Health System's Response and Impact of COVID-19 on Health Services, Providers, and Seekers: A Rapid Review at the Wake of the Pandemic (preprint)

Background: The Covid-19 pandemic abruptly disrupted global healthcare systems, necessitating rapid adaptations. This study evaluates the impact on health systems and services in the aftermath of the first wave in the Indian context. It analyses the disruptions, adaptive measures, and changes made, as well as the challenges faced by healthcare providers and seekers. Valuable insights from this study will enhance the resilience and preparedness of healthcare systems for future challenges. Methods: The eligible studies included primary studies conducted in the Indian context that explore the impact of COVID-19 on health services provision, utilisation, and the well-being of healthcare providers and seekers. Electronic searches were conducted in six databases: PubMed, MEDLINE, Embase, Global Health, CINAHL, and the WHO database on COVID-19. The results were analysed using detailed narrative synthesis. Results: The review includes 38 articles, incorporating a total of 22,502 subjects. There has been a substantial impact on health service provision, particularly in outpatient departments (OPD) (n=19) and elective services (n=16), while emergency services continued at sub-optimal levels (n=20). Various adaptations and changes were implemented in precautionary measures, protocols, staff allocation and training, usage of personal protective equipment (PPE), preoperative, operative, and postoperative measures, as well as physical infrastructure and resources. Depression and stress (n=14), fear of contracting the infection (n=6), stigmatisation (n=5), and financial repercussions (n=5) significantly affected the mental health of healthcare providers, and healthcare seekers also faced significant challenges (n=11). Conclusion: The study reveals COVID-19's substantial impact on health services. The healthcare system responded by quickly adjusting staff management, resource allocation, and infection prevention measures. The study also highlights the mental health challenges faced by healthcare providers and the concerns of healthcare seekers regarding delays and suboptimal care. Looking ahead, the findings underscore the importance of preparedness for future pandemics, including improved healthcare infrastructure, resource optimisation, and comprehensive protocols. Lessons learned from COVID-19 should inform strategies to mitigate disruptions and ensure the well-being of healthcare providers and seekers in future outbreaks.

Unraveling antiviral efficacy of multifunctional immunomodulatory triterpenoids against SARS-COV-2 targeting virus-specific enzymes (preprint)

The coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus (SARS-CoV-2) may be over, but its variants continue to emerge, and patients with mild symptoms having long COVID is still under investigation. SARS-CoV-2 infection leading to elevated cytokine levels and suppressed immune responses set off cytokine storm, fatal systemic inflammation, tissue damage, and multi-organ failure. Thus, drug molecules against virus-specific proteins that play a role in viral inflammation and simultaneous act on the host pathways participating in viral inflammation, will provide an effective antiviral therapy against emerging variants of concern. Evolutionarily conserved papain-like protease (PLpro) and main protease (Mpro) play an indispensable role in the virus life cycle and immune evasion. Direct-acting antivirals targeting both these viral proteases represent an attractive antiviral strategy that is also expected to reduce viral inflammation. The present study has evaluated the antiviral and anti-inflammatory potential of natural triterpenoids: azadirachtin, withanolide_A, and isoginkgetin. These molecules inhibit the Mpro and PLpro proteolytic activities with half-maximal inhibitory concentrations (IC50) values ranging from 1.42 to 32.7 M. Isothermal titration calorimetry (ITC) analysis validated the binding of these compounds to Mpro and PLpro. As expected, the two compounds, withanolide_A and azadirachtin exhibit potent antiviral activity with half-maximum effective concentration (EC50) values of 21.73 M and 31.19 M, respectively. The anti-inflammatory role of azadirachtin and withanolide_A when assessed using HEK293T cells were found to significantly reduce the levels of CXCL10, TNF, IL6, and IL8 cytokines, which are elevated in severe cases of COVID-19. Interestingly, azadirachtin and withanolide_A were also found to rescue the decreased type-I interferon response (IFN-1). The results of this study clearly highlight the role of triterpenoids as effective antiviral molecules that target SARS-CoV-2 specific enzymes and also host immune pathways involved in virus mediated inflammation.

