Gender differences in COVID-19 knowledge, risk perception, and public stigma among the general community: Findings from a nationwide cross-sectional study in India.

Introduction: Individual and community characteristics predictive of knowledge, perception, and attitude on COVID-19, specifically on gender, have not been adequately explored. Objective: To examine the gender differences in COVID-19 knowledge, self-risk perception and public stigma among the general community and to understand other socio-demographic factors which were predictive of them. Method: A nationally representative cross-sectional multi-centric survey was conducted among adult individuals(≥18 yrs) from the community member (N = 1978) from six states and one union territory of India between August 2020 to February 2021. The participants were selected using systematic random sampling. The data were collected telephonically using pilot-tested structured questionnaires and were analyzed using STATA. Gender-segregated multivariable analysis was conducted to identify statistically significant predictors (p < 0.05) of COVID-19-related knowledge, risk perception, and public stigma in the community. Results: Study identified significant differences between males and females in their self-risk perception (22.0% & 18.2% respectively) and stigmatizing attitude (55.3% & 47.1% respectively). Highly educated males and females had higher odds of having COVID-19 knowledge (aOR: 16.83: p < 0.05) than illiterates. Highly educated women had higher odds of having self-risk perception (aOR: 2.6; p < 0.05) but lower public stigma [aOR: 0.57; p < 0.05]. Male rural residents had lower odds of having self-risk perception and knowledge [aOR: 0.55; p < 0.05 & aOR: 0.72; p < 0.05] and female rural residents had higher odds of having public stigma [aOR: 1.36; p < 0.05]. Conclusion: Our study findings suggest the importance of considering thegender differentials and their background, education status and residential status in designing effective interventions to improve knowledge and reduce risk perception and stigma in the community about COVID-19.

Molecular evolutionary model based on phylogenetic and mutation analysis of SARS-CoV-2 spike protein sequences from Asian countries: A phylogenomic approach.

The lethal pathogenic severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection has caused the COVID-19 pandemic, posing serious risks to people. The clove-like spike (S) protein that distinguishes coronaviruses from other viruses is important for viral pathogenicity, evolution, and transmission. The investigation of the unique structural mutations of the SARS-CoV-2 spike protein among 34 Asian countries, as well as the resulting phylogenetic relationship, provided critical information in understanding the pathogenesis. This can be utilized for the discovery of possible treatments and vaccine development. The current study analyzed and depicted phylogenetic and evolutionary models useful for understanding SARS-CoV-2 human-human transmission dynamics in Asian regions with shared land borders. Further, integrated bioinformatics analysis was performed to predict the pathogenic potential and stability of 53 mutational positions among 34 coronavirus strains. Mutations at positions N969K, D614G and S884F have deleterious effects on protein function. These findings are crucial because the Asian mutations could potentially provide a vaccine candidate with co-protection against all SARS-CoV-2 strains. This region is vulnerable because of the high population density and the volume of domestic and international travel for business and tourism. These discoveries would also aid in the development of plans for governments and the general populace to implement all required biocontainment protocols common to all countries.

Challenges in Accessing and Delivering Maternal and Child Health Services during the COVID-19 Pandemic: A Cross-Sectional Rapid Survey from Six States of India.

BACKGROUND/OBJECTIVES: Globally, the COVID-19 pandemic and its prevention and control policies have impacted maternal and child health (MCH) services. This study documents the challenges faced by patients in accessing MCH services, and the experiences of health care providers in delivering those services during the COVID-19 outbreak, explicitly focusing on the lockdown period in India. METHODS: A cross-sectional study (rapid survey) was conducted in 18 districts from 6 states of India during March to June, 2020. The sample size included 540 MCH patients, 18 gynaecologists, 18 paediatricians, 18 district immunisation officers and 108 frontline health workers. Bivariate analysis and multivariable analysis were used to assess the association between sociodemographic characteristics, and challenges faced by the patients. RESULTS: More than one-third of patients (n = 212; 39%) reported that accessing MCH services was a challenge during the lockdown period, with major challenges being transportation-related difficulties (n = 99; 46%) unavailability of hospital-based services (n = 54; 23%) and interrupted outreach health services (n = 39; 18.4%). The supply-side challenges mainly included lack of infrastructural preparedness for outbreak situations, and a shortage of human resources. CONCLUSIONS/RECOMMENDATIONS: A holistic approach is required that focuses on both preparedness and response to the outbreak, as well reassignment and reinforcement of health care professionals to continue catering to and maintaining essential MCH services during the pandemic.

