Surfaces as a Source for SARS-CoV-2 Transmission

The role of contaminated surfaces as a potential source for SARS-CoV-2 transmission has not been clear at the beginning of the pandemic. Numerous laboratory studies show that SARS-CoV-2 can remain infectious at room temperature on different types of surfaces for a few days and substantially longer in the dark. A higher temperature such as 30 °C or 40 °C and a higher relative humidity result in a shorter persistence. On surfaces in the surrounding of confirmed COVID-19 patients the detection rates of SARS-CoV-2 RNA were mostly less than 30% with Ct-values mostly >30 suggesting a low viral load and the absence of infectious SARS-CoV-2. The RNA detection rates on public surfaces were low with 0-22.1%, the corresponding Ct values were mostly >30. Infectious SARS-CoV-2 was only detected in 2 of 11 studies in the immediate surrounding of COVID-19 patients with 0.7% or 10.5% of the samples being positive. A major limitation of the results, however, is that in one study 7 of 8 positive samples were obtained in the surrounding of only one patient with persistent cough and frequent sputum spitting during sampling. Overall, the probability of surfaces to be the source of SARS-CoV-2 transmission is low, especially for public surfaces. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.

Optimization of Contactless Distribution in the Post-COVID Era

During an emergency, timely and effective distribution of emergency supplies is critical in rescue. In the context of Covid-19, given the difficulties in distributing supplies to communities due to super infectious viruses, unmanned vehicle distribution is studied by taking into account the priority and satisfaction of communities to improve distribution safety and effectiveness of supplies. Furthermore, the influence of distribution time on the overall efficiency is also taken into account, thus ultimately establishing an unmanned distribution model with the shortest distribution time while meeting community satisfaction. The improved whale algorithm is used to solve the dual-objective model and compared with the basic whale optimization algorithm. The results show that the improved whale algorithm demonstrates better convergence, searchability, and stability. The constructed model can scientifically distribute daily necessities to communities while considering their priority and satisfaction. © 2022 IEEE.

Research and Application of 5G Edge AI in Medical Industry

With the development of 5G and AI technology, the infectious virus detection framework system based on the combination of 5G MEC and medical sensors can effectively assist in the intelligent detection and control of influenza viruses such as COVID-19. Employing the edge computing and 5G+MEC model, the virus AI model is trained for the collected influenza virus data. Then the virus AI model can be used to evaluate the virus patients on the local edge computing service platform. Therefore, this paper introduces an algorithm and resource allocation, which uses 5G functions (especially, low latency, high bandwidth, wide connectivity, and other functions) to achieve local chest X-ray or CT scan images to detect COVID-19. Meanwhile, this paper also compares the computational efficiency of different algorithms in the 5G edge AI-based infectious virus detection framework, in this way to select the best algorithm and resource allocation. © 2022 IEEE.

A novel isothermal digital amplification system and its application for absolute quantification of respiratory infectious virus

Herein, we establish a novel isothermal digital amplification system termed digital nicking and extension chain reaction system-based amplification (dNESBA) by utilizing the isothermal NESBA technique and the newly developed miniaturized fluorescence monitoring system (mFMS). dNESBA enables parallel isothermal NESBA reactions in more than 10,000 localized droplet microreactors and read the fluorescence signals rapidly in 150 s by mFMS. This system could identify the genomic RNA (gRNA) extracted from target respiratory syncytial virus A (RSV A) as low as 10 copies with remarkable specificity. The practical applicability of dNESBA was also successfully verified by reliably detecting the gRNA in the artificial sputum samples with excellent reproducibility and accuracy. Due to the intrinsic advantages of isothermal amplifying technique including the elimination of the requirement of thermocycling device and the enhanced portability of the miniaturized read-out equipment, the dNESBA technique equipped with mFMS could serve as a promising platform system to achieve point-of-care (POC) digital molecular diagnostics, enabling absolute and ultra-sensitive quantification of various infectious pathogens even in an early stage.Copyright © 2023

