SeroNet Pooling Project of immunocompromised populations

Introduction: COVID-19 vaccination substantially reduces morbidity and mortality associated with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and severe illness. However, despite effective COVID-19 vaccines many questions remain about the efficacy of vaccines and the durability and robustness of immune responses, especially in immunocompromised persons. The NCI-funded Serological Sciences Network (SeroNet) is a coordinated effort including 11 sites to advance research on the immune response to SARS-CoV-2 infection and COVID-19 vaccination among diverse and vulnerable populations. The goals of the Pooling Project are: (1) to conduct real-world data (RWD) analyses using electronic medical records (EMR) data from four health care systems (Kaiser Permanente Northern California, Northwell Health, Veterans Affairs-Case Western, and Cedars-Sinai) to determine vaccine effectiveness in (a) cancer patients;(b) autoimmune diseases and (c) solid organ transplant recipients (SOTR);(2) to conduct meta-analyses of prospective cohort studies from eight SeroNet institutions (Cedars-Sinai, Johns Hopkins, Northwell Health, Emory University, University of Minnesota, Mount Sinai, Yale University) to determine post-vaccine immune responses in (a) lung cancer patients;(b) hematologic cancers/hematopoietic stem cell transplant (HSCT) recipients;(c) SOTR;(d) lupus. Method(s): For our RWD analyses, data is extracted from EMR using standardized algorithms using ICD-10 codes to identify immunocompromised persons (hematologic and solid organ malignancy;SOTR;autoimmune disease, including inflammatory bowel disease, rheumatoid arthritis, and SLE). We use common case definitions to extract data on demographic, laboratory values, clinical co morbidity, COVID-19 vaccination, SARS-CoV-2 infection and severe COVID-19, and diseasespecific variables. In addition, we pool individual-level data from prospective cohorts enrolling patients with cancer and other immunosuppressed conditions from across network. Surveys and biospecimens from serology and immune profiling are collected at pre-specified timepoints across longitudinal cohorts. Result(s): Currently, we have EMR data extracted from 4 health systems including >715,000 cancer patients, >9,500 SOTR and >180,000 with autoimmune conditions. Prospective cohorts across the network have longitudinal data on >450 patients with lung cancer, >1,200 patients with hematologic malignancies, >400 SOTR and >400 patients with lupus. We will report results examining vaccine effectiveness for prevention of SARS-CoV-2 infection, severe COVID-19 and post-acute sequelae of COVID-19 (PAS-C or long COVID) in cancer patients compared to other immunocompromised conditions. Conclusion(s): Our goal is to inform public health guidelines on COVID-19 vaccine and boosters to reduce SARS-CoV-2 infection and severe illness in immunocompromised populations.

Antibody Responses to an Additional Dose of SARS-CoV-2 mRNA Vaccine in Solid Organ Transplant Recipients with and without HIV

Purpose: Solid organ transplant (SOT) recipients mount suboptimal immune responses to a two-dose SARS-CoV-2 mRNA vaccine series. Data regarding antibody responses in HIV and SOT remains limited. We characterized spike binding antibody responses before and after an additional mRNA vaccine dose in SOT recipients, including in people with HIV (PWH). Method(s): Spike binding antibody titers were assessed before and one month after an additional vaccine dose using a quantitative ELISA. An additional vaccine dose was defined as a third dose of a mRNA vaccine primary series, as recommended by the CDC. Result(s): Antibody titers were assessed in 64 SOT recipients (58% kidney, 34% liver, 8% other). Participants had a median age of 57 and 47% were women. PWH comprised 14% of the cohort (9/64, 78% kidney). 70% (45/64) of SOT recipients developed antibodies after a two-dose vaccine series (62% kidney, 33% liver). The additional dose was given a median of 169 days (IQR 144.75-185.75 days) after the second vaccine dose, and 72% received three doses of BNT162b2 (Pfizer-BioNTech) while 28% received three doses of mRNA-1273 vaccine (Moderna). The median time between transplantation and an additional vaccine dose was 2.8 years (IQR, 0.6-8.9). 32% (6/19) of SOT recipients who had no detectable antibody seroconverted after receiving an additional vaccine dose. The 45 participants who were seropositive prior to the third dose displayed a median 4.4-fold increase in antibody titers. SOT recipients with HIV had comparable antibody responses to those without HIV. Conclusion(s): Our data indicate that SOT recipients benefit from an additional SARS-CoV-2 mRNA vaccine dose. SOT recipients with and without HIV appear to mount comparable antibody responses upon vaccination, although larger numbers are needed.

