Effect of probiotics as an immune modulator for the management of COVID-19.

COVID-19, an acute respiratory viral infection conveyed by pneumonia caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has affected millions of individuals globally, and is a public health emergency of international concern. Till now, there are no highly effective therapies for this infection without vaccination. As they can evolve quickly and cross the strain level easily, these viruses are causing epidemics or pandemics that are allied with more severe clinical diseases. A new approach is needed to improve immunity to confirm the protection against emerging viral infections. Probiotics can modify gut microbial dysbiosis, improve the host immune system, and stimulate immune signaling, increasing systemic immunity. Several probiotic bacterial therapies have been proven to decrease the period of bacterial or viral infections. Superinduction of inflammation, termed cytokine storm, has been directly linked with pneumonia and severe complications of viral respiratory infections. In this case, probiotics as potential immunomodulatory agents can be an appropriate candidate to improve the host's response to respiratory viral infections. During this COVID-19 pandemic, any approach that can induce mucosal and systemic immunity could be helpful. Here, we summarize contexts regarding the effectiveness of various probiotics for preventing virus-induced respiratory infectious diseases, especially those that could be employed for COVID-19 patients. In addition, the effects of probiotics, their mechanisms on different aspects of immune responses against respiratory viral infection, and their antiviral properties in clinical findings have been described in detail.

Eye Detection from Face Images covered in Face-masks using HAAR features

The contagious illness known as COVID-19 made wearing a mask an essential part of daily life. Mask-covered faces cannot be detected by the current eye detection methods. Many biometric identification systems, like iris recognition, depend on accurate eye detection. Thus, in this study, an efficient method using machine learning for detecting eyes of people wearing mask is presented. Haar-cascade classifier is used to implement real-time eye detection from a live stream via webcam. From the live stream, frames are extracted and saved as images. Dataset was prepared by collecting face images of people wearing mask under various background. Haar-cascade classifier which was trained using 2000 positive and 4000 negative images is used to detect the position of eyes. According to the results on dataset, the system could attain an average accuracy of 96.72%. © 2022 IEEE.

A Review of Big Data Analytics on Post-COVID Health Issues

New technology developments and its processes generate large quantities of data every day. Organizations are faced a number of problems for managing these big data. IoT (Internet of Things) devices are now used for collecting data rapidly and safely in high capacity storage devices and internet clouds. Big data has many characteristics including unstructured which does not conform to a data model. In an organization about 85% data is in unstructured format. The semi-structured data does not conform to a data model but it has some structure. The structured data is in an organized form and can be easily used by a computer program. From the year 2019 a new big data formation happened with COVID-19 pandemic in the world society. Corona virus and COVID-19 pandemic have fully affected the people and this pandemic situation has frightened the people worldwide. It has to find excellent big data analytical methods to control and solve the future problems related to this pandemic. This paper presents big data quality dimensions, big data analytics in COVID-19 pandemic, and physical and mental post-COVID health issues. © 2022 IEEE.

In silico screening of potential antiviral inhibitors against SARS-CoV-2 main protease

Respiratory illness due to SARS-CoV-2 emerged in 2019 and has a significant morbidity and mortality rate. The main protease (Mpro) is mainly responsible for viral replications, which acts as a good drug target to inhibit SARS-CoV-2-related diseases. Chemical compounds obtained from various herbal plants are showing potent antiviral activity against numerous viral diseases. Initial screening was performed with the phytochemicals against Mpro using molecular docking. This result shows that there is a strong interaction exhibited between active sites (His-41 and Cys-145) of Mpro with chemical compounds. In addition, ADME prediction and Lipinski's rule of five (RO5) calculations demonstrated that the selected compounds have potential drug-like properties. Further, molecular dynamics (MD) simulations were performed to understand the stability and structural changes of protein–ligand complexes for the top five compounds. MM/PBSA studies strongly suggested that compounds, β-spinasterol, and asarinin form stable complexes with Mpro. The most significant hot spot residues such as Thr-25, Met-49, Cys-145, Met-165, and Gln-189 have strongly interacted with the selected chemical compounds. Our calculations suggest that asarinin is the best inhibitor to the Mpro, which supports these candidates and could be potent antiviral agent against SARS-CoV-2. © 2022 Informa UK Limited, trading as Taylor & Francis Group.