COVID-19 Future Forecasting Using Machine Learning Models

Covid-19 is a very infectious virus. According to World Health Organization (WHO), millions of individuals have been diagnosed with Covid-19 since then, and at least a million have died as the virus has expanded dramatically. While most of the news on this front is scary, technology is helping to pave the path through this crisis. Manual forecasting is a difficult challenge for humans due to its large scale and complexity. Machine Learning (ML) techniques can effectively predict Covid-19 infected patients. There are a lot of study that have been developed to predict and forecast the future number of cases affected by Covid-19. In this area, our forecasting can be tackled as a problem of supervised learning. Supervised ML is very popular regression methods due to its simplicity to be interpreted by Humans. In this paper, we use two datasets to predict the symptoms through two different types of regression algorithms (single and multiple regression), the ML algorithms are LR, SVM, LASSO, ES and Polynomial regression, for the multiple regression we used LR, SVM and LASSO. The obtained results validate that for the single regression the Exponential Smoothing (ES) outperforms other machine learning approaches like Linear Regression (LR) and LASSO in terms of R-Square, Adjusted R-Square, Mean Absolute Error (MAE), Mean Square Error (MSE), and Root Mean Square Error (RMSE). The same accuracy is observed for the models used in the multiple regression. © 2022 IEEE.

Persistent SARS-CoV-2 infection with accumulation of mutations in a patient with poorly controlled HIV infection.

A 22-year-old female with uncontrolled advanced HIV infection was persistently infected with SARS-CoV-2 beta variant for 9 months, the virus accumulating >20 additional mutations. Antiretroviral therapy suppressed HIV and cleared SARS-CoV-2 within 6-9 weeks. Increased vigilance is warranted to benefit affected individuals and prevent the emergence of novel SARS-CoV-2 variants.

Multi-Criteria Recommender System for Determining Risk Level of Covid-19

The coronavirus pandemic is a global disease outbreak causing countless loss of lives and also threatening the economic, social, religious, education, and other key sectors of nations. This highly infectious virus continues to spread rapidly and therefore, the need to develop innovative strategies and policies to curb the growing effects becomes very crucial. One significant approach is the introduction of lockdown measures, although this instrument is not completely dependable, due to possible adverse effects on societal activities. Prior to deployment, a number of criteria are taken into account, including demographic conditions, healthcare options, and Covid-19 case data. Depending on the influencing factors, a lockdown decision is typically made by assessing the different danger levels of a certain place. Consequently, this research propose a multi-criteria recommender system to determine the worth and risk of various regions, based on several constraints and databases. The model, which utilized the analytical network process (ANP) to discover interconnectedness and feedback, also included the weighting technique. In this study carried out in 27 districts and cities in West Java, Indonesia, 15% of the selected locations were categorized as high-risk levels. Meanwhile, 63% and 22% were associated with medium and low risk, respectively. © 2022 IEEE.

DESIGN OPTIMIZATION OF MICROFLUIDIC DIAGNOSTIC DEVICES FOR THE RAPID GENETIC DETECTION OF MULTIPLE INFECTIOUS VIRUSES

This paper presents a newly developed microfluidic flow control theory for autonomous sample dispensing into an array of reaction microchambers. The theoretical predictions for the possible dispensing number and maximum flow rate were validated by comparison to experimental results. Moreover, we successfully demonstrated the rapid genetic detection of multiple infectious viruses including SARS-CoV-2 in fabricated polydimethylsiloxane (PDMS)-based microfluidic devices based on the loop-mediated isothermal amplification (LAMP) method. © 2021 MicroTAS 2021 - 25th International Conference on Miniaturized Systems for Chemistry and Life Sciences. All rights reserved.

Production of single-cycle infectious SARS-CoV-2 through a trans-complemented replicon.

Single-cycle infectious virus can elicit close-to-natural immune response and memory. One approach to generate single-cycle severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is through deletion of structural genes such as spike (S) and nucleocapsid (N). Transcomplementation of the resulting ΔS or ΔN virus through enforced expression of S or N protein in the cells gives rise to a live but unproductive virus. In this study, ΔS and ΔN BAC clones were constructed and their live virions were rescued by transient expression of S and N proteins from the ancestral and the Omicron strains. ΔS and ΔN virions were visualized by transmission electron microscopy. Virion production of ΔS was more efficient than that of ΔN. The coated S protein from ΔS was delivered to infected cells in which the expression of N protein was also robust. In contrast, expression of neither S nor N was detected in ΔN-infected cells. ΔS underwent viral RNA replication, induced type I interferon (IFN) response, but did not form plaques. Despite RNA replication in cells, ΔS infection did not produce viral progeny in culture supernatant. Interestingly, viral RNA replication was not further enhanced upon overexpression of S protein. Taken together, our work provides a versatile platform for development of single-cycle vaccines for SARS-CoV-2.