GQNN: Greedy Quanvolutional Neural Network Model

Quantum computation, particularly in the field of machine learning, is a rapidly growing technology. Major advantage of Quantum computing is its speed to perform calculations. This paper proposes a novel model architecture for feature extraction. It extracts the features from a colored spectrogram as an extension to the already existing Quanvolutional Neural Network which works on only grayscale images or 2-dimensional representation of spectrograms. The proposed model architecture works on all the three layers of an image (RGB) and uses random quantum circuits to extract features from them and distribute them into several output images and out of them one is selected which contains the most important and pertinent features from the original image helping the training of the CNN model used ahead. COVID-19 use case is used for performance evaluation. Normally the testing methods used to detect virus are expensive, examples include RT-PCR test, CT scan images. These methods require a medical professional to conduct the test while being in the proximity of the patient. Also, the testing kits once used cannot be used again. One of the most evident changes in a Covid 19 patient is the change in his/her coughing and breathing pattern. This work analyzed the spectrograms of the audio samples of coughing and breathing patterns of Covid 19 patients using the proposed model architecture and provided subsequent results. Finally to generalize our model’s applicability, the model is also run-on Alzheimer disease dataset and corresponding results are provided. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Jaya Honey Badger optimization-based deep neuro-fuzzy network structure for detection of (SARS-CoV) Covid-19 disease by using respiratory sound signals

Purpose The Covid-19 prediction process is more indispensable to handle the spread and death occurred rate because of Covid-19. However early and precise prediction of Covid-19 is more difficult because of different sizes and resolutions of input image. Thus these challenges and problems experienced by traditional Covid-19 detection methods are considered as major motivation to develop JHBO-based DNFN. Design/methodology/approach The major contribution of this research is to design an effectual Covid-19 detection model using devised JHBO-based DNFN. Here, the audio signal is considered as input for detecting Covid-19. The Gaussian filter is applied to input signal for removing the noises and then feature extraction is performed. The substantial features, like spectral roll-off, spectral bandwidth, Mel-frequency cepstral coefficients (MFCC), spectral flatness, zero crossing rate, spectral centroid, mean square energy and spectral contract are extracted for further processing. Finally, DNFN is applied for detecting Covid-19 and the deep leaning model is trained by designed JHBO algorithm. Accordingly, the developed JHBO method is newly designed by incorporating Honey Badger optimization Algorithm (HBA) and Jaya algorithm. Findings The performance of proposed hybrid optimization-based deep learning algorithm is estimated by means of two performance metrics, namely testing accuracy, sensitivity and specificity of 0.9176, 0.9218 and 0.9219. Research limitations/implications The JHBO-based DNFN approach is developed for Covid-19 detection. The developed approach can be extended by including other hybrid optimization algorithms as well as other features can be extracted for further improving the detection performance. Practical implications The proposed Covid-19 detection method is useful in various applications, like medical and so on. Originality/value Developed JHBO-enabled DNFN for Covid-19 detection: An effective Covid-19 detection technique is introduced based on hybrid optimization-driven deep learning model. The DNFN is used for detecting Covid-19, which classifies the feature vector as Covid-19 or non-Covid-19. Moreover, the DNFN is trained by devised JHBO approach, which is introduced by combining HBA and Jaya algorithm.

Evaluation and semantic approach for student performance prediction using data mining techniques

Educational Data Mining (EDM) refers to the field that focuses on using various statistical methods and data mining techniques to draw inferences from large amount of educational data set. Over the years it has been used for student performance prediction by applying various machine learning processes and more recently deep learning. As a result of the lockdown announced after the spread of Covid-19, many colleges were forced to adapt to online learning tools. In this paper, we identify and evaluate the impact of the Covid-19 pandemic and its subsequent fallout in predicting student's academic performance. For this, a data set of various undergraduate students was compiled from March 2021. A Likert-type questionnaire was administered and large number of responses were gathered from various primary and secondary resources. This was subsequently used to validate the proposed methodology. Furthermore, different classification algorithms were used to predict the performance of the student and subsequently compared with one another based on their accuracy. The results show that the excessive use of e- learning tools including smartphones, laptops and tablets have a significant impact on student's academic performance as well as on their psychological health. The work will help us to better understand the impact of the lockdown on student's scholastic performance and point out areas where online-learning methods can be improved. © 2022 Author(s).