Development & validation of scales to assess stigma related to COVID-19 in India.

Background & objectives: COVID-19 pandemic has triggered social stigma towards individuals affected and their families. This study describes the process undertaken for the development and validation of scales to assess stigmatizing attitudes and experiences among COVID-19 and non-COVID-19 participants from the community. Methods: COVID-19 Stigma Scale and Community COVID-19 Stigma Scale constituting 13 and six items, respectively, were developed based on review of literature and news reports, expert committee evaluation and participants' interviews through telephone for a multicentric study in India. For content validity, 61 (30 COVID-19-recovered and 31 non-COVID-19 participants from the community) were recruited. Test-retest reliability of the scales was assessed among 99 participants (41 COVID-19 recovered and 58 non-COVID-19). Participants were administered the scale at two-time points after a gap of 7-12 days. Cronbach's alpha, overall percentage agreement and kappa statistics were used to assess internal consistency and test-retest reliability. Results: Items in the scales were relevant and comprehensible. Both the scales had Cronbach's α above 0.6 indicating moderate-to-good internal consistency. Test-retest reliability assessed using kappa statistics indicated that for the COVID-19 Stigma Scale, seven items had a moderate agreement (0.4-0.6). For the Community COVID-19 Stigma Scale, four items had a moderate agreement. Interpretation & conclusions: Validity and reliability of the two stigma scales indicated that the scales were comprehensible and had moderate internal consistency. These scales could be used to assess COVID-19 stigma and help in the development of appropriate stigma reduction interventions for COVID-19 infected, and mitigation of stigmatizing attitudes in the community.

Omicron BA.2 lineage predominance in severe acute respiratory syndrome coronavirus 2 positive cases during the third wave in North India.

Background: Recent studies on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) reveal that Omicron variant BA.1 and sub-lineages have revived the concern over resistance to antiviral drugs and vaccine-induced immunity. The present study aims to analyze the clinical profile and genome characterization of the SARS-CoV-2 variant in eastern Uttar Pradesh (UP), North India. Methods: Whole-genome sequencing (WGS) was conducted for 146 SARS-CoV-2 samples obtained from individuals who tested coronavirus disease 2019 (COVID-19) positive between the period of 1 January 2022 and 24 February 2022, from three districts of eastern UP. The details regarding clinical and hospitalized status were captured through telephonic interviews after obtaining verbal informed consent. A maximum-likelihood phylogenetic tree was created for evolutionary analysis using MEGA7. Results: The mean age of study participants was 33.9 ± 13.1 years, with 73.5% accounting for male patients. Of the 98 cases contacted by telephone, 30 (30.6%) had a travel history (domestic/international), 16 (16.3%) reported having been infected with COVID-19 in past, 79 (80.6%) had symptoms, and seven had at least one comorbidity. Most of the sequences belonged to the Omicron variant, with BA.1 (6.2%), BA.1.1 (2.7%), BA.1.1.1 (0.7%), BA.1.1.7 (5.5%), BA.1.17.2 (0.7%), BA.1.18 (0.7%), BA.2 (30.8%), BA.2.10 (50.7%), BA.2.12 (0.7%), and B.1.617.2 (1.3%) lineages. BA.1 and BA.1.1 strains possess signature spike mutations S:A67V, S:T95I, S:R346K, S:S371L, S:G446S, S:G496S, S:T547K, S:N856K, and S:L981F, and BA.2 contains S:V213G, S:T376A, and S:D405N. Notably, ins214EPE (S1- N-Terminal domain) mutation was found in a significant number of Omicron BA.1 and sub-lineages. The overall Omicron BA.2 lineage was observed in 79.5% of women and 83.2% of men. Conclusion: The current study showed a predominance of the Omicron BA.2 variant outcompeting the BA.1 over a period in eastern UP. Most of the cases had a breakthrough infection following the recommended two doses of vaccine with four in five cases being symptomatic. There is a need to further explore the immune evasion properties of the Omicron variant.

