doubtlessly aid in analyzing reports regarding possible future outbreaks as well as building various strategies for prevention and coping with such epidemics. Infectious diseases are known to act in both predictable and unpredictable ways, which leads to the notions of emerging and reemerging infectious diseases. Emerging diseases with their disastrous consequences might be surprising and unpredictable, but they could be foreseen. For instance, some emerging diseases and recently the coronavirus disease 2019 (COVID-19) were the reason for papers published by the World Health Organization (WHO) and other researchers addressing the likely pathogens causing future outbreaks, according to the reports of the WHO in 2016 and 2018. Although it might seem like a wisdom in retrospect, several studies had already indicated possible future outbreaks caused by coronaviruses. Announcements, which may be viewed as "warnings," appeared since the emergence of the first coronavirus-related outbreak caused by severe acute respiratory syndrome coronavirus (SARS-CoV) in the winter of 2002–2003 and a later outbreak caused by the Middle East respiratory syndrome coronavirus (MERS-CoV) in 2012–2013. Therefore, we were curious to review the medical literature prior to the COVID-19 pandemic with an aim to enumerate and evaluate studies addressing and warning against future outbreaks, and surprisingly pandemics, of members of coronaviruses. Interestingly, we found numerous studies that correctly predicted the current pandemic of COVID-19. While this part is highly interesting, how authorities reacted and prepared for warnings, if any, and how will they get prepared for the next warnings are our main messages. Taking these points into serious consideration will certainly aid in analyzing reports regarding possible future outbreaks as well as in developing various strategies for prevention and coping with such epidemics. [ABSTRACT FROM AUTHOR]

Behavioral economic demand models quantify the extent to which an organism defends its consumption of a commodity. Commodity purchase tasks permit humans a quick yet psychometrically sound approach to assessing commodity demand for various retail products. Operant behavioral economic literature suggests economy type (open vs closed) can significantly alter demand, yet this effect is largely undocumented in the commodity purchase task literature. In this study, we leveraged the market pressures for retail goods (hand lotion and sanitizer; paper towels and toilet paper; soda and water) resulting from SARS-CoV-2 into a natural experiment comparing within-subject demand across two time-points during the pandemic using a crowdsourced approach. Results suggest that hypothetical commodity purchase tasks are sensitive to extra-experimental market pressures (e.g., scarcity due to the closing of economies), adding additional confidence to the self-report nature of purchase task responding and providing further construct validity to these approaches. • Reinforcer scarcity modulates operant demand. • The SARS-CoV-2 pandemic presented a natural experiment on scarcity. • Crowdsourced data shows effects of real-world scarcity on hypothetical demand. [ABSTRACT FROM AUTHOR]

• SARS-CoV-2 significantly impacts the UPS, a key cellular regulatory mechanism. • SARS-CoV-2 encoded proteinsinteract with host UPS, influencing immune signaling and apoptosis. • Stability of ORF3a and ORF8 may or may not be influenced by host proteasome. • Unlike previous studies, recent studies do not show ORF3a as an ion channel. • SARS-CoV-2 PLpro alters host immune responses via interfering withUPS. • Proteomic studies reveal changes in ubiquitination in SARS-CoV-2 infected cells. • Promising treatment include targeting PLpro with zinc-ejector drugs, targeting viral nsp12 via heat treatment. The Ubiquitin proteasome system (UPS), an essential eukaryotic/host/cellular post-translational modification (PTM), plays a critical role in the regulation of diverse cellular functions including regulation of protein stability, immune signaling, antiviral activity, as well as virus replication. Although UPS regulation of viral proteins may be utilized by the host as a defense mechanism to invade viruses, viruses may have adapted to take advantage of the host UPS. This system can be manipulated by viruses such as the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) to stimulate various steps of the viral replication cycle and facilitate pathogenesis, thereby causing the respiratory disease COVID-19. Many SARS-CoV-2 encoded proteins including open reading frame 3a (ORF3a), ORF6, ORF7a, ORF9b, and ORF10 interact with the host's UPS machinery, influencing host immune signaling and apoptosis. Moreover, SARS-CoV-2 encoded papain-like protease (PLpro) interferes with the host UPS to facilitate viral replication and to evade the host's immune system. These alterations in SARS-CoV-2 infected cells have been revealed by various proteomic studies, suggesting potential targets for clinical treatment. To provide insight into the underlying causes of COVID-19 and suggest possible directions for therapeutic interventions, this paper reviews the intricate relationship between SARS-CoV-2 and UPS. Promising treatment strategies are also investigated in this paper including targeting PLpro with zinc-ejector drugs, as well as targeting viral non-structural protein (nsp12) via heat treatment associated ubiquitin-mediated proteasomal degradation to reduce viral pathogenesis. [ABSTRACT FROM AUTHOR]

The mutant strains of COVID-19 caused a global explosion of infections, including many cities of China. In 2020, a hybrid AI model was proposed by Zheng et al., which accurately predicted the epidemic in Wuhan. As the main part of the hybrid AI model, ISI method makes two important assumptions to avoid over-fitting. However, the assumptions cannot be effectively applied to new mutant strains. In this paper, a more general method, named the multi-weight susceptible-infected model (MSI) is proposed to predict COVID-19 in Chinese Mainland. First, a Gaussian pre-processing method is proposed to solve the problem of data fluctuation based on the quantity consistency of cumulative infection number and the trend consistency of daily infection number. Then, we improve the model from two aspects: changing the grouped multi-parameter strategy to the multi-weight strategy, and removing the restriction of weight distribution of viral infectivity. Experiments on the outbreaks in many places in China from the end of 2021 to May 2022 show that, in China, an individual infected by Delta or Omicron strains of SARS-CoV-2 can infect others within 3–4 days after he/she got infected. Especially, the proposed method effectively predicts the trend of the epidemics in Xi'an, Tianjin, Henan, and Shanghai from December 2021 to May 2022. [ABSTRACT FROM AUTHOR]