A Highly Sensitive Graphene-based Field Effect Transistor for the Detection of Myoglobin

Biomedical applications adapt Nano technology-based transistors as a key component in the biosensors for diagnosing life threatening diseases like Covid-19, Acute myocardial infarction (AMI), etc. The proposed work introduces a new biosensor, based on Graphene Field Effect Transistor (GFET), which is used in the diagnosis of Myoglobin (Mb) in human blood. Graphene-based biosensors are faster, more precise, stronger, and more trustworthy. A GFET is created in this study for the detection of myoglobin biomarker at various low concentrations. Because graphene is sensitive to a variety of biomarker materials, it can be employed as a gate material. When constructed Graphene FET is applied to myoglobin antigens, it has a significant response. The detection level for myoglobin is roughly 30 fg/ml, which is quite high. The electrical behavior of the GFET-based biosensor in detecting myoglobin marker is ideal for Lab-on-Chip platforms and Cardiac Point-of-Care Diagnosis.

Induced Pluripotent Stem Cell Derived Airway to Assess Cystic Fibrosis Intrinsic Epithelial Response to SARS-CoV-2

Rationale There is a lack of knowledge of how CFTR-deficient airway epithelium intrinsically responds to SARS-CoV-2. Though prior work has demonstrated altered CF airway expression of viral entry factors, it is unknown whether these alterations are protective and whether they reflect host genetic variation or secondary response of chronic inflammation. We address this gap by infecting induced pluripotent stem cell (iPSC)-derived airways from CF patients and syngeneic CFTR-corrected controls with SARS-CoV-2 and assessing differential susceptibility to infection and inflammatory and anti-viral response. MethodsCF (F508del homozygous) and syngeneic CFTR-corrected (CRISPR-Cas9) iPSC- were differentiated into airway epithelium cultured at airliquid interface (ALI) by a directed differentiation protocol that generates a pure population of major and rare airway cell-types. After 21 days in ALI culture, the iPSC-airway were infected with either mock or SARS-CoV-2 (isolate USA-WA1/2020) with MOI of 4, and harvested at 0, 1, 3 days post infection (dpi) for RT-PCR and immune-stainingResultsBoth CF and CFTR-corrected iPSC-airway express viral entry factors of ACE2 and TMPRSS2, and are permissive to SARS-CoV-2 infection. CF iPSC-airway exhibited significantly increase in SARS-CoV-2 nucleocapsid protein (N) transcript at 1 dpi, accompanied by increases in IFN2, RSAD2, and CXCL10 at 3 dpi, compared to its CFTR-corrected counter-part. There are no baseline significant differences in ACE2, TMPRSS2, TP63, NGFR, MUC5B, MUC5AC, SCGB1A1, FOXJ1, FOXI1 expression between CF and CFTR-corrected iPSC-airway before SARS-CoV-2 infection. ConclusionsOur preliminary studies indicate increased early SARS-CoV-2 infection in CFTR-deficient epithelium with accompanied subsequent rise in anti-viral and inflammatory response compared to its genetically controlled CFTR-corrected counterpart. Future studies are aimed at assessing differential CF epithelial kinetics of SARS-CoV-2 viral entry and replication, morphological changes, global transcriptomic response, and how treatment with CFTRmodulator would alter the epithelial response. Ultimately, we aim to establish a reductionist, physiologically relevant model system that is coupled with gene-editing technology to study intrinsic CF epithelial response to SARS-CoV-2, which would generate insights to aid practice guidelines for CF patients, and open future directions to evaluate gene-specific mechanisms of airway response to pathogens. (Figure Presented).

The Inhibition Activity of Natural Products against Host and Viral Proteins of SARS-CoV-2: Computational Perspective

The Severe Acute Respiratory Syndrome Coronavirus 2 (SARSCoV-2) has disseminated worldwide, decimating millions of people. The number of illnesses and deaths will rise exponentially since there are no viable medications. Especially, with the complex mutations spreading worldwide, the design and development of effective drugs are much needed. Herein, to understand the molecular interactions and mode of binding, 100 natural compounds were tested against Main protease (Mpro), Receptor Binding Domain (RBD) of SARS-CoV-2, and human Angiotensinconverting enzyme 2 (hACE2) using molecular docking. Molecular dynamics simulations were conducted for a period of 100 ns for the best 3 compounds with each target to validate the stability of the complexes. RMSD, RMSF, and Rg analyses were performed to determine the structure and stability of protein-ligand complexes. Further, binding free energy calculations were performed using MM/PBSA approach to identify the effective antiviral agents. Our results will render the potent inhibitors of SARS-Cov-2. © The Electrochemical Society