Factors associated with COVID-19 stigma during the onset of the global pandemic in India: A cross-sectional study

Objective To assess factors associated with COVID-19 stigmatizing attitudes in the community and stigma experiences of COVID-19 recovered individuals during first wave of COVID-19 pandemic in India. Methods A cross-sectional study was conducted in 18 districts located in 7 States in India during September 2020 to January 2021 among adults > 18 years of age selected through systematic random sampling. Data on socio demographic and COVID-19 knowledge were collected from 303 COVID-19 recovered and 1,976 non-COVID-19 infected individuals from community using a survey questionnaire. Stigma was assessed using COVID-19 Stigma Scale and Community COVID-19 Stigma Scale developed for the study. Informed consent was sought from the participants. Univariate and multivariate binary logistic regression analysis were conducted. Results Half of the participants (51.3%) from the community reported prevalence of severe stigmatizing attitudes toward COVID-19 infected while 38.6% of COVID-19 recovered participants reported experiencing severe stigma. Participants from the community were more likely to report stigmatizing attitudes toward COVID-19 infected if they were residents of high prevalent COVID-19 zone (AOR: 1.5;CI: 1.2–1.9), staying in rural areas (AOR: 1.5;CI:1.1–1.9), belonged to the age group of 18–30 years (AOR: 1.6;CI 1.2–2.0), were male (AOR: 1.6;CI: 1.3–1.9), illiterate (AOR: 2.7;CI: 1.8–4.2), or living in Maharashtra (AOR: 7.4;CI: 4.8–11.3). COVID-19 recovered participants had higher odds of experiencing stigma if they had poor knowledge about COVID-19 transmission (AOR: 2.8;CI: 1.3–6.3), were staying for 6–15 years (AOR: 3.24;CI: 1.1–9.4) in the current place of residence or belonged to Delhi (AOR: 5.3;CI: 1.04–26.7). Conclusion Findings indicated presence of stigmatizing attitudes in the community as well as experienced stigma among COVID-19 recovered across selected study sites in India during the first wave of COVID-19 pandemic. Study recommends timely dissemination of factual information to populations vulnerable to misinformation and psychosocial interventions for individuals affected by stigma.

Genome Sequencing Reveals a Mixed Picture of SARS-CoV-2 Variant of Concern Circulation in Eastern Uttar Pradesh, India.

Uttar Pradesh is the densely populated state of India and is the sixth highest COVID-19 affected state with 22,904 deaths recorded on November 12, 2021. Whole-genome sequencing (WGS) is being used as a potential approach to investigate genomic evolution of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus. In this study, a total of 87 SARS-CoV-2 genomes-49 genomes from the first wave (March 2020 to February 2021) and 38 genomes from the second wave (March 2021 to July 2021) from Eastern Uttar Pradesh (E-UP) were sequenced and analyzed to understand its evolutionary pattern and variants against publicaly available sequences. The complete genome analysis of SARS-CoV-2 during the first wave in E-UP largely reported transmission of G, GR, and GH clades with specific mutations. In contrast, variants of concerns (VOCs) such as Delta (71.0%) followed by Delta AY.1 (21.05%) and Kappa (7.9%) lineages belong to G clade with prominent signature amino acids were introduced in the second wave. Signature substitution at positions S:L452R, S:P681R, and S:D614G were commonly detected in the Delta, Delta AY.1, and Kappa variants whereas S:T19R and S:T478K were confined to Delta and Delta AY.1 variants only. Vaccine breakthrough infections showed unique mutational changes at position S:D574Y in the case of the Delta variant, whereas position S:T95 was conserved among Kappa variants compared to the Wuhan isolate. During the transition from the first to second waves, a shift in the predominant clade from GH to G clade was observed. The identified spike protein mutations in the SARS-CoV-2 genome could be used as the potential target for vaccine and drug development to combat the effects of the COVID-19 disease.

COVID-19 and waste management in Indian scenario: challenges and possible solutions.

The outbreak of COVID-19 pandemic has created havoc all across the globe causing exponential casualties and tremendous health and economic loss. With increasing COVID-19 cases, the amount of biomedical waste has increased manifolds making more people vulnerable to the pandemic. The developing and underdeveloped countries are already facing the challenges of waste management, and the waste generated during the pandemic scenario has added to the already existing challenges. The improper waste management practices need to be corrected; otherwise, the world will be facing a new disaster that could be termed as 'waste disaster'. The increase in COVID-19-associated waste (CAW) quantity and their availability in the environment will result in their easy approach to other organisms, which will possibly increase the potential risk of food chain contamination. Some of the countries have already started to make backup plans and are struggling to overcome the 'waste disaster'. In light of the limited knowledge available on the mutational properties and possible hosts of this newly emerged COVID-19, there is a great demand to have an efficient strategy to prevent the environment from further contamination in India. The necessity of the prevailing time is to create a more efficient, automatic, mechanized, and well-modified waste management system for handling the present situation and delaying the projected waste disaster in the near future in the era of COVID-19. The article aims to address the issues that originated from waste discharges, their potential sources along with possible sustainable solutions.