Mental Health During Covid-19 Pandemic

The outburst of coronavirus in December 2019 from Wuhan, China leads to the global COVID-19 pandemic. COVID-19 was declared as a pandemic by WHO at the beginning of 2020. This resulted in lockdown in many countries, as a preventive measure. Due to the lockdown, people were forced to stay at home, which increased the feeling of loneliness, anxiety, depression, or suicidal thoughts. Mental health is the least discussed topic but most important. With the outbreak of the highly infectious virus, public fear, anxiety, stress due to lethality, uncertainty also follows. This review article is aimed to explore the impact of the COVID-19 pandemic on the mental health of individuals and groups of individuals. A twenty percent increase in mental illnesses was reported in a survey by the Indian Psychiatric Society, since the coronavirus outbreak in India. In China, a study showed 16.5% moderate to severe depressive symptoms;28.8% moderate to severe anxiety symptoms;8.1% moderate to severe stress due to COVID -19. Different countries all over the world showed similar statistics. CONCLUSION: The COVID-19 pandemic had probably been the greatest pandemic in modernized human history. To prevent the transmission of coronavirus, the lockdown was imposed, which forced everyone to stay at home. The isolation had an adverse effect on the mental health of individuals.. The mental health of females of all age groups was more adversely affected than the males. Older people were more prone to mental illness, as compared to youngers. Students lacked interest in studies and their motivation to study was decreased. Health care professions were in the most important position during the entire pandemic, however, they weren't resistant to anxiety, stress, or depression. © The Electrochemical Society

Prediction of COVID 19- Chest Image Classification and Detection using RELM Classifier in Machine Learning

This novel coronavirus (CoV) is known as 'SARS-CoV2' or '2019 novel coronavirus' or 'COVID-19' by the WHO. It is started at the end of 2019 in China. It is the outbreak of pneumonia related to chest issues. COVID-19 is an infectious virus. As COVID-19 is a contiguous disease, early detection is more important. It can be incurable if the virus is detected later. The identification of COVID-19 disease is done by collecting samples from the throat and nose. Sometimes when the patient is more severe, that time they are asked to take a chest X-Ray. This research proposed a system for the identification of the virus utilizing X-Ray images. Dataset used consists of both Covid and Normal X-ray images. In this research, we used the ResNet50 model to predict the disease. It contains 48 convolutional layers, one MaxPool, and Average Pool layers. 'RELM' is a suitable classifier, and it gave better accuracy than other classifiers. This research can be practically helpful to the physicians with the usage of datasets for the successful diagnosis of pandemic disease (COVID-19) in the healthcare field. We built the RELM classifiers with convolution Neural Network as our contribution in this research. © 2022 IEEE.

Vaccine Awareness and Enhancing Networked Healthcare System Across the Globe

Immunisation is the procedure of providing a vaccine to a person in order to protect him or her against disease. This process has been widely recognized and adopted as one of the world's most successful and cost-effective health interventions. Vaccines have been saving millions of lives worldwide from deadly infectious diseases and viruses, such as hepatitis, measles and polio. However, the COVID outbreak in the late 2019 has witnessed huge devastation on the global health front. For now, vaccine is the only cost-effective health intervention to control the spread of virus and completely eradicating it. Technological breakthroughs are making a significant contribution to the improvement of healthcare. Blockchain technology is one example of such a disruptive technology. Blockchains have the potential to improve the healthcare system in a variety of ways. In this paper, we have thoroughly discussed how we can create vaccine awareness across the globe by focusing on parents, healthcare workers, frontline workers, policymakers, media, and ultimately how everyone must work together to ensure that every individual in every country gets the vaccine. We also discussed how blockchain technology may be applied to many sectors of healthcare and the benefits it can provide in terms of enhancing global network healthcare systems. © 2022 IEEE.

Modeling Influenza with a Forest Deep Neural Network Utilizing a Virtualized Clinical Semantic Network

CoViD-19 pandemic has shown that we have deep gaps in understanding this extremely infectious virus - not only both from a clinical diagnosis and treatment perspective - but also from a forecasting point of view, so that we are better prepared for the next onset of a similar pandemic, which, at this point, seems almost inevitable. In this paper, we present a novel approach towards modeling influenza, a closely related disease to CoViD-19, marrying clinical understanding with artificial intelligence, exploiting the Forest Deep Neural Network (fDNN) with accuracy rates in the 90% range. © 2021 IEEE.

Infectious Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Virus in Symptomatic Coronavirus Disease 2019 (COVID-19) Outpatients: Host, Disease, and Viral Correlates.