Coronavirus 2019 (COVID-19) and its variants are still spreading rapidly with deadly consequences and profound impacts on the global health and world economy. Without a suitable vaccine, mobility restriction has been the most effective method so far to prevent its spreading and avoid overwhelming the heath system of the affected country. The compartmental model SIR (or Susceptible, Infected, and Recovered) is the most popular mathematical model used to predict the course of the COVID-19 pandemic in order to plan the control actions and mobility restrictions against its spreading. A major limitation of this model in relation to modeling the spreading of COVID-19, and the mobility limitation strategy, is that the SIR model does not include mobility or take into account changes in mobility within its structure. This paper develops and tests a new hybrid SIR model; SIR-M which is integrated with an urban activity travel model to explore how it might improve the prediction of pandemic course and the testing of mobility limitation strategies in managing virus spread. The paper describes the enhanced methodology and tests a range of mobility limitation strategies on virus spread outcomes. Implications for policy and research futures are suggested. [ABSTRACT FROM AUTHOR]

• Vaccine-derived herd immunity against COVID-19 can be achieved if at least 60% of the population is fully-vaccinated. • COVID-19 elimination is feasible by June 2022 if the current baseline full vaccination coverage is increased by about 20%. • Elimination prospects are improved significantly if vaccination is combined with the use of moderate to high-quality masks. • Having more people wear surgical masks is more beneficial than having fewer people wear the highly-effective N95 masks. • Treatment of symptomatic individuals has a significant impact on reducing daily hospitalizations. The effectiveness of control interventions against COVID-19 is threatened by the emergence of SARS-CoV-2 variants of concern. We present a mathematical model for studying the transmission dynamics of two of these variants (Delta and Omicron) in the United States, in the presence of vaccination, treatment of individuals with clinical symptoms of the disease and the use of face masks. The model is parameterized and cross-validated using observed daily case data for COVID-19 in the United States for the period from November 2021 (when Omicron first emerged) to March 2022. Rigorous qualitative analysis of the model shows that the disease-free equilibrium of the model is locally-asymptotically stable when the control reproduction number of the model (denoted by R c) is less than one. This equilibrium is shown to be globally-asymptotically stable for a special case of the model, where disease-induced mortality is negligible and both vaccine-derived immunity in fully-vaccinated individuals and natural immunity do not wane, when the associated reproduction number is less than one. The epidemiological implication of the latter result is that the combined vaccination-boosting strategy can lead to the elimination of the pandemic if its implementation can bring (and maintain) the associated reproduction number to a value less than one. An analytical expression for the vaccine-derived herd immunity threshold is derived. Using this expression, together with the baseline values of the parameters of the parameterized model, we showed that the vaccine-derived herd immunity can be achieved in the United States (so that the pandemic will be eliminated) if at least 68 % of the population is fully-vaccinated with two of the three vaccines approved for use in the United States (Pfizer or Moderna vaccine). Furthermore, this study showed (as of the time of writing in March 2022) that the control reproduction number of the Omicron variant was approximately 3.5 times that of the Delta variant (the reproduction of the latter is computed to be ≈ 0.2782), indicating that Delta had practically died out and that Omicron has competitively-excluded Delta (to become the predominant variant in the United States). Based on our analysis and parameterization at the time of writing of this paper (March 2022), our study suggests that SARS-CoV-2 elimination is feasible by June 2022 if the current baseline level of the coverage of fully-vaccinated individuals is increased by about 20 %. The prospect of pandemic elimination is significantly improved if vaccination is combined with a face mask strategy that prioritizes moderately effective and high-quality masks. Having a high percentage of the populace wearing the moderately-effective surgical mask is more beneficial to the community than having low percentage of the populace wearing the highly-effective N95 masks. We showed that waning natural and vaccine-derived immunity (if considered individually) offer marginal impact on disease burden, except for the case when they wane at a much faster rate (e.g., within three months), in comparison to the baseline (estimated to be within 9 months to a year). Treatment of symptomatic individuals has marginal effect in reducing daily cases of SARS-CoV-2, in comparison to the baseline, but it has significant impact in reducing daily hospitalizations. Furthermore, while treatment significantly reduces daily hospitalizations (and, consequently, deaths), the prospects of COVID-19 elimination in the United States are significantly enhanced if investments in control resources are focused on mask usage and vaccination rather than on treatment. [ABSTRACT FROM AUTHOR]

In March 2020, the World Health Organization (WHO) declared COVID-19 a global epidemic, caused by the SARS-CoV-2 virus. Initially, COVID-19 was diagnosed using real-time reverse transcription–polymerase chain reaction (RT-PCR) tests with a turnaround time of 2–3 days. To enhance diagnostic accuracy, medical professionals use medical imaging alongside RT-PCR. A positive result on both RT-PCR and medical imaging confirms a COVID-19 diagnosis. Imaging modalities like chest X-ray (CXR), computed tomography (CT) scans, and ultrasound are widely utilized for rapid and precise COVID-19 diagnoses. However, interpreting COVID-19 from these images is time-consuming and susceptible to human error. Therefore, leveraging artificial intelligence (AI) methods, particularly deep learning (DL) models, can deliver consistent, high-performance results. Unlike conventional machine learning (ML), DL models automate all stages of feature extraction, selection, and classification. This paper presents a comprehensive review of using DL techniques for diagnosing COVID-19 from medical imaging. The introduction provides an overview of diagnosing the coronavirus using medical imaging, highlighting associated challenges. Subsequently, the paper delves into key aspects of Computer-Aided Diagnosis Systems (CADS) based on DL methods for diagnosing COVID-19, covering segmentation, classification, explainable AI (XAI), and predictive research. Additionally, it reviews the rehabilitation systems such as the Internet of Medical Things (IoMT) in the context of COVID-19. In another section, uncertainty quantification (UQ) research is showcased, focusing on DL models for the diagnosis of Covid-19. Crucial challenges and future research directions are outlined in another section. Finally, discussion and conclusion sections are also provided at the end of the paper. [ABSTRACT FROM AUTHOR]