SARS CoV-2 Re infection after natural infection compared with previously sero-negative: Descriptive longitudinal study

Background: WHO declared SARS-CoV-2 infection as pandemic on March 11, 2020. As cases recovered, it became important to know the rate of re-infection from the same virus and its severity. Therefore, the study was done to find out re-infection rate among the previously infected individuals. Aim: To find out re-infection rate among already exposed and nonexposed individuals. Materials and Methods: A cohort study was done over 5000 previously serosurveyed individual. They were followed up via telephone. Data was collected using a questionnaire with questions regarding infection post-serosurvey, severity of infection among relatives and vaccination status. Thus information collected was uploaded in Google form. Results: Re-infection rate among previously exposed individuals was 1.2%;at the same time period, 6% of nonexposed individuals got infected. All the re-infection cases were mild, whereas 80.74% of individuals who got infected for the first time had mild symptoms. Exposure to SARS-CoV-2 in relatives who were staying with participants was found to be 3.23% and 4.22% among previously exposed and non-exposed individuals respectively. 17% of previously nonexposed individuals were fully vaccinated, whereas 0.65% of exposed individual got fully vaccinated. Conclusion: Re-infection rate in the study was less and mild on the basis of severity. Infection rate among the nonexposed was at a higher side stating that chances of getting re-infected are much lesser. Previously exposed individuals did not show the same type of interest for vaccination compared to previously nonexposed individuals. © 2022 International Journal of Nutrition, Pharmacology, Neurological Diseases ;Published by Wolters Kluwer - Medknow.

COVID-19 Antibody Detection and Assay Performance Using Red Cell Agglutination

Background. Serologic assays detecting antibodies against the SARS-CoV-2 spike or nucleocapsid proteins have been developed to advance our understanding of the prognosis and clinical course of the COVID-19 disease. We recently developed a red cell agglutination-based assay to detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibodies. This assay uses peptide fragments of the SARS-CoV-2 spike protein to label red cells (C19-kodecytes). We performed a clinical evaluation of this C19-kodecyte assay in COVID-19 convalescent plasma (CCP) donors previously assessed with 2 commercial immunoassays and a virus neutralizing assay. Methods. Red cells were coated with peptide fragments of the SARS-CoV-2 spike protein. We tested plasma samples from 140 CCP donors. The results were compared with those of a virus neutralizing assay and 2 commercial chemiluminescent antibody tests: anti-SARS-CoV-2 Total (IgG, IgM and IgA) assay and anti-SARS-CoV-2 IgG assay (Ortho). Inter-rater agreement between the different assays was measured using Cohen's kappa. Specificity was tested with 150 plasma samples, collected in 2008, more than a decade before the COVID-19 outbreak and with 125 plasma samples, collected in 2020 from consecutive healthy volunteer donors, who tested negative for the Ortho Total assay. Testing was performed using the column agglutination technique commonly employed for blood typing. Results. The area under the ROC curve (AUC) for the C19-kodecyte assay reached 0.95 (95% CI: 0.93 - 0.97) with sensitivity of 92.8% (95% CI: 86.9% - 96.3%) and specificity of 96.3% (95% CI: 93.2% - 98.1%). In almost all of the 40 CCP donors with longitudinal data, the antibody concentration decreased during the follow-up, which ranged from 7 to 44 weeks. In the 140 CCP donors, we compared the C19-kodecyte score to the antibody concentrations from the 2 FDA authorized assays (Ortho Total and Ortho IgG) and the titer in the neutralizing assay. There was a positive relationship between the results of all 4 assays. The Spearman's correlation of our assay was 0.20 with the neutralizing assay (0.49 with IgG, and 0.41 with Total assays). Conclusions. Sensitivity and specificity of the C19-kodecyte assay were within the minimum performance range required by the FDA for EUA authorization of serology tests. The limited correlation in assay reaction strengths suggested that the assays may be influenced by different antibody specificities. Unlike the other 84 FDA authorized serologic tests for SARS-CoV-2, this C19-kodecyte assay is a simple and rapid test that can be easily established in any blood typing laboratory worldwide using its routine setup for column agglutination or tube technique. The technique could vastly improve assay capacity, particularly in resource limited hospital blood banks. Disclosures: Bovin: Kode Biotech: Current Employment, Current holder of stock options in a privately-held company. Henry: Kode Biotech: Current Employment, Current holder of stock options in a privately-held company.