In silico prediction of interactions and molecular dynamics simulation analysis of Mpro of Severe Acute Respiratory Syndrome caused by novel coronavirus 2 with the FDA-approved nonprotein antiviral drugs

In the current scenario of the severe acute respiratory syndrome caused by novel coronavirus 2 (SARS-CoV-2) pandemic, the repurposing of the Food and Drug Administration (FDA)-approved antiviral drugs for the possibility of treating SARS-CoV-2 is an unavoidable scientific method. It further exemplifies the physical interactions between the target protein and the chosen drugs. In this study, the main protease (Mpro) structure of SARS-CoV-2 Protein Data Bank ID: 7BUY with 42 FDA-approved antiviral drugs was analyzed by molecular docking using PyRx-Vina, and the amino acids involved in docking are analyzed using Discovery Studio Visualizer. The protein–drug complex stability was analyzed by molecular dynamics simulation (MDS) using GROMACS. The results showed that ledipasvir showed the maximum binding affinity (−10.4 kcal/mol) with Mpro of SARS-CoV-2 followed by paritaprevir (−9.1 kcal/mol) and velpatasvir (−8.8 kcal/mol). These three compounds are found to have a significant number of interactions. Moreover, ledipasvir and velpatasvir showed similar interactions at GLU240, PRO241, ILE249, PRO293, and VAL202. MDS showed that the top ligands had formed stable complexes with Mpro. Molecular Mechanics Poisson–Boltzmann Surface Area calculation revealed thermodynamically stable binding energies of −195.370 ± 1.119 kJ/mol and −180.778 ± 0.868 kJ/mol for ledipasvir and velpatasvir, respectively. Paritaprevir showed stable binding energy of −75.679 ± 0.922 kJ/mol with Mpro of SARS-CoV-2. © 2022. Subramaniam Sivakumar et al. This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/).

A machine learning-based approach to determine infection status in recipients of BBV152 (Covaxin) whole-virion inactivated SARS-CoV-2 vaccine for serological surveys.

Data science has been an invaluable part of the COVID-19 pandemic response with multiple applications, ranging from tracking viral evolution to understanding the vaccine effectiveness. Asymptomatic breakthrough infections have been a major problem in assessing vaccine effectiveness in populations globally. Serological discrimination of vaccine response from infection has so far been limited to Spike protein vaccines since whole virion vaccines generate antibodies against all the viral proteins. Here, we show how a statistical and machine learning (ML) based approach can be used to discriminate between SARS-CoV-2 infection and immune response to an inactivated whole virion vaccine (BBV152, Covaxin). For this, we assessed serial data on antibodies against Spike and Nucleocapsid antigens, along with age, sex, number of doses taken, and days since last dose, for 1823 Covaxin recipients. An ensemble ML model, incorporating a consensus clustering approach alongside the support vector machine model, was built on 1063 samples where reliable qualifying data existed, and then applied to the entire dataset. Of 1448 self-reported negative subjects, our ensemble ML model classified 724 to be infected. For method validation, we determined the relative ability of a random subset of samples to neutralize Delta versus wild-type strain using a surrogate neutralization assay. We worked on the premise that antibodies generated by a whole virion vaccine would neutralize wild type more efficiently than delta strain. In 100 of 156 samples, where ML prediction differed from self-reported uninfected status, neutralization against Delta strain was more effective, indicating infection. We found 71.8% subjects predicted to be infected during the surge, which is concordant with the percentage of sequences classified as Delta (75.6%-80.2%) over the same period. Our approach will help in real-world vaccine effectiveness assessments where whole virion vaccines are commonly used.

Effectiveness of ChAdOx1 nCoV-19 Corona Virus Vaccine (CovishieldTM) in preventing SARS-CoV2 infection, Chennai, Tamil Nadu, India, 2021 (preprint)