The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been ongoing for more than three years and urgently needs to be addressed. Traditional Chinese medicine (TCM) prescriptions have played an important role in the clinical treatment of patients with COVID-19 in China. However, it is difficult to uncover the potential molecular mechanisms of the active ingredients in these TCM prescriptions. In this paper, we developed a new approach by integrating the experimental assay, virtual screening, and the experimental verification, exploring the rapid discovery of active ingredients from TCM prescriptions. To achieve this goal, 4 TCM prescriptions in clinical use for different indications were selected to find the antiviral active ingredients in TCMs. The 3-chymotrypsin-like protease (3CLpro), an important target for fighting COVID-19, was utilized to determine the inhibitory activity of the TCM prescriptions and single herb. It was found that 10 single herbs had better inhibitory activity than other herbs by using a fluorescence resonance energy transfer (FRET) - based enzymatic assay of SARS-CoV-2 3CLpro. The ingredients contained in 10 herbs were thus virtually screened and the predicted active ingredients were experimentally validated. Thus, such a research strategy firstly removed many single herbs with no inhibitory activity against SARS-CoV-2 3CLpro at the very beginning by FRET-based assay, making our subsequent virtual screening more effective. Finally, 4 active components were found to have stronger inhibitory effects on SARS-CoV-2 3CLpro, and their inhibitory mechanism was subsequently investigated. Among of them, methyl rosmarinate as an allosteric inhibitor of SARS-CoV-2 3CLpro was confirmed and its ability to inhibit viral replication was demonstrated by the SARS-CoV-2 replicon system. To validate the binding mode via docking, the mutation experiment, circular dichroism (CD), enzymatic inhibition and surface plasmon resonance (SPR) assay were performed, demonstrating that methyl rosmarinate bound to the allosteric site of SARS-CoV-2 3CLpro. In conclusion, this paper provides the new ideas for the rapid discovery of active ingredients in TCM prescriptions based on a specific target, and methyl rosmarinate has the potential to be developed as an antiviral therapeutic candidate against SARS-CoV-2 infection. • This paper explores the rapid discovery of the active ingredients from TCMs. • TCM prescriptions were selected to find anti-SARS-CoV-2 3CLpro active ingredients. • Methyl rosmarinate is an allosteric inhibitor of SARS-CoV-2 3CLpro. [ABSTRACT FROM AUTHOR]

Background: Survivors of acute respiratory distress syndrome (ARDS) are at risk of long-term comorbidities. This systematic review and meta-analysis evaluated health-related quality of life (HRQoL), and physical and psychological impairments in ARDS survivors from 3 months to 5 yr follow-up after ICU discharge.Methods: Systematic search of PubMed, AMED, BNI, and CINAHL databases from January 2000 to date. The primary outcome was HRQoL. Secondary outcomes included physical, pulmonary, and cognitive function, mental health, and return to work. A secondary analysis compared classical ARDS with severe acute respiratory syndrome coronavirus disease-2 (SARS-CoV-2) ARDS.Results: Forty-eight papers met inclusion criteria including 11 693 patients; of those 85% (n=9992) had classical ARDS and 14% (n=1632) had SARS-CoV-2 ARDS. The 36-Item Short Form Health Survey (SF-36) physical component summary score mean (95% confidence interval [CI]) was 46 (41-50) at 3 months, 39 (36-41) at 6 months, and 40 (38-43) at 12 months. The SF-36 mental component summary mean score was 53 (48-57) at 3 months, 45 (40-50) at 6 months, and 44 (42-47) at 12 months. SF-36 values were lower than those found in the normal population up to 5 yr. The predictive distance walked in 6 min was 57% (45-69), 63% (56-69), and 66% (62-70) at 3, 6, and 12 months, respectively. Classical ARDS and SARS-CoV-2 ARDS showed no difference in HRQoL and physical function; however, patients with classical ARDS had higher incidence of anxiety and depression (P<0.001).Conclusion: ARDS survivors can experience reduced HRQoL and physical and mental health impairment. These symptoms might not recover completely up to 5 yr after ICU discharge.Systematic Review Registration: PROSPERO: CRD42021296506. [ABSTRACT FROM AUTHOR]

Background: We performed a systematic review of mechanically ventilated patients with COVID-19, which analysed the effect of tracheostomy timing and technique (surgical vs percutaneous) on mortality. Secondary outcomes included intensive care unit (ICU) and hospital length of stay (LOS), decannulation from tracheostomy, duration of mechanical ventilation, and complications.Methods: Four databases were screened between January 1, 2020 and January 10, 2022 (PubMed, Embase, Scopus, and Cochrane). Papers were selected according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and the Population or Problem, Intervention or exposure, Comparison, and Outcome (PICO) guidelines. Meta-analysis and meta-regression for main outcomes were performed.Results: The search yielded 9024 potentially relevant studies, of which 47 (n=5268 patients) were included. High levels of between-study heterogeneity were observed across study outcomes. The pooled mean tracheostomy timing was 16.5 days (95% confidence interval [CI]: 14.7-18.4; I2=99.6%). Pooled mortality was 22.1% (95% CI: 18.7-25.5; I2=89.0%). Meta-regression did not show significant associations between mortality and tracheostomy timing, mechanical ventilation duration, time to decannulation, and tracheostomy technique. Pooled mean estimates for ICU and hospital LOS were 29.6 (95% CI: 24.0-35.2; I2=98.6%) and 38.8 (95% CI: 32.1-45.6; I2=95.7%) days, both associated with mechanical ventilation duration (coefficient 0.8 [95% CI: 0.2-1.4], P=0.02 and 0.9 [95% CI: 0.4-1.4], P=0.01, respectively) but not tracheostomy timing. Data were insufficient to assess tracheostomy technique on LOS. Duration of mechanical ventilation was 23.4 days (95% CI: 19.2-27.7; I2=99.3%), not associated with tracheostomy timing. Data were insufficient to assess the effect of tracheostomy technique on mechanical ventilation duration. Time to decannulation was 23.8 days (95% CI: 19.7-27.8; I2=98.7%), not influenced by tracheostomy timing or technique. The most common complications were stoma infection, ulcers or necrosis, and bleeding.Conclusions: In patients with COVID-19 requiring tracheostomy, the timing and technique of tracheostomy did not clearly impact on patient outcomes.Systematic Review Protocol: PROSPERO CRD42021272220. [ABSTRACT FROM AUTHOR]