Assessing Usability and Accessibility of Indian Tourism Websites for Visually Impaired

The tourism industry cannot ignore the needs of people with special needs. Providing accessible tourism is essential because of social and legal obligations, but also because they have large business opportunities. These people with special needs face challenges in every social, economic, and digital environment. One of the greatest barriers they face is the lack of accessible and usable information on the Internet, which thwarts their travel plans. This research is aimed at identifying the usability and accessibility status of official state tourism websites of India. The usability evaluation was done on various web quality parameters using automated online tools. The accessibility evaluation was done to check the compliance of Web Content Accessibility Guideline version 2.0 by the tourism website using the automated tool TAW. Further manual inspection was applied to identify accessibility and language options on the webpage. The result revealed that Indian state tourism websites had low usability and accessibility status, and they need much improvement to make them accessible to people with special needs.

Discovery of anti-SARS-CoV-2 molecules using structure-assisted repurposing approach targeting N-protein (preprint)

SARS-CoV-2 nucleocapsid protein (N-protein) is a virus specific multitasking protein, responsible for recognition and encapsidation of the viral genome. The N-terminal domain (NTD) of N-protein has a major role of packaging viral RNA genome into a long helical nucleocapsid structure. In this study, using structure-based drug repurposing strategy, small molecules from a FDA approved, natural product, and LOPAC1280 libraries have been virtually screened against the RNA binding pocket of SARS-CoV-2 NTD and twelve candidate molecules with high binding affinity were identified. Highly sensitive isothermal titration calorimetry (ITC) method was utilized to confirm binding of these molecules to purified NTD protein. In vitro cell-based SARS-CoV-2 antiviral assays demonstrate that nine of these identified molecules are highly efficacious in inhibiting virus replication with half maximal effective concentration (EC50) ranging from 0.98 M-10 M. FDA approved drugs: Telmisartan, an angiotensin II type 1 (AT1) receptor antagonist used in the management of hypertension and Bictegravir, an HIV-1 integrase inhibitor showed significant inhibitory activity against SARS-CoV-2 with a EC50 values of 1.02 M and 8.11 M respectively. Additionally, Bisdemethoxycurcumin, a natural analogue of curcumin and MCC-555, an anti-diabetic drug exerted antiviral activity with EC50 values of 1.64 M and 4.26 M, respectively. Taken together, this is the first report of drug molecules targeting the NTD of SARS-CoV-2 N-protein and the data presented in this study exhibit high potential for development of COVID-19 therapy based on drug repurposing

Predictors of COVID-19 Vaccine Confidence: Findings from Slums of Four Major Metro Cities of India.

There are limited studies on COVID vaccine confidence at the household level in urban slums, which are at high risk of COVID-19 transmission due to overcrowding and poor living conditions. The objective was to understand the reasons influencing COVID-19 vaccine confidence, in terms of barriers and enablers faced by communities in urban slums and informal settlements in four major metro cities in India. A mixed method approach was adopted, where in field studies were conducted during April-May 2021. First, a survey of at least 50 subjects was conducted among residents of informal urban settlements who had not taken any dose of the COVID-19 vaccine in Mumbai, Bengaluru, Kolkata and Delhi; second, a short interview with five subjects who had taken at least one dose of the vaccine in each of the four cities to understand the factors that contributed to positive behaviour and, finally, an in-depth interview of at least 3 key informants in each city to ascertain the vaccination pattern in the communities. The reasons were grouped under contextual, individual/group and vaccine/vaccination specific issues. The most frequent reason (27.7%) was the uncertainty of getting the vaccine. The findings show the need for increasing effectiveness of awareness campaigns, accessibility and the convenience of vaccination, especially among vulnerable groups, to increase the uptake.