BACKGROUND: Although severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infectious virus isolation in outpatients with coronavirus disease 2019 (COVID-19) has been associated with viral RNA levels and symptom duration, little is known about the host, disease, and viral determinants of infectious virus detection. METHODS: COVID-19 adult outpatients were enrolled within 7 days of symptom onset. Clinical symptoms were recorded via patient diary. Nasopharyngeal swabs were collected to quantitate SARS-CoV-2 RNA by reverse transcriptase polymerase chain reaction and for infectious virus isolation in Vero E6-cells. SARS-CoV-2 antibodies were measured in serum using a validated ELISA assay. RESULTS: Among 204 participants with mild-to-moderate symptomatic COVID-19, the median nasopharyngeal viral RNA was 6.5 (interquartile range [IQR] 4.7-7.6 log10 copies/mL), and 26% had detectable SARS-CoV-2 antibodies (immunoglobulin (Ig)A, IgM, IgG, and/or total Ig) at baseline. Infectious virus was recovered in 7% of participants with SARS-CoV-2 antibodies compared to 58% of participants without antibodies (prevalence ratio [PR] = 0.12, 95% confidence interval [CI]: .04, .36; P = .00016). Infectious virus isolation was also associated with higher levels of viral RNA (mean RNA difference +2.6 log10, 95% CI: 2.2, 3.0; P < .0001) and fewer days since symptom onset (PR = 0.79, 95% CI: .71, .88 per day; P < .0001). CONCLUSIONS: The presence of SARS-CoV-2 antibodies is strongly associated with clearance of infectious virus. Seropositivity and viral RNA levels are likely more reliable markers of infectious virus clearance than subjective measure of COVID-19 symptom duration. Virus-targeted treatment and prevention strategies should be administered as early as possible and ideally before seroconversion. CLINICAL TRIALS REGISTRATION: NCT04405570.

A Numerical Study on Indoor Air Quality (IAQ) Designs for Hospital Waiting Room in the Context of COVID-19 for Hot and Warm Humidity Climate

COVID-19 is a virus originated from Corona Virus which can severe acute respiratory syndrome (SARS) symptoms such as chest pain, dry cough, fever, and difficulty breathing. The AC and ventilation system is not only important for the thermal comfort occupants but to ensure the room is safe and free from infectious virus. Thermal comfort is important measurement in indoor space which influenced by temperature, Relative Humidity (RH), airflow velocity and others. This research was executed and focused on lecture room in Bilik Persatuan 10, Universiti Malaysia Perlis (UniMAP) instead of real hospital waiting room. It comes with the room dimensions 11.87m (Length) x 5.17m (Width) x 2.93m (Height) for the numerical study. In addition, Computational Fluid Dynamics (CFD) analysis is used to investigate the air flow pattern and temperature distribution inside the room. By using software Ansys FLUENT 19, field experimental and simulation work can be compared which have 14.55% difference in temperature distribution. It is expected by increasing the air velocity of the AC inlet diffuser influence the pattern of airflow in the room, but average temperature remains same for all these conditions. © 2021 Institute of Physics Publishing. All rights reserved.

Virucidal effect of monogalactosyl diacylglyceride from a green microalga, Coccomyxa sp. KJ, against clinical isolates of SARS-CoV-2 as assessed by a plaque assay.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of coronavirus disease 2019 (COVID-19) and is capable of human-to-human transmission and rapid global spread. Thus, the establishment of high-quality viral detection and quantification methods, and the development of anti-SARS-CoV-2 agents are critical. METHODS: Here, we present the rapid detection of infectious SARS-CoV-2 particles using a plaque assay with 0.5% agarose-ME (Medium Electroosmosis) as an overlay medium. RESULTS: The plaques were capable of detecting the virus within 36-40 h post-infection. In addition, we showed that a monogalactosyl diacylglyceride isolated from a microalga (Coccomyxa sp. KJ) could inactivate the clinical isolates of SARS-CoV-2 in a time- and concentration-dependent manner. CONCLUSIONS: These results would allow rapid quantification of the infectious virus titers and help develop more potent virucidal agents against SARS-CoV-2.

Postmortem Stability of SARS-CoV-2 in Mouse Lung Tissue.

The infectivity of severe acute respiratory syndrome coronavirus 2 in deceased persons and organisms remains unclear. We studied transgenic K18 hACE2 mice to determine the kinetics of virus infectivity after host death. Five days after death, virus infectivity in the lung declined by >96% and RNA copies declined by 48.2%.

Repeated Coronavirus Disease 2019 Molecular Testing: Correlation of Severe Acute Respiratory Syndrome Coronavirus 2 Culture With Molecular Assays and Cycle Thresholds.