The Brighton Collaboration Benefit-Risk Assessment of VAccines by TechnolOgy (BRAVATO) Working Group has prepared standardized templates to describe the key considerations for the benefit-risk assessment of several vaccine platform technologies, including nucleic acid (RNA and DNA) vaccines. This paper uses the BRAVATO template to review the features of a vaccine employing a proprietary mRNA vaccine platform to develop Moderna COVID-19 Vaccine (mRNA-1273); a highly effective vaccine to prevent coronavirus disease 2019 (Covid-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In response to the pandemic the first in human studies began in March 2020 and the pivotal, placebo-controlled phase 3 efficacy study in over 30,000 adults began in July 2020. Based on demonstration of efficacy and safety at the time of interim analysis in November 2020 and at the time of trial unblinding in March 2021, the mRNA-1273 received Emergency Use Authorization in December 2020 and full FDA approval in January 2022. [ABSTRACT FROM AUTHOR]

• Virus variants are represented by 4-letter sequence based on AA mutations on spike. • An n -distance algorithm in UPGMA is utilized to derive variant phylogenetic tree. • Discovering new strain involves union of mutated sites and randomly generated set X. • New macro-lineage of SARS-CoV-2 is predicted when X reaches a sufficient scale. • Demarcation values that differentiate between various macro-lineages are derived. With the rapid evolution of SARS-CoV-2, the emergence of new strains is an intriguing question. This paper presents an evolutionary theory to analyze the mutations of the virus and identify the conditions that lead to the generation of new strains. We represent the virus variants using a 4-letter sequence based on amino acid mutations on the spike protein and employ an n -distance algorithm to derive a variant phylogenetic tree. We show that the theoretically-derived tree aligns with experimental data on virus evolution. Additionally, we propose an A-X model, utilizing the set of existing mutation sites (A) and a set of randomly generated sites (X), to calculate the emergence of new strains. Our findings demonstrate that a sufficient number of random iterations can predict the generation of new macro-lineages when the number of sites in X is large enough. These results provide a crucial theoretical basis for understanding the evolution of SARS-CoV-2. [ABSTRACT FROM AUTHOR]

The 2019 coronavirus disease outbreak, caused by the severe acute respiratory syndrome type-2 virus (SARS-CoV-2), was declared a pandemic in March 2020. Since its emergence to the present day, this disease has brought multiple countries to the brink of health care collapse during several waves of the disease. One of the most common tests performed on patients is chest x-ray imaging. These images show the severity of the patient's illness and whether it is indeed covid or another type of pneumonia. Automated assessment of this type of imaging could alleviate the time required for physicians to treat and diagnose each patient. To this end, in this paper we propose the use of Convolutional Neural Networks (CNNs) to carry out this process. The aim of this paper is twofold. Firstly, we present a pipeline adapted to this problem, covering all steps from the preprocessing of the datasets to the generation of classification models based on CNNs. Secondly, we have focused our study on the modification of the information fusion processes of this type of architectures, in the pooling layers. We propose a number of aggregation theory functions that are suitable to replace classical processes and have shown their benefits in past applications, and study their performance in the context of the x-ray classification problem. We find that replacing the feature reduction processes of CNNs leads to drastically different behaviours of the final model, which can be beneficial when prioritizing certain metrics such as precision or recall. • Convolutional Neural Networks are effective for detecting SARS-CoV-2 on x-ray images. • Intermediate extracted features can be fused through different aggregation functions. • Grouping functions are harder to train but can offer better classification accuracy. • An early restart policy eases training models which make use of grouping functions. [ABSTRACT FROM AUTHOR]

Coronavirus disease 2019 (COVID-19) caused by the SARS-CoV-2 virus is likely to remain endemic globally despite widespread vaccination. There is increasing concern for myocardial involvement and ensuing cardiac complications due to COVID-19, however, the available evidence suggests these risks are low. Pandemic publishing has resulted in rapid manuscript availability though pre-print servers. Subsequent article retractions, a lack of standardised definitions, over-reliance on isolated troponin elevation and the heterogeneity of studied patient groups (i.e. severe vs. symptomatic vs all infections) resulted in early concern for high rates of myocarditis in patients with and recovering from COVID-19. The estimated incidence of myocarditis in COVID-19 infection is 11 cases per 100,000 infections compared with an estimated 2.7 cases per 100,000 persons following mRNA vaccination. For substantiated cases, the clinical course of myocarditis related to COVID-19 or mRNA vaccination appears mild and self-limiting, with reports of severe/fulminant myocarditis being rare. There is limited data available on the management of myocarditis in these settings. Clinical guidance for appropriate use of cardiac investigations and monitoring in COVID-19 is needed for effective risk stratification and efficient use of cardiac resources in Australia. An amalgamation of national and international position statements and guidelines is helpful for guiding clinical practice. This paper reviews the current available evidence and guidelines and provides a summary of the risks and potential use of cardiac investigations and monitoring for patients with COVID-19. [ABSTRACT FROM AUTHOR]