New onset rheumatoid arthritis with refractory hyper-eosinophilia associated with inactivated COVID-19 vaccine (preprint)

COVID-19 vaccines are considered one of the primary strategies for countering the pandemic. While mRNA based and viral vector-based vaccines have been predominantly used, inactivated SARS-CoV-2 vaccines are being manufactured in countries such as China and India. Post approval, rare but serious adverse events such as myocarditis and stroke have been observed with mRNA based and viral vectored COVID-19 vaccines. Inactivated vaccines in general have shown better tolerability in clinical trials. Here we report the first case of new-onset seropositive rheumatoid arthritis (RA) with rheumatoid nodules and refractory reactive eosinophilia within two weeks of receiving an inactivated COVID-19 vaccine (COVAXIN).

CT Image Synthesis Using Weakly Supervised Segmentation and Geometric Inter-Label Relations For COVID Image Analysis (preprint)

While medical image segmentation is an important task for computer aided diagnosis, the high expertise requirement for pixelwise manual annotations makes it a challenging and time consuming task. Since conventional data augmentations do not fully represent the underlying distribution of the training set, the trained models have varying performance when tested on images captured from different sources. Most prior work on image synthesis for data augmentation ignore the interleaved geometric relationship between different anatomical labels. We propose improvements over previous GAN-based medical image synthesis methods by learning the relationship between different anatomical labels. We use a weakly supervised segmentation method to obtain pixel level semantic label map of images which is used learn the intrinsic relationship of geometry and shape across semantic labels. Latent space variable sampling results in diverse generated images from a base image and improves robustness. We use the synthetic images from our method to train networks for segmenting COVID-19 infected areas from lung CT images. The proposed method outperforms state-of-the-art segmentation methods on a public dataset. Ablation studies also demonstrate benefits of integrating geometry and diversity.

One-Stop Serum Assay Identifies COVID-19 Disease Severity and Vaccination Responses.

SARS-CoV-2 has caused over 100,000,000 cases and almost 2,500,000 deaths globally. Comprehensive assessment of the multifaceted antiviral Ab response is critical for diagnosis, differentiation of severity, and characterization of long-term immunity, especially as COVID-19 vaccines become available. Severe disease is associated with early, massive plasmablast responses. We developed a multiplex immunoassay from serum/plasma of acutely infected and convalescent COVID-19 patients and prepandemic and postpandemic healthy adults. We measured IgA, IgG, and/or IgM against SARS-CoV-2 nucleocapsid (N), spike domain 1 (S1), S1-receptor binding domain (RBD) and S1-N-terminal domain. For diagnosis, the combined [IgA + IgG + IgM] or IgG levels measured for N, S1, and S1-RBD yielded area under the curve values ≥0.90. Virus-specific Ig levels were higher in patients with severe/critical compared with mild/moderate infections. A strong prozone effect was observed in sera from severe/critical patients-a possible source of underestimated Ab concentrations in previous studies. Mild/moderate patients displayed a slower rise and lower peak in anti-N and anti-S1 IgG levels compared with severe/critical patients, but anti-RBD IgG and neutralization responses reached similar levels at 2-4 mo after symptom onset. Measurement of the Ab responses in sera from 18 COVID-19-vaccinated patients revealed specific responses for the S1-RBD Ag and none against the N protein. This highly sensitive, SARS-CoV-2-specific, multiplex immunoassay measures the magnitude, complexity, and kinetics of the Ab response and can distinguish serum Ab responses from natural SARS-CoV-2 infections (mild or severe) and mRNA COVID-19 vaccines.

Triage of potential COVID-19 patients from chest X-ray images using hierarchical convolutional networks.