Suboptimal Humoral and Cellular Immune Response to SARS-CoV-2 RNA Vaccination in Myeloma Patients Is Associated with Anti-CD38 and BCMA-Targeted Treatment

Background: Multiple myeloma (MM) patients are immunocompromised due to defects in humoral/cellular immunity and immunosuppressive therapy. Reports indicate that the antibody (Ab) response in MM after 1 dose of SARS-CoV-2 RNA vaccine is attenuated. The impact of treatment on cellular immunity after vaccination remains unknown. Methods: We analyzed SARS-CoV-2 spike-binding (anti-S) IgG level in 320 MM patients receiving SARS-CoV-2 RNA vaccination. Blood and saliva were taken at multiple time points and compared with serology data of 69 age-matched vaccinated healthcare workers. We profiled SARS-CoV-2-specific T cell responses in a subset of 45 MM patients and 12 age-matched healthy controls by flow cytometry and ELIspot. All subjects were enrolled in studies approved by the Institutional Review Board at the Icahn School of Medicine at Mount Sinai. Results: The 320 patients (median age 68 year) received two-dose RNA vaccines (69.1% BNT162b2, 27.2% mRNA-1273). Median time to diagnosis was 60 months with a median of 2 prior treatment lines (range 0-16). We included 23 patients with smoldering MM. Patients received various treatments at vaccination with 148 (43.8%) on anti-CD38-containing treatment, 36 (11.3%) on BCMA-targeted therapy and 59 (18.4%) not on active treatment (incl. SMM patients). At the last available evaluation prior to vaccination, 131 (40.9%) exhibited a complete response. At data cutoff, a total of 260 patients (81.3%) had anti-S IgG measured >10 days after the second vaccine (median 51 days). Of these, 84.2% mounted measurable anti-S IgG levels (median 149 AU/mL). In the control group, Ab levels were significantly higher (median 300 AU/mL). Ab levels in the vaccinated MM patients with prior COVID-19 were 10-fold higher than those of patients without prior COVID-19 (p<0.001). Repeat Ab measurements up to 60 days after second vaccination confirm delayed and suboptimal IgG kinetics, particularly in patients receiving anti-MM treatment compared to controls (Figure 1). MM patients on active treatment had lower anti-S IgG levels (p=0.004) compared to patients not on therapy (median 70 vs 183 AU/mL). Notably, 41 patients (15.8%) failed to develop detectable anti-S IgG: 24/41 (58.5%) were on anti-CD38, 13/41 (31.7%) on anti-BCMA bispecific Ab therapy and 4/41 (9.8%) >3 months after CAR T. Univariate analysis showed an association of disease-related factors with absence of anti-S IgG: more previous lines of treatment (>3 lines, p=0.035;>5 lines, p=0.009), receiving active MM treatment (p=0.005), grade 3 lymphopenia (p=0.018), receiving anti-CD38 therapy (p=0.042) and receiving BCMA-targeted therapy (p<0.001). Multivariate analysis (corrected for age, vaccine type, lines of treatment, time since diagnosis, response status and lymphopenia) confirmed that anti-CD38 (p=0.005) and BCMA-targeted treatment (p<0.001) are associated with not developing detectable anti-S IgG. Clinical relevance is emphasized by 10 cases of COVID-19 after 1 (n=7) or 2 vaccine doses (n=3, all without anti-S IgG) with 1 patient passing due to respiratory failure. We