The COVID-19 disease continues to cause unparalleled disruption to life and the economy world over. This paper is the second in what will be an ongoing series of analyses of a longitudinal travel and activity survey. In this paper we examine data collected over a period of late May to early June in Australia, following four-to-six weeks of relatively flat new cases in COVID-19 after the initial nationwide outbreak, as many state jurisdictions have begun to slowly ease restrictions designed to limit the spread of the SARS-CoV-2 virus. We find that during this period, travel activity has started to slowly return, in particular by private car, and in particular for the purposes of shopping and social or recreational activities. Respondents indicate comfort with the idea of meeting friends or returning to shops, so authorities need to be aware of potential erosion of social distancing and appropriate COVID-safe behaviour in this regard. There is still a concern about using public transport, though it has diminished noticeably since the first wave of data collection. We see that working from home continues to be an important strategy in reducing travel and pressure on constrained transport networks, and a policy measure that if carried over to a post-pandemic world, will be an important step towards a more sustainable transport future. We find that work from home has been a generally positive experience with a significant number of respondents liking to work from home moving forward, with varying degrees of employer support, at a level above those seen before COVID-19. Thus, any investment to capitalise on current levels of work from home should be viewed as an investment in transport. • Aggregate travel has increased by 50% but is still less than two-thirds of that which occurred prior to COVID-19. • Motor vehicle travel rebounding more than other modes, those planning a return to train and bus intended to do so strongly. • Large increases in activity planned for shopping and social and recreation purposes. • People feel most comfortable with meeting with friends, going to the shops and visiting restaurants. • Working from home continues, and has been largely positive for those who have been able to do so.. • Concern about the risk of COVID-19 has decreased significantly since the initial outbreak. [ABSTRACT FROM AUTHOR]

The novel coronavirus disease 2019 (COVID-19) epidemic that emerged in December 2019 has rapidly evolved in recent months to become a worldwide and ongoing pandemic. Shortage of medical masks remains an unresolved problem. This study aims to investigate the filtration efficiency (FE) of home-made masks that could be used as alternatives for community mitigation of COVID-19. Experimental observational analytic study. The FE of home-made masks and medical masks (as the control) were tested under laminar flow within a scaled air duct system using nebulised NaCl aerosols sized 6–220 nm. The size-resolved NaCl aerosol count was measured using a scanning mobility particle-sizer spectrometer. Home-made masks with an external plastic face shield also underwent a splash test. In addition, the fibre structures of medical masks were studied under an electron microscope after treatment with either 75% alcohol or soap and water at 60 °C. The FE of the home-made masks at 6–200 nm were non-inferior to that of medical masks (84.54% vs 86.94%, P = 0.102). Both types of masks achieved an FE of 90% at 6–89 nm. A significantly higher FE was achieved when one piece of tissue paper was added adjacent to the inner surface of the medical mask than medical mask alone (6–200 nm: 91.64% vs 86.94%, P < 0.0001; 6–89 nm: 94.27% vs 90.54%, P < 0.0001; 90–200 nm: 82.69% vs 73.81%, P < 0.0001). The plastic face shield prevented the home-made mask from fluid splash. The fibre structures of the external surface of medical masks were damaged after treatment with either 75% alcohol or soap and water at 60 °C. The home-made masks in this study, which were made of one piece of tissue paper and two pieces of kitchen towels, layered from face to external, had an FE at 6–200 nm non-inferior to that of medical mask materials, which had a certified FE of ≥95% at 3 μm. In the current COVID-19 pandemic with the shortage of medical masks, these home-made masks combined with an external plastic shield could be used as an alternative to medical masks for community mitigation. In addition, one piece of tissue paper could be placed adjacent to the inner surface of a medical mask to prolong effective lifespan of the medical mask. These demand reduction strategies could be used to reserve medical masks for use in healthcare and certain high-risk community settings, such as symptomatic persons, caregivers and attendees to healthcare institutions. • Our home-made masks have filtration efficiency comparable to medical masks. • They may be used as alternatives in low-risk community settings. • Plastic face shields may be used in situations when social distancing and/or face masks are not feasible. • Decontamination of medical masks with 75% alcohol or soap and water damages the fibres and is not recommended. • Community mitigation measures are an important part of the global efforts in combating COVID-19. [ABSTRACT FROM AUTHOR]

Maybe 2021 wasn't so bad after all! It was like 2020, but with COVID vaccines and better access to plastic pipette tips, and clearly, 2022 is getting off to a bad start. Even better, 2021 had some exciting papers in clinical microbiology, which is what is highlighted in this 2021 year in review. None of them are about COVID-19. Of course, there were some interesting discoveries about SARS-CoV-2 and COVID-19, but this review is completely COVID-19 free (almost). [ABSTRACT FROM AUTHOR]

Various unexpected, low-probability events can have short or long-term effects on organizations and the global economy. Hence there is a need for appropriate risk management practices within organizations to increase their readiness and resiliency, especially if an event may lead to a series of irreversible consequences. One of the main aspects of risk management is to analyze the levels of change and risk in critical variables which the organization's survival depends on. In these cases, an awareness of risks provides a practical plan for organizational managers to reduce/avoid them. Various risk analysis methods aim at analyzing the interactions of multiple risk factors within a specific problem. This paper develops a new method of variability and risk analysis, termed R.Graph, to examine the effects of a chain of possible risk factors on multiple variables. Additionally, different configurations of risk analysis are modeled, including acceptable risk, analysis of maximum and minimum risks, factor importance, and sensitivity analysis. This new method's effectiveness is evaluated via a practical analysis of the economic consequences of new Coronavirus in the electricity industry. [ABSTRACT FROM AUTHOR]