Background: India experienced the second wave of the COVID-19 pandemic in March 2021, driven by the delta variant. Apprehensions around the usefulness of vaccines against delta variant posed a risk to the vaccination program. Therefore, we estimated the effectiveness of two doses of the ChAdOx1 nCoV-19 (Covishield) vaccine against COVID-19 infection among individuals [≥]45 years in Chennai, India. Methods: A community-based cohort study was conducted from May to September 2021 in a selected geographic area in Chennai, Tamil Nadu. The estimated sample size was 10,232. We enumerated individuals from all eligible households and periodically updated vaccination and COVID-19 infection data. We computed vaccine effectiveness with its 95% confidence interval for two doses of the Covishield vaccine against any COVID-19 infection. Results: We enrolled 69,435 individuals, of which 21,793 were above 45 years. Two dose coverage of Covishield in the 18+ and 45+ age group was 18% and 31%, respectively. The overall incidence of COVID-19 infection was 1099 per 100,000 population. The vaccine effectiveness against COVID-19 disease in the [≥]45 age group was 61.3% (95% CI: 43.6 - 73.4) at least two weeks after receiving the second dose of Covishield. Genomic analysis of 74 (28 with two doses, 15 with one dose, and 31 with zero dose) out of the 90 aliquots collected from the 303 COVID-19 positive individuals in the 45+ age group showed delta variants and their sub-lineages. Conclusion: We demonstrated the effectiveness of two doses of the ChAdOx1 vaccine against the delta variant in the general population of Chennai. We recommend similar future studies considering emerging variants and newer vaccines. Two-dose vaccine coverage could be ensured to protect against COVID-19 infection.

Cyberchondria and its Impact on Self-Medication and Self Care in Covid-19 Pandemic - A Cross Sectional Study

Corona Virus Disease 2019 (COV ID-19) has brought several impacts on the health of people. The infodemic which accompanied the pandemic can lead to cyberchondria, fear and anxiety accompanying excessive online search of COV ID-19 related information. Most of the people try to avoid getting infected with this virus by taking adequate protective measures. Hence the aim of this study was to analyze the impact of COV ID-19 related cyberchondria on self-medication and self care. An online cross-sectional semi-structured questionnaire based study was done and a total of 323 responses were obtained. Participants were segregated into two clusters based on the cyberchondria severity score which included four constructs using k-means cluster analysis considering the score obtained in each construct. The impact of cyberchondria on self care and self care among medical practitioners between the clusters were analyzed using independent t-test. Qualitative data were analyzed using descriptive statistics. This study found that 35% of the participants were categorized in the cluster with high cyberchondria score. A marked proportion of the participants who have taken self-medication for COV ID-19 prophylaxis belonged to this cluster. A statistically significant difference was observed in the mean of the scores used to assess self care between the clusters (p = 0.003) whereas no significant difference was observed among registered medical practitioners (p=0.222). Anxiety related with excessive online COV ID-19 information seeking behaviour had effects in terms of enhanced self care and self-medication in the respondents. Hence it is important to use internet wisely for self well being.

A machine learning-based approach to determine infection status in recipients of BBV152 whole virion inactivated SARS-CoV-2 vaccine for serological surveys (preprint)

Data science has been an invaluable part of the COVID-19 pandemic response with multiple applications, ranging from tracking viral evolution to understanding the effectiveness of interventions. Asymptomatic breakthrough infections have been a major problem during the ongoing surge of Delta variant globally. Serological discrimination of vaccine response from infection has so far been limited to Spike protein vaccines used in the higher-income regions. Here, we show for the first time how statistical and machine learning (ML) approaches can discriminate SARS-CoV-2 infection from immune response to an inactivated whole virion vaccine (BBV152, Covaxin, India), thereby permitting real-world vaccine effectiveness assessments from cohort-based serosurveys in Asia and Africa where such vaccines are commonly used. Briefly, we accessed serial data on Anti-S and Anti-NC antibody concentration values, along with age, sex, number of doses, and number of days since the last vaccine dose for 1823 Covaxin recipients. An ensemble ML model, incorporating a consensus clustering approach alongside the support vector machine (SVM) model, was built on 1063 samples where reliable qualifying data existed, and then applied to the entire dataset. Of 1448 self-reported negative subjects, 724 were classified as infected. Since the vaccine contains wild-type virus and the antibodies induced will neutralize wild type much better than Delta variant, we determined the relative ability of a random subset of such samples to neutralize Delta versus wild type strain. In 100 of 156 samples, where ML prediction differed from self-reported uninfected status, Delta variant, was neutralized more effectively than the wild type, which cannot happen without infection. The fraction rose to 71.8% (28 of 39) in subjects predicted to be infected during the surge, which is concordant with the percentage of sequences classified as Delta (75.6%-80.2%) over the same period.