The current COVID-19 pandemic has motivated the researchers to use artificial intelligence techniques for a potential alternative to reverse transcription-polymerase chain reaction due to the limited scale of testing. The chest X-ray (CXR) is one of the alternatives to achieve fast diagnosis, but the unavailability of large-scale annotated data makes the clinical implementation of machine learning-based COVID detection difficult. Another issue is the usage of ImageNet pre-trained networks which does not extract reliable feature representations from medical images. In this paper, we propose the use of hierarchical convolutional network (HCN) architecture to naturally augment the data along with diversified features. The HCN uses the first convolution layer from COVIDNet followed by the convolutional layers from well-known pre-trained networks to extract the features. The use of the convolution layer from COVIDNet ensures the extraction of representations relevant to the CXR modality. We also propose the use of ECOC for encoding multiclass problems to binary classification for improving the recognition performance. Experimental results show that HCN architecture is capable of achieving better results in comparison with the existing studies. The proposed method can accurately triage potential COVID-19 patients through CXR images for sharing the testing load and increasing the testing capacity.

Elevated SARS-CoV-2 Antibodies Distinguish Severe Disease in Early COVID-19 Infection (preprint)

BackgroundSARS-CoV-2 has caused over 36,000,000 cases and 1,000,000 deaths globally. Comprehensive assessment of the multifaceted anti-viral antibody response is critical for diagnosis, differentiation of severe disease, and characterization of long-term immunity. Initial observations suggest that severe disease is associated with higher antibody levels and greater B cell/plasmablast responses. A multi-antigen immunoassay to define the complex serological landscape and clinical associations is essential. MethodsWe developed a multiplex immunoassay and evaluated serum/plasma from adults with RT-PCR-confirmed SARS-CoV-2 infections during acute illness (N=52) and convalescence (N=69); and pre-pandemic (N=106) and post-pandemic (N=137) healthy adults. We measured IgA, IgG, and/or IgM against SARS-CoV-2 Nucleocapsid (N), Spike domain 1 (S1), receptor binding domain (S1-RBD) and S1-N-terminal domain (S1-NTD). ResultsTo diagnose infection, the combined [IgA+IgG+IgM] or IgG for N, S1, and S1-RBD yielded AUC values -0.90 by ROC curves. From days 6-30 post-symptom onset, the levels of antigen-specific IgG, IgA or [IgA+IgG+IgM] were higher in patients with severe/critical compared to mild/moderate infections. Consistent with excessive concentrations of antibodies, a strong prozone effect was observed in sera from severe/critical patients. Notably, mild/moderate patients displayed a slower rise and lower peak in anti-N and anti-S1 IgG levels compared to severe/critical patients, but anti-RBD IgG and neutralization responses reached similar levels at 2-4 months. ConclusionThis SARS-CoV-2 multiplex immunoassay measures the magnitude, complexity and kinetics of the antibody response against multiple viral antigens. The IgG and combined-isotype SARS-CoV-2 multiplex assay is highly diagnostic of acute and convalescent disease and may prognosticate severity early in illness. One Sentence SummaryIn contrast to patients with moderate infections, those with severe COVID-19 develop prominent, early antibody responses to S1 and N proteins.

The aging whole blood transcriptome reveals a potential role of FASLG in COVID-19 (preprint)

The risk for severe illness from COVID-19 increases with age as older patients are at the highest risk. Although it is still unclear whether the virus is blood-transmitted, the viral RNA is detected in serum. Identifying how Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) interacts with specific blood components during aging is expected to guide proper therapies. Considering that all human coronavirus require host cellular molecules to promote infection, we investigated the aging whole blood transcriptome from the Genotype-Tissue Expression (GTEx) database to explore differentially expressed genes (DEGs) translated into proteins potentially interacting with viral proteins. From a total of 22 DEGs in aged blood, five genes (FASLG, CTSW, CTSE, VCAM1, and BAG3) changed expression during aging. These age-related genes are involved in immune response, inflammation, cell component and cell adhesion, and platelet activation/aggregation. Both males and females older than 50 overexpress FASLG compared with younger adults (20-30 years old), possibly inducing a hyper-inflammatory cascade that activates specific immune cells. Furthermore, the expression of cathepsins (CTSW and CTSE) and the anti-apoptotic co-chaperone molecule BAG3 was significantly increased throughout aging in both gender. By exploring publicly available Single-Cell RNA-Sequencing (scRNA-Seq) data on peripheral blood of SARS-CoV-2-infected patients, we found FASLG and CTSW expressed mainly in natural killer (NK) cells and CD8+ (cytotoxic) T lymphocytes whereas BAG3 was expressed in CD4+ T cells, naive T cells, and CD14+ monocytes. The increased expression of FASLG in blood during aging may explain why older patients are more prone to severe acute viral infection complications. These results indicate FASLG as a prognostic candidate and potential therapeutic target for more aggressive clinical manifestation of COVID-19.