The novel coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has caused a global pandemic in the last year. Along with major respiratory distress, a myriad of neurological manifestations was also reported to be associated with COVID-19 patients. These cases indicate that SARS-CoV-2 can be considered as an opportunistic pathogen of the brain. SARS-CoV-2 enters the brain through the olfactory bulb, retrograde axonal transport from peripheral nerve endings, or via hematogenous or lymphatic routes. Notably, COVID-19 infection can cause or even present with different neurological features including encephalopathy, impaired consciousness, confusion, agitation, seizure, ataxia, headache, anosmia, ageusia, neuropathies, and neurodegenerative diseases. In this paper, we provide a brief review of observed neurological manifestations associated with COVID-19. [ABSTRACT FROM AUTHOR]

• Developing a time-fractional compartmental model that incorporates the effect of contact tracing for Covid-19. • Describe the effective reproduction number in terms of observable quantities. • Discuss effects of tracking, reporting and monitoring in contact tracing. • Monitoring proportion of reported cases which must be tracked to ensure that the reproduction number is below one. • Numerical simulations are done to discuss the impact of contact tracing on the pandemic. Contact Tracing (CT) is one of the measures taken by government and health officials to reduce the spread of the novel coronavirus. In this paper, we investigate its efficacy by developing a compartmental model for assessing its impact on mitigating the spread of the virus. We describe the impact on the reproduction number R 0 of COVID-19. In particular, we discuss the importance and relevance of parameters of the model such as the number of reported cases, effectiveness of tracking and monitoring policy, and the transmission rates to contact tracing. We describe the terms "perfect tracking", "perfect monitoring" and "perfect reporting" to indicate that traced contacts will be tracked while incubating, tracked contacts are efficiently monitored so that they do not cause secondary infections, and all infected persons are reported, respectively. We consider three special scenarios: (1) perfect monitoring and perfect tracking of contacts of a reported case, (2) perfect reporting of cases and perfect monitoring of tracked reported cases and (3) perfect reporting and perfect tracking of contacts of reported cases. Furthermore, we gave a lower bound on the proportion of contacts to be traced to ensure that the effective reproduction, R c , is below one and describe R c in terms of observable quantities such as the proportion of reported and traced cases. Model simulations using the COVID-19 data obtained from John Hopkins University for some selected states in the US suggest that even late intervention of CT may reasonably reduce the transmission of COVID-19 and reduce peak hospitalizations and deaths. In particular, our findings suggest that effective monitoring policy of tracked cases and tracking of traced contacts while incubating are more crucial than tracing more contacts. The use of CT coupled with other measures such as social distancing, use of face mask, self-isolation or quarantine and lockdowns will greatly reduce the spread of the epidemic as well as peak hospitalizations and total deaths. [ABSTRACT FROM AUTHOR]

Nucleocapsid protein (N protein) is the primary antigen of the virus for development of sensitive diagnostic assays of COVID-19. In this paper, we demonstrate the significant impact of dimerization of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) N-protein on sensitivity of enzyme-linked immunosorbent assay (ELISA) based diagnostics. The expressed purified protein from E. coli is composed of dimeric and monomeric forms, which have been further characterized using biophysical and immunological techniques. Indirect ELISA indicated elevated susceptibility of the dimeric form of the nucleocapsid protein for identification of protein-specific monoclonal antibody as compared to the monomeric form. This finding also confirmed with the modelled structure of monomeric and dimeric nucleocapsid protein via HHPred software and its solvent accessible surface area, which indicates higher stability and antigenicity of the dimeric type as compared to the monomeric form. The sensitivity and specificity of the ELISA at 95% CI are 99.0% (94.5–99.9) and 95.0% (83.0–99.4), respectively, for the highest purified dimeric form of the N protein. As a result, using the highest purified dimeric form will improve the sensitivity of the current nucleocapsid-dependent ELISA for COVID-19 diagnosis, and manufacturers should monitor and maintain the monomer-dimer composition for accurate and robust diagnostics. [Display omitted] [ABSTRACT FROM AUTHOR]

Various unexpected, low-probability events can have short or long-term effects on organizations and the global economy. Hence there is a need for appropriate risk management practices within organizations to increase their readiness and resiliency, especially if an event may lead to a series of irreversible consequences. One of the main aspects of risk management is to analyze the levels of change and risk in critical variables which the organization's survival depends on. In these cases, an awareness of risks provides a practical plan for organizational managers to reduce/avoid them. Various risk analysis methods aim at analyzing the interactions of multiple risk factors within a specific problem. This paper develops a new method of variability and risk analysis, termed R.Graph, to examine the effects of a chain of possible risk factors on multiple variables. Additionally, different configurations of risk analysis are modeled, including acceptable risk, analysis of maximum and minimum risks, factor importance, and sensitivity analysis. This new method's effectiveness is evaluated via a practical analysis of the economic consequences of new Coronavirus in the electricity industry. [ABSTRACT FROM AUTHOR]

Airborne transmissibility of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has highlighted the urgent need for aerosol monitoring of SARS-CoV-2 to prevent sporadic outbreaks of COVID-19. The inadequate sensitivity of conventional methods and the lack of an on-site detection system limited the practical SARS-CoV-2 monitoring of aerosols in public spaces. We have developed a novel SARS-CoV-2-in-aerosol monitoring system (SIAMs) which consists of multiple portable cyclone samplers for collecting aerosols from several venues and a sensitive "sample-to-answer" microsystem employing an integrated cartridge for the analysis of SARS-CoV-2 in aerosols (iCASA) near the sampling site. By seamlessly combining viral RNA extraction based on a chitosan-modified quartz filter and " in situ " tetra-primer recombinase polymerase amplification (tpRPA) into an integrated microfluidic cartridge, iCASA can provide an ultra-high sensitivity of 20 copies/mL, which is nearly one order of magnitude greater than that of the commercial kit, and a short turnaround time of 25 min. By testing various clinical samples of nasopharyngeal swabs, saliva, and exhaled breath condensates obtained from 23 COVID-19 patients, we demonstrate that the positive rate of our system was 3.3 times higher than those of the conventional method. Combining with multiple portable cyclone samplers, we detected 52.2% (12/23) of the aerosol samples, six times higher than that of the commercial kit, collected from the isolation wards of COVID-19 patients, demonstrating the excellent performance of our system for SARS-CoV-2-in-aerosol monitoring. We envision the broad application of our microsystem in aerosol monitoring for fighting the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