Design and Development of Graphene FET Biosensor for the Detection of SARS-CoV-2

The most affected disease in recent years is Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-COV-2) that is notable as COVID-19. It has been started as a disease in one place and arisen as a pandemic throughout the world. A serious health problem is developed in the lungs due to the effect of this coronavirus. Sometimes it may result in death as a consequence of extensive alveolar damage and progressive respiratory failure. Hence, early detection and appropriate diagnosis of corona virus in patient's body is very essential to save the lives of affected patients This work evolves a Silicon (Si) based label-free electrical device i.e. the reduced graphene oxide field-effect transistor (rGO FET) for SARS-CoV-2 detection. Firstly rGO FET functionalized with SARS-CoV-2 monoclonal antibodies (mAbs). Then the rGO FET characteristic response is observed to detect the antibody-antigen reaction of SARS-CoV-2 with different molar ranges. The developed GFET shows better performance towards the drain current and limit-of-detection (LoD) up to 2E-18 M. Therefore, we believe that an intense response was observed than the earlier developed devices and signifies impressive capability for subsequent implementation in point-of-care (PoC) diagnostic tests.

Modelling the COVID-19 Pandemic: Asymptomatic Patients, Lockdown and Herd Immunity

The SARS-Cov-2 is a type of coronavirus that has caused the COVID-19 pandemic. In traditional epidemiological models such as SEIR (Susceptible, Exposed, Infected, Removed), the exposed group E does not infect the susceptible group S. A distinguishing feature of COVID-19 is that, unlike with previous viruses, there is a distinct "asymptomatic" group A, who do not show any symptoms, but can nevertheless infect others, at the same rate as infected patients. This situation is captured in a model known as SAIR (Susceptible, Asymptomatic, Infected, Removed), introduced in Robinson and Stilianakis (2013). The dynamical behavior of the SAIR model is quite different from that of the SEIR model. In this paper, we use Lyapunov theory to establish the global asymptotic stabiilty of the SAIR model. Next, we present methods for estimating the parameters in the SAIR model. We apply these estimation methods to data from several countries including India, and show that the predicted trajectories of the disease closely match actual data. Copyright (C) 2020 The Authors.

Insights from a Pan India Sero-Epidemiological survey (Phenome-India Cohort) for SARS-CoV2.

To understand the spread of SARS-CoV2, in August and September 2020, the Council of Scientific and Industrial Research (India) conducted a serosurvey across its constituent laboratories and centers across India. Of 10,427 volunteers, 1058 (10.14%) tested positive for SARS-CoV2 anti-nucleocapsid (anti-NC) antibodies, 95% of which had surrogate neutralization activity. Three-fourth of these recalled no symptoms. Repeat serology tests at 3 (n = 607) and 6 (n = 175) months showed stable anti-NC antibodies but declining neutralization activity. Local seropositivity was higher in densely populated cities and was inversely correlated with a 30-day change in regional test positivity rates (TPRs). Regional seropositivity above 10% was associated with declining TPR. Personal factors associated with higher odds of seropositivity were high-exposure work (odds ratio, 95% confidence interval, p value: 2.23, 1.92-2.59, <0.0001), use of public transport (1.79, 1.43-2.24, <0.0001), not smoking (1.52, 1.16-1.99, 0.0257), non-vegetarian diet (1.67, 1.41-1.99, <0.0001), and B blood group (1.36, 1.15-1.61, 0.001).

The detection of SARS-CoV-2 in autolysed samples from an exhumed decomposed body: Implications to virus survival, genome stability, and spatial distribution in tissues (preprint)

Here we report for the first time the SARS-CoV-2 detection in autolysed samples from an exhumed decomposed body post-thirty six days after death. Both naso-oropharyngeal swabs and visceral samples from the lung, intestine, liver, and kidney were collected from the body exhumed post-fifteen days after burial, stored in viral transport medium and in saturated salt solution respectively. Naso-oropharyngeal swabs showed the presence of the SARS-CoV-2 genome as identified by the amplification of viral E, N, RdRP, or ORF1ab genes by RT-PCR. Subsequent examination of tissues reveal the detection of the virus genome in the intestine and liver, while no detection in the kidney and lung. These results signify the genome stability and implicate the virus survival in decomposed swab samples and in tissues and thereafter in storage solution. Further results also indicate spatial distribution of the virus in tissues during the early stage of infection in the subject with no respiratory distress. Considering the presence of cool, humid, and moist location of the exhumation, the presence of virus genome might also indicate that SARS-CoV-2 can persist for more than seven days on the surface of dead bodies similar to the Ebola virus, confirming that transmission from deceased subjects is possible for an extended period after death. These results further reaffirm the robustness of the RT-PCR aiding in the detection of viruses or their genome in decomposed samples when other methods of detection could not be useful.