studied SARS-CoV-2-specific T cell responses >2 weeks after the second vaccine in 18 MM patients with undetectable anti-S IgG (seronegative), 27 with detectable anti-S IgG (seropositive) and 12 healthy seropositive controls. We found that seropositive MM patients had CD4+CD154+ T cells producing IFNg, TNFa and IL-2 at similar levels as controls, whereas in the seronegative MM cohort CD4 T cell responses were significantly reduced (p<0.005). SARS-CoV-2-specific CD8 T cell responses were overall weaker and not different across cohorts. This data suggests that absence of detectable IgG is associated with suboptimal response of humoral and cellular immunity. Conclusion: MM patients mount a suboptimal IgG response after SARS-CoV-2 vaccination, with 15.8% of patients without detectable anti-S IgG. Ongoing analyses will highlight durability of serological protection against COVID-19. Additional data on T cell responses and immunophenotyping in the context of vaccination will be upda ed at the meeting. Implications are continuation of non-pharmacological interventions, e.g. masking/social distancing, for vulnerable patients. The findings underscore a need for serological monitoring of MM patients after vaccination and for trials assessing use of prophylactic strategies or studies exploring additional immunization strategies. [Formula presented] Disclosures: Wang: Sanofi Genzyme: Consultancy. Chari: Karyopharm: Consultancy, Membership on an entity's Board of Directors or advisory committees;Seattle Genetics: Membership on an entity's Board of Directors or advisory committees, Research Funding;Millenium/Takeda: Consultancy, Research Funding;Sanofi Genzyme: Consultancy, Membership on an entity's Board of Directors or advisory committees;Genentech: Consultancy, Membership on an entity's Board of Directors or advisory committees;Pharmacyclics: Research Funding;GlaxoSmithKline: Consultancy, Membership on an entity's Board of Directors or advisory committees;Secura Bio: Consultancy, Membership on an entity's Board of Directors or advisory committees;Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding;Antengene: Consultancy, Membership on an entity's Board of Directors or advisory committees;Oncopeptides: Consultancy, Membership on an entity's Board of Directors or advisory committees;Novartis: Consultancy, Research Funding;Janssen Oncology: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding;Shattuck Labs: Consultancy, Membership on an entity's Board of Directors or advisory committees;BMS/Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding;Takeda: Consultancy, Research Funding;AbbVie: Consultancy, Membership on an entity's Board of Directors or advisory committees. Cordon-Cardo: Kantaro: Patents & Royalties. Krammer: Kantaro: Patents & Royalties;Merck: Consultancy;Pfizer: Consultancy;Avimex: Consultancy;Seqirus: Consultancy. Jagannath: Legend Biotech: Consultancy;Karyopharm Therapeutics: Consultancy;Janssen Pharmaceuticals: Consultancy;Bristol Myers Squibb: Consultancy;Sanofi: Consultancy;Takeda: Consultancy. Simon: Kantaro: Patents & Royalties. Parekh: Foundation Medicine Inc: Consultancy;Amgen: Research Funding;PFIZER: Research Funding;CELGENE: Research Funding;Karyopharm Inv: Research Funding.