BACKGROUND: Repeated coronavirus disease 2019 (COVID-19) molecular testing can lead to positive test results after negative results and to multiple positive results over time. The association between positive test results and infectious virus is important to quantify. METHODS: A 2-month cohort of retrospective data and consecutively collected specimens from patients with COVID-19 or patients under investigation were used to understand the correlation between prolonged viral RNA positive test results, cycle threshold (Ct) values and growth of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in cell culture. Whole-genome sequencing was used to confirm virus genotype in patients with prolonged viral RNA detection. Droplet digital polymerase chain reaction was used to assess the rate of false-negative COVID-19 diagnostic test results. RESULTS: In 2 months, 29 686 specimens were tested and 2194 patients underwent repeated testing. Virus recovery in cell culture was noted in specimens with a mean Ct value of 18.8 (3.4) for SARS-CoV-2 target genes. Prolonged viral RNA shedding was associated with positive virus growth in culture in specimens collected up to 21 days after the first positive result but mostly in individuals symptomatic at the time of sample collection. Whole-genome sequencing provided evidence the same virus was carried over time. Positive test results following negative results had Ct values >29.5 and were not associated with virus culture. Droplet digital polymerase chain reaction results were positive in 5.6% of negative specimens collected from patients with confirmed or clinically suspected COVID-19. CONCLUSIONS: Low Ct values in SARS-CoV-2 diagnostic tests were associated with virus growth in cell culture. Symptomatic patients with prolonged viral RNA shedding can also be infectious.

Infectivity assay for detection of SARS-CoV-2 in samples from patients with COVID-19.

Since the coronavirus disease 2019 (COVID-19) outbreak, laboratory diagnosis has mainly been conducted using reverse-transcription polymerase chain reaction (RT-PCR). Detecting the presence of an infectious virus in the collected sample is essential to analyze if a person can transmit infectious severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, there have been no quantitative investigations conducted for infectious SARS-CoV-2 in clinical samples. Therefore, in the present study, a rapid and simple focus-forming assay using the peroxidase-antiperoxidase technique was developed to quantify infectious SARS-CoV-2 titers in 119 samples (n = 52, nasopharyngeal swabs [NPS]; n = 67, saliva) from patients with COVID-19. Furthermore, the study findings were compared with the cycle threshold (Ct) values of real-time RT-PCR. The infectious virus titers in NPS samples and Ct values were inversely correlated, and no infectious virus could be detected when the Ct value exceeded 30. In contrast, a low correlation was observed between the infectious virus titers in saliva and Ct values (r = -0.261, p = 0.027). Furthermore, the infectious virus titers in the saliva were significantly lower than those in the NPS samples. Ten days after the onset of COVID-19 symptoms, the infectious virus was undetectable, and Ct values were more than 30 in NSP and saliva samples. The results indicate that patients whose symptoms subsided 10 days after onset, with Ct values more than 30 in NSP and saliva samples, were less likely to infect others.

SARS-CoV-2 rapid antigen test: High sensitivity to detect infectious virus.

BACKGROUND: The COVID-19 pandemic has highlighted the need for rapid, cost effective and easy-to-use diagnostic tools for SARS-CoV-2 infections that can be used in point of care settings to limit disease transmission. OBJECTIVE: We evaluated two rapid antigen immunochromatographic tests, Abbott Panbio™ COVID-19 Ag Rapid Test (Panbio) and Zhejiang Orient Gene/Healgen Biotech Coronavirus Ag rapid test cassette (Orient gene) for detection of infectious SARS-CoV-2. RESULTS: The tests were evaluated on nasopharyngeal samples taken from individuals having respiratory and/or COVID-19 related symptoms, which had been analyzed for SARS-CoV-2 RNA using real-time PCR. In total 156 PCR-positive, and 130 (Panbio) and 176 (Orient Gene) PCR-negative samples were analyzed. Overall sensitivity and specificity were 71.8% and 100% for Panbio and 79.5% and 74.4% for the Orient Gene test respectively. The false positives by the Orient Gene test were verified as SARS-CoV-2 negative by in-house real-time PCR assay and were negative for the four seasonal coronaviruses. Subgroup analysis revealed that the antigen tests had high sensitivity for samples with Ct-values <25 (>88%) and for samples containing infectious viruses as determined by cultivation on Vero cells, 94.1% and 97.1% for the Panbio and Orient gene tests, respectively. Furthermore, both tests had a sensitivity of <50 picogram for nucleocapsid protein. No sample with a Ct-value >27 was shown to contain infectious virus. CONCLUSION: The results indicate that the rapid antigen tests, especially the Panbio tests may be a valuable tool to detect contagious persons during the ongoing pandemic.