Insights from a Pan India Sero-Epidemiological survey (Phenome-India Cohort) for SARS-CoV2 (preprint)

BackgroundIndia has been amongst the most affected nations during the SARS-CoV2 pandemic, with sparse data on country-wide spread of asymptomatic infections and antibody persistence. This longitudinal cohort study was aimed to evaluate SARS-CoV2 sero-positivity rate as a marker of infection and evaluate temporal persistence of antibodies with neutralization capability and to infer possible risk factors for infection. MethodsCouncil of Scientific and Industrial Research, India (CSIR) with its more than 40 laboratories and centers in urban and semi-urban settings spread across the country piloted the pan country surveillance. 10427 adult individuals working in CSIR laboratories and their family members based on voluntary participation were assessed for antibody presence and stability was analyzed over 6 months utilizing qualitative Elecsys SARS CoV2 specific antibody kit and GENScript cPass SARS-CoV2 Neutralization Antibody Detection Kit. Along with demographic information, possible risk factors were evaluated through self to be filled online forms with data acquired on blood group type, occupation type, addiction and habits including smoking and alcohol, diet preferences, medical history and transport type utilized. Symptom history and information on possible contact and compliance with COVID 19 universal precautions was also obtained. Findings1058 individuals (10{middle dot}14%) had antibodies against SARS-CoV2. A follow-up on 346 sero-positive individuals after three months revealed stable to higher antibody levels against SARS-CoV2 but declining plasma activity for neutralizing SARS-CoV2 receptor binding domain and ACE2 interaction. A repeat sampling of 35 individuals, at six months, revealed declining antibody levels while the neutralizing activity remained stable compared to three months. Majority of sero-positive individuals (75%) did not recall even one of nine symptoms since March 2020. Fever was the most common symptom with one-fourth reporting loss of taste or smell. Significantly associated risks for sero-positivity (Odds Ratio, 95% CI, p value) were observed with usage of public transport (1{middle dot}79, 1{middle dot}43 - 2{middle dot}24, 2{middle dot}81561E-06), occupational responsibilities such as security, housekeeping personnel etc. (2{middle dot}23, 1{middle dot}92 - 2{middle dot}59, 6{middle dot}43969E-26), non-smokers (1{middle dot}52, 1{middle dot}16 - 1{middle dot}99, 0{middle dot}02) and non-vegetarianism (1{middle dot}67, 1{middle dot}41 - 1{middle dot}99, 3{middle dot}03821E-08). An iterative regression analysis was confirmatory and led to only modest changes to estimates. Predilections for sero-positivity was noted with specific ABO blood groups -O was associated with a lower risk. InterpretationIn a first-of-its-kind study from India, we report the sero-positivity in a country-wide cohort and identify variable susceptible associations for contacting infection. Serology and Neutralizing Antibody response provides much-sought-for general insights on the immune response to the virus among Indians and will be an important resource for designing vaccination strategies. FundingCouncil of Scientific and Industrial Research, India (CSIR)

51.6 IMPACT OF COVID-19 ON THE GLOBAL ASSESSMENT OF FUNCTIONING SCORES

Objectives: The objectives of this presentation are to: 1) examine the change in level of functioning and mood that COVID-19 has had on children with psychiatry appointments;and 2) identify associated factors that may play a part in this change such as decreased social contacts, increased time with guardians, decreased teacher presentation time, decreased availability of extracurricular activities, and sleep schedule changes. Methods: A total of 10 adolescents between the ages of 6 and 19 years old were interviewed over 2 weeks to discuss the impacts of COVID-19 and ascertain a score congruent to the Global Assessment of Functioning (GAF) score. Variables such as sleep, parental relationships, interests, academics, and virtual and physical socialization were discussed in a qualitative manner. Results: Using a paired-sample t test for each patient, the GAF score from an office visit approximately 1 year prior (within 1 month) was compared to their most recent mental health appointment to control for seasonal affective disorders and school timing. The change in GAF scores was found to be increased by a significant amount (p = 0.008) with a large standardized effect size (1.06). Conclusions: COVID-19 has caused physical limitations and confined many children to their household;however, during this study, GAF scores either improved or were maintained possibly due to increased parental supervision or exploration of new activities. The limitation of this study is that children may achieve better GAF scores on their own through maturation or default regression of the mean. Additionally, being under the mental and pharmacologic treatment of a psychiatrist has already proven to improve behavioral functioning. FAM, COPI, SII