Based on the discrete model of infection spread in a closed population, appearance of epidemic waves associated with strengthening and weakening quarantine measures in the present paper is shown. The effect of quarantine measures is considered in the model under consideration via time dependence in the infection transmission rate. It was shown that the epidemic development is controlled by four key parameters: the number of infected persons, the average virus carriage time (as applied to COVID-19-type epidemics caused by the virus SARS-CoV-2 spread), the average number of dangerous contacts (which can cause virus transfer from an infected person to healthy men) of one infectious person (virus carrier) per day and the probability of infection due to a hazardous contact. The two latter parameters enter the model only as a product called the indicator of infection growth (IG) in population. The found solutions depend also on the population size and on the initial number of infected persons. The IG in the model under consideration is similar in meaning to the reproductive number in continuous SIR and SEIR models. At the same time, due to the prolonged virus carriage characteristic of COVID-19, the solutions proposed here are based on the equations with delay, and even without temporal variations of the IG, differ significantly from the SIR and SEIR models. The effect of the feedback between the epidemic spread rate and variations in the IG, caused by strengthening or weakening quarantine measures is studied. It results in a principal change in the epidemic behavior, which not reaching the saturation mode, transforms to its wavy flow mode. The dependence of the onset of epidemic waves on characteristic times of quarantine restriction weakening was revealed. In the model under consideration, the possibility of complete epidemic end in the case of long-term restricted quarantine measures was shown. The possible existence of the quasi-steady mode of low-intensity epidemic was detected. In this mode, the number of virus carriers remains unchanged for a long time due to the balance of the number of infections and recoveries per day. • Based on the discrete model of infection spread in a closed population, appearance of epidemic waves associated with strengthening and weakening quarantine measures was shown. The effect of quarantine measures is considered in the model under consideration via time dependence in the infection transmission rate. • The epidemic development is controlled by the parameters: the number of infected persons, the average virus carriage time, the average number of dangerous contacts of one virus carrier per day and the probability of infection due to a hazardous contact. • The found solutions depend also on the population size and on the initial number of infected persons. The infection growth parameter IG in the model under consideration is similar in meaning to the reproductive number in continuous SIR and SEIR models. At the same time, due to the prolonged virus carriage characteristic of COVID-19, the solutions proposed here are based on the equations with delay, and even without temporal variations of the IG, differ significantly from the SIR and SEIR models. • The effect of the feedback between the epidemic spread rate and variations in the IG, caused by strengthening or weakening quarantine measures is studied. It results in a principal change in the epidemic behavior, which not reaching the saturation mode, transforms to its wavy flow mode. In the model under consideration, the possibility of complete epidemic end in the case of long-term restricted quarantine measures was shown. • The possible existence of the quasi-steady mode of low-intensity epidemic was detected. In this mode, the number of virus carriers remains unchanged for a long time due to the balance of the number of infections and recoveries per day. [ABSTRACT FROM AUTHOR]

In recent years, the new coronavirus COVID-19 has brought great disaster and loss to the world and is still spreading around the world. The situation in China is generally well controlled, and the lockdown has been removed, but the comments and messages about the epidemic persist online. For people working and living normally in China, their attitudes and views toward COVID-19 directly reflect the current situation of the pandemic. This paper collected Chinese microblogs, forums, and online comments, identified the latest comments about COVID-19, and conducted a sentiment analysis of them. Specifically, we proposed a new sentiment analysis method that integrated the semantics of words with the text analyzed. Different from the traditional sentiment analysis method which only relied on sentiment words, the proposed method extended the semantic concepts of affective words by integrating the semantic conceptual information about the affective words from the context of the comments and thus, provided information to support the final judgment of the affective opinions. The proposed approach incorporated the part-of-speech embedding information along with word embedding and relies on semantic concepts to enhance the emotional expression of words in context. The experimental results showed that by integrating the semantics of words, the accuracy of sentiment analysis is substantially improved, and it also reflected that different semantics of the same word have different influences on sentiment analysis. On several benchmark datasets, there was a 3–6% improvement in accuracy. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic's profound impact on global health and the economy underscores the need for new computational strategies to rapidly identify potential antiviral drugs against emerging and re-emerging infectious diseases. AI-based drug repurposing methods have the potential to significantly shorten the drug discovery process, rendering them a crucial and efficacious approach for screening anti-SARS-CoV-2 compounds. In this paper, we proposed GINCM-DTA, an AI-based graph isomorphism network with protein contact map representation for drug–target affinity (DTA) prediction, and presented the COVID-DTA dataset for SARS-CoV-2-specific drug repurposing. Pre-training GINCM-DTA on large-scale Davis and KIBA datasets achieved state-of-the-art performance, while fine-tuning on the COVID-DTA dataset using transfer learning resulted in a mean square error of 0.026 and concordance index of 0.967. Utilizing the fine-tuned GINCM-DTA model, we predicted DTAs for drugs against SARS-CoV-2 main targets, focusing on key conserved proteins and unmutated spike proteins for virtual screening. We integrated GINCM-DTA predictions with molecular docking simulations to identify five candidates. In vitro assays revealed Hydralazine (5.737 nM) as a potential inhibitor of ACE2 and TMPRSS2, effectively blocking SARS-CoV-2 infection. Moreover, the results highlight the potential of Hydralazine as a broad-spectrum drug candidate, demonstrating its efficacy in obstructing the binding between ACE2 and spike proteins of multiple Omicron variants, including the currently dominant strains BQ.1, BQ.1.1, XBB.1.5, and XBB.1.16. Our method offers a novel computational strategy for COVID-19 antiviral screening and prepares for potential future epidemics incited by emerging viruses. • Proposed GINCM-DTA: a novel GIN model for DTA prediction with SOTA performance. • The fine-tuned GINCM-DTA achieved excellent performance: MSE=0.026, CI=0.967. • Identified Hydralazine as a potential inhibitor to block SARS-CoV-2 infection. • Potential effective against Omicron subvariants: BQ.1, BQ.1.1, XBB.1.5, XBB.1.16. • New computational strategy for COVID-19 antiviral screening & future virus epidemics. [ABSTRACT FROM AUTHOR]