A Study of the Impact of Covid-19 Using a Sieve Approach

COVID-19 is an exceptionally infectious illness that has affected the general public. Displaying such sicknesses can be critical in the expectation of their effect. The assessment of the COVID patient and its correlation with sequential age is a significant task in the clinic, however, with the help of machine learning algorithms we can effectively model the expectations. Getting factual expectation can be tedious as movements can be inclined to intra-rater changeability, the utilization of strategies that can computerize it, similar to machine learning techniques, is of value. The objective of this part is to introduce the strainer chart, patterns and holes in the examination identified with age and sex assessment that utilize machine learning techniques and also provides the COVID issues with various problems in combination with sieve methods. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

COVID-19 antibodies in convalescent plasma evaluated by the C19-kodecyte (Anti-SARSCoV- 2 Red Cell) Assay

Background/Case Studies: We had developed a simple and rapid red cell agglutination assay for serologic screening of antibodies to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We evaluated this new C19-kodecyte assay in a cohort of convalescent patients with PCR-confirmed SARS-CoV-2 infection and compared its analytical performance with three established assays. Study Design/Methods: Red cells modified with peptides from SARS-CoV-2 spike protein using the Kode Technology were prepared.We tested plasma samples from 140 convalescent plasma donors and 125 healthy donors that had tested negative for anti-SARS-CoV-2 Total (Ortho). Plasma samples were stored at -30 °C before testing. Testing was performed using the column agglutination technology commonly employed for blood typing. The results were evaluated and compared with the results of a virus neutralization assay and two commercial chemiluminescent antibody tests: Ortho anti-SARS-CoV-2 Total (IgG, IgM and IgA) assay and Ortho anti-SARS-CoV-2 IgG antibody assay. Results/Findings: The median time interval from the onset of symptoms and plasma donation was 94 days (range: 33 - 331 days). Our simple and rapid C19-kodecyte assay detected SARS-CoV-2 antibodies with a specificity of 95.2% and sensitivity of 92.1%. Correlation analysis of measurement data among the different platforms showed a weak to moderate concordance. The Pearson correlation coefficient ranged between 0.21 and 0.28 for C19-kodecyte versus Ortho anti-SARS-CoV-2 Total and Ortho anti-SARS-CoV-2 IgG assays while it was 0.24 between C19-kodecyte and neutralizing titer. Agreements among C19-kodecyte versus Ortho anti-SARS-CoV-2 Total and Ortho anti-SARS-CoV-2 IgG assays were moderate: 0.41 (0.09-0.73) and 0.41 (0.14-0.68), respectively. Conclusions: Sensitivity and specificity of the C19-kodecyte assay are within the estimated range of FDA issued EUA authorized serology tests (88% to 100% sensitivity and 95% to 100% specificity). The low correlation between C19-kodecyte versus Ortho anti-SARSCoV- 2 results and between C19-kodecyte versus neutralizing titer suggests that COVID-19 patients develop a broad antibody repertoire against multiple SARS-CoV-2 proteins and epitopes and different assays detect diverse antibody specificities. Our easily scalable approach using C19-kodecytes can be operated in blood typing laboratories worldwide using common routine setups. The availability of standard blood group serology techniques for SARS-CoV-2 antibody screening could vastly improve assay capacity. This would be particularly useful in developing countries, where dedicated virology and microbiology may be lacking the necessary turnaround capacity.

Low Cost Design of Non-Contact Thermometry for Diagnosis and Monitoring

The novel coronavirus pandemic has created the need for employee health monitoring and diagnosis in the workplace as one of the measures. The authors have attempted to design a non-contact thermometry device to create an open-source design that is simultaneously inexpensive. Such a device can be manufactured and deployed in a wide variety of economically challenged areas. The first iteration of a working design is summarized in this paper. Future work will include design customizations for cost-savings, accuracy, and precision improvements and considerations such as design for manufacturability and repairability.

Impact on anxiety of COVID-19 and lockdown

Background: India was placed under "lockdown" since March 25, 2020, to curb the spread of COVID-19 pandemic. Faced with this unprecedented situation, many individuals reported mounting apprehensions and some sought medical relief of anxiety. This study was carried to assess the impact of anxiety on COVID-19 pandemic and lockdown on the general public (18-65 years of age) and to assess its correlates. Materials and Methods: An online survey was conducted during lockdown. Using a survey form, a link was circulated using social media and E-mail. The survey included bilingual informed consent, sociodemographic data, characteristics specific to lockdown, and a self-rating anxiety scale. The survey link was circulated from April 1, 2020, to April 30, 2020. Results: A total of 987 responses were collected and analyzed. The study revealed minimal-to-moderate anxiety in 28.5%, marked-to-severe anxiety in 3.3%, and extreme anxiety in 0.1% of the participants. Anxiety scores were significantly correlated with younger age, students, currently employed, male gender, and lower income. Conclusions: The current survey indicates that 31.9% are experiencing significant anxiety due to lockdown and COVID-19 pandemic. Younger age, students, currently employed, male gender, and lower income are associated with higher anxiety. These findings suggest that there is a need of expanding the mental health services in society during and immediately after the pandemic situation.

Facade of media and social media during covid-19: A review

A novel coronavirus (COVID-19) arose in Wuhan, China, in December 2019. Soon it spread to other countries worldwide to become a pandemic. Globally, governments enforced quarantine and social distancing measures to prevent the spread of the infection. Mass media and social media platforms played a crucial role in providing information regarding the Coronavirus. Since little is known about COVID-19, various fake news, misinformation and rumours spread across the digital media that panicked people into making panic deci-sions. The rapid spread of misinformation and stories via social media platforms such as Twitter, Facebook and YouTube became a vital concern of the government and public health authorities. Medical misinformation and unver-ifiable content about the COVID-19 pandemic are spreading on social media at an unprecedented pace. Mitigating the advent of rumours and misinformation during the COVID-19 epidemic is crucial, since misinformation and fake news creates panic, fear and anxiety among people, predisposing them to various mental health conditions. Instead of considering social media as a secondary medium, it should be utilised to convey important information. Besides, it allows citizens to address their queries directly. Several governments across the world have taken actions to contain the pandemic of misinformation, yet measures are required to prevent such communication complications.