Triage of Potential COVID-19 Patients from Chest X-ray Images using Hierarchical Convolutional Networks (preprint)

The current COVID-19 pandemic has motivated the researchers to use artificial intelligence techniques for a potential alternative to reverse transcription-polymerase chain reaction (RT-PCR) due to the limited scale of testing. The chest X-ray (CXR) is one of the alternatives to achieve fast diagnosis but the unavailability of large-scale annotated data makes the clinical implementation of machine learning-based COVID detection difficult. Another issue is the usage of ImageNet pre-trained networks which does not extract reliable feature representations from medical images. In this paper, we propose the use of hierarchical convolutional network (HCN) architecture to naturally augment the data along with diversified features. The HCN uses the first convolution layer from COVIDNet followed by the convolutional layers from well-known pre-trained networks to extract the features. The use of the convolution layer from COVIDNet ensures the extraction of representations relevant to the CXR modality. We also propose the use of ECOC for encoding multiclass problems to binary classification for improving the recognition performance. Experimental results show that HCN architecture is capable of achieving better results in comparison to the existing studies. The proposed method can accurately triage potential COVID-19 patients through CXR images for sharing the testing load and increasing the testing capacity.

Extrafollicular B cell responses correlate with neutralizing antibodies and morbidity in COVID-19.

A wide spectrum of clinical manifestations has become a hallmark of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) COVID-19 pandemic, although the immunological underpinnings of diverse disease outcomes remain to be defined. We performed detailed characterization of B cell responses through high-dimensional flow cytometry to reveal substantial heterogeneity in both effector and immature populations. More notably, critically ill patients displayed hallmarks of extrafollicular B cell activation and shared B cell repertoire features previously described in autoimmune settings. Extrafollicular activation correlated strongly with large antibody-secreting cell expansion and early production of high concentrations of SARS-CoV-2-specific neutralizing antibodies. Yet, these patients had severe disease with elevated inflammatory biomarkers, multiorgan failure and death. Overall, these findings strongly suggest a pathogenic role for immune activation in subsets of patients with COVID-19. Our study provides further evidence that targeted immunomodulatory therapy may be beneficial in specific patient subpopulations and can be informed by careful immune profiling.

In Silico Guided Drug Repurposing to Combat SARS-CoV-2 by Targeting Mpro, the Key Virus Specific Protease (preprint)

The reemergence of SARS-CoV named, as SARS-CoV-2 has been highly infectious and able to infect a large population around the globe. The World Health Organization (WHO) has declared this SARS-CoV-2 associated Coronavirus Disease 2019 (COVID-19) as pandemic. SARS-CoV-2 genome is translated into polyproteins and has been processed by its protease enzymes. 3CLprotease is named as main protease (Mpro) enzyme which cleaves nsp4-nsp16. This crucial role of Mpro makes this enzyme a prime and promising antiviral target. The drug repurposing is a fast alternative method than the discovery of novel antiviral molecules. We have used high-throughput virtual screening approach to examine FDA approved LOPAC1280 library against Mpro. Primary screening have identified few potential drug molecule for the target among which 10 molecules were studied further. Molecular docking of selected molecules was done to detailed study about their binding energy and binding modes. Positively, Etoposide, BMS_195614, KT185, Idarubicin and WIN_62577 were found interacting with substrate binding pocket of Mpro with higher binding energy. These molecules are being advanced by our group for in vitro and in vivo testing to study the efficacy of identified drugs. As per our understanding, these molecules have the potential to efficiently interrupt the viral life cycle and may reduce or eliminate the expeditious outspreading of SARS-CoV-2.