Introduction: The COVID-19 (coronavirus disease 2019)-related pandemic represents a global source of societal and health burden. Yet, the impact of the pandemic on people with severe mental illness, including bipolar disorder (BD), remains unclear, warranting scoping review on the matter.Methods: The MEDLINE and EMBASE databases were systematically searched from inception up to April 24, 2021, adopting broad inclusion criteria to assess a variety of clinical and public health themes related to people with a primary diagnosis of BD during the COVID-19 pandemics. The present work complying with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews (PRISMA-ScR) registered in the Open Science Framework (OSF) repository (https://osf.io/7evpx/).Results: Fourteen papers informed the present scoping review. Four major themes were identified: (i) impact of COVID-19-related stressors on BD; (ii) impact of COVID-19 on mental health service utilization among people with BD; (iii) impact of BD on the risk of acquiring SARS-CoV-2 infection; (iv) engagement in preventative behaviors among people with BD. Additional themes warranting further research were nonetheless detected.Limitations: Further original studies are needed.Conclusion: The present study confirmed the high-vulnerability hypothesis concerning people with BD versus the general population, reinforcing the need for further research related to the COVID-19 pandemic. Additional information is warranted to compare the impact of the pandemic period among BD people against pre-pandemic records, the general population, and other severe mental illnesses, namely people with schizophrenia or major depressive disorder, to inform the public health and the delivery of patient-tailored interventions. [ABSTRACT FROM AUTHOR]

• Prophet Model provides understanding of the number of people affected daily by this disease. • The imposed interventions are reflected by five significant changepoints detected by the model in the growth curve of India. • The model forecasts90 days future growth trend and finds the peak time for all the six countries and six states of India. • The model has achieved around 85% MAPE for all the six countries and the six states of India. Covid-19 disease caused by novel coronavirus (SARS-CoV-2) is a highly contagious epidemic that originated in Wuhan, Hubei Province of China in late December 2019. World Health Organization (WHO) declared Covid-19 as a pandemic on 12th March 2020. Researchers and policy makers are designing strategies to control the pandemic in order to minimize its impact on human health and economy round the clock. The SARS-CoV-2 virus transmits mostly through respiratory droplets and through contaminated surfacesin human body.Securing an appropriate level of safety during the pandemic situation is a highly problematic issue which resulted from the transportation sector which has been hit hard by COVID-19. This paper focuses on developing an intelligent computing model for forecasting the outbreak of COVID-19. The Facebook Prophet model predicts 90 days future values including the peak date of the confirmed cases of COVID-19 for six worst hit countries of the world including India and six high incidence states of India. The model also identifies five significant changepoints in the growth curve of confirmed cases of India which indicate the impact of the interventions imposed by Government of India on the growth rate of the infection. The goodness-of-fit of the model measures 85% MAPE for all six countries and all six states of India. The above computational analysis may be able to throw some light on planning and management of healthcare system and infrastructure. [Display omitted] [ABSTRACT FROM AUTHOR]

• Ventilation air is important in our lifestyle and improve the human health. • Using 100% fresh air of A/C systems leads to the protection of COVID-19. • The enclitic air can carry suspended particles of the COVID-19 for hours. • Improper use of filters leads to the spread of the bacterial and viruses' indoor environment. • Important recommendations are extracted to face the spread of the COVID-19 pandemic. The Coronavirus disease (COVID-19) has spread over the world, resulting in more than 225 million patients, and 4.7 million deaths in September 2021. It also caused panic and terror, halted numerous activities, and resulted in the world economy deteriorates. It altered human behavior and compelled people to alter their lifestyles to avoid infection. Air conditioning systems are one of the most important sectors that must be considered because of the pandemic SARS-CoV-2 all over the world. Air is used as a heat transfer medium in heating, ventilation, and air conditioning (HVAC) systems. The air contains a variety of pollutants, viruses, and bacteria, all of which have an impact on and destroy human life. Significantly in summer, people spend more time in air conditioners which results in lower levels of vitamin D and melatonin which may affect the functioning of their immune system and are susceptible to receiving SARS-CoV-2 from other individuals. As an important component of air conditioning and ventilation systems, the air filter plays a significant role. As a result, researchers must work harder to improve its design to prevent the ultra-small particles loaded with COVID-19. This paper contributes to the design of existing HVAC systems in terms of their suitability and impact on the spread of the hybrid SARS-CoV-2 epidemic, as well as efforts to obtain a highly efficient air filter to remove super-sized particles for protection against epidemic infection. In addition, important guideline recommendations have been extracted to limit the spread of the SARS-CoV-2 throughout the world and to get the highest quality indoor air in air-conditioned places. [ABSTRACT FROM AUTHOR]