SARS-CoV-2 antibody seroprevalence in India, August-September, 2020: findings from the second nationwide household serosurvey.

BACKGROUND: The first national severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) serosurvey in India, done in May-June, 2020, among adults aged 18 years or older from 21 states, found a SARS-CoV-2 IgG antibody seroprevalence of 0·73% (95% CI 0·34-1·13). We aimed to assess the more recent nationwide seroprevalence in the general population in India. METHODS: We did a second household serosurvey among individuals aged 10 years or older in the same 700 villages or wards within 70 districts in India that were included in the first serosurvey. Individuals aged younger than 10 years and households that did not respond at the time of survey were excluded. Participants were interviewed to collect information on sociodemographics, symptoms suggestive of COVID-19, exposure history to laboratory-confirmed COVID-19 cases, and history of COVID-19 illness. 3-5 mL of venous blood was collected from each participant and blood samples were tested using the Abbott SARS-CoV-2 IgG assay. Seroprevalence was estimated after applying the sampling weights and adjusting for clustering and assay characteristics. We randomly selected one adult serum sample from each household to compare the seroprevalence among adults between the two serosurveys. FINDINGS: Between Aug 18 and Sept 20, 2020, we enrolled and collected serum samples from 29 082 individuals from 15 613 households. The weighted and adjusted seroprevalence of SARS-CoV-2 IgG antibodies in individuals aged 10 years or older was 6·6% (95% CI 5·8-7·4). Among 15 084 randomly selected adults (one per household), the weighted and adjusted seroprevalence was 7·1% (6·2-8·2). Seroprevalence was similar across age groups, sexes, and occupations. Seroprevalence was highest in urban slum areas followed by urban non-slum and rural areas. We estimated a cumulative 74·3 million infections in the country by Aug 18, 2020, with 26-32 infections for every reported COVID-19 case. INTERPRETATION: Approximately one in 15 individuals aged 10 years or older in India had SARS-CoV-2 infection by Aug 18, 2020. The adult seroprevalence increased approximately tenfold between May and August, 2020. Lower infection-to-case ratio in August than in May reflects a substantial increase in testing across the country. FUNDING: Indian Council of Medical Research.

COVIDScreen: explainable deep learning framework for differential diagnosis of COVID-19 using chest X-rays.

COVID-19 has emerged as a global crisis with unprecedented socio-economic challenges, jeopardizing our lives and livelihoods for years to come. The unavailability of vaccines for COVID-19 has rendered rapid testing of the population instrumental in order to contain the exponential rise in cases of infection. Shortage of RT-PCR test kits and delays in obtaining test results calls for alternative methods of rapid and reliable diagnosis. In this article, we propose a novel deep learning-based solution using chest X-rays which can help in rapid triaging of COVID-19 patients. The proposed solution uses image enhancement, image segmentation, and employs a modified stacked ensemble model consisting of four CNN base-learners along with Naive Bayes as meta-learner to classify chest X-rays into three classes viz. COVID-19, pneumonia, and normal. An effective pruning strategy as introduced in the proposed framework results in increased model performance, generalizability, and decreased model complexity. We incorporate explainability in our article by using Grad-CAM visualization in order to establish trust in the medical AI system. Furthermore, we evaluate multiple state-of-the-art GAN architectures and their ability to generate realistic synthetic samples of COVID-19 chest X-rays to deal with limited numbers of training samples. The proposed solution significantly outperforms existing methods, with 98.67% accuracy, 0.98 Kappa score, and F-1 scores of 100, 98, and 98 for COVID-19, normal, and pneumonia classes, respectively, on standard datasets. The proposed solution can be used as one element of patient evaluation along with gold-standard clinical and laboratory testing.

Strategies and perspectives to develop SARS-CoV-2 detection methods and diagnostics.

To develop diagnostics and detection methods, current research is focussed on targeting the detection of coronavirus based on its RNA. Besides the RNA target, research reports are coming to develop diagnostics by targeting structure and other parts of coronavirus. PCR based detection system is widely used and various improvements in the PCR based detection system can be seen in the recent research reports. This review will discuss multiple detection methods for coronavirus for developing appropriate, reliable, and fast alternative techniques. Considering the current scenario of COVID-19 diagnostics around the world and an urgent need for the development of reliable and cheap diagnostic, various techniques based on CRISPR technology, antibody, MIP, LAMP, microarray, etc. should be discussed and tried.