Prevalence of probable post-COVID cardiac sequelae and its health seeking behaviour among health care workers: A cross-sectional analytical study

Background Post-COVID Sequelae are considered as the signs and symptoms that develop during or after an infection consistent with COVID-19 which continue for more than 12 weeks and are not explained by alternative diagnosis. The prevalence of post-COVID cardiac sequelae ranges from 2% to 71% across the globe and it is reported to be around 22% in India. With this background, the study was conducted to assess the prevalence of probable post-COVID cardiac sequelae (PCCS) and delay in health-seeking for post-COVID cardiac sequelae among healthcare workers. Methods A facility-based cross-sectional study was conducted among health workers and students in a medical educational institute in Karnataka from May 2022 to July 2022. Health workers and students who had a past history of COVID-19 during the COVID pandemic were included in the study. Socio-demographic details, clinical profile, symptoms of post-COVID cardiac sequelae, and health-seeking behavior were collected. Data were collected in Epicollect5 and analyzed using STATA statistical software. The prevalence of probable PCCS was expressed with 95% confidence interval. Univariate binomial logistic regression was done to assess the determinants of probable post-COVID sequelae. Results A total of 336 health workers were included in the study with a mean (SD) age of 25.6 (8.6) years. A majority (68.2%) of them were females and only 25 (7.4%) belonged to the age group of 45-60 years. The prevalence of probable post-COVID cardiac sequelae among health workers and medical students was 11.9% (95% CI: 8.76 - 15.7). Among the 40 participants who had probable post-COVID cardiac sequelae, 55% (95% CI: 40% - 70%) were not evaluated further which was their treatment-seeking behavior. Females, hypertensive individuals, and those who had moderate-severe disease during acute COVID-19 disease were at higher risk of developing probable post-COVID cardiac sequelae. Conclusion Around one out of ten individuals had experienced probable post-COVID cardiac sequelae, but only half of them got evaluated for it. An appropriate screening program for post-COVID cardiac sequelae needs to be implemented along with awareness-raising activities about long COVID to prevent the morbidity and mortality associated with it.

Community Dynamics and Engagement Strategies in Establishing Demographic Development and Environmental Surveillance Systems: A Multi-Site Report from India.

BACKGROUND: Six diverse Demographic Development and Environmental Surveillance System (DDESS) sites were established in urban slum, urban resettlement, peri-urban, rural, and tribal areas located in Northern, North-East, Eastern, and Southern regions of India from June 2020 to March 2022. Understanding the community dynamics and engaging people in the community is critically important in the process of establishing DDESS. We ascertained the barriers, challenges, and facilitators during the establishment of multiple DDESS sites across India. METHODS: This was a cross-sectional descriptive mixed-methods study. RESULTS: Multiple barriers and challenges encountered were reported in the process of community engagement (CE), such as geographical inaccessibility, language barriers, adverse weather, non-responsiveness due to perceived lack of individual benefit or financial gain, fear of contracting COVID-19, COVID-19 vaccine hesitancy, etc. Facilitators in the CE process were pre-existing links with the community, constitution of community advisory boards, community need assessment, concomitant delivery of outreach health services, and skill-building facilities. CONCLUSION: Most community barriers in the development of DDESS sites in resource-limited settings can be overcome through a multipronged approach, including effective community engagement by focusing on demonstrating trust at the local level, enlisting community mobilization and support, utilizing pre-existing community linkages, initiating community diagnosis, and meeting perceived community health needs.

Inactivated whole-virion vaccine BBV152/Covaxin elicits robust cellular immune memory to SARS-CoV-2 and variants of concern.

BBV152 is a whole-virion inactivated vaccine based on the Asp614Gly variant. BBV152 is the first alum-imidazoquinolin-adjuvanted vaccine authorized for use in large populations. Here we characterized the magnitude, quality and persistence of cellular and humoral memory responses up to 6 months post vaccination. We report that the magnitude of vaccine-induced spike and nucleoprotein antibodies was comparable with that produced after infection. Receptor binding domain-specific antibodies declined against variants in the order of Alpha (B.1.1.7; 3-fold), Delta (B.1.617.2; 7-fold) and Beta (B.1.351; 10-fold). However, pseudovirus neutralizing antibodies declined up to 2-fold against the Delta followed by the Beta variant (1.7-fold). Vaccine-induced memory B cells were also affected by the Delta and Beta variants. The SARS-CoV-2-specific multicytokine-expressing CD4+ T cells were found in ~85% of vaccinated individuals. Only a ~1.3-fold reduction in efficacy was observed in CD4+ T cells against the Beta variant. We found that antigen-specific CD4+ T cells were present in the central memory compartment and persisted for at least up to 6 months post vaccination. Vaccine-induced CD8+ T cells were detected in ~50% of individuals. Importantly, the vaccine was capable of inducing follicular T helper cells that exhibited B-cell help potential. These findings show that inactivated vaccine BBV152 induces robust immune memory to SARS-CoV-2 and variants of concern that persists for at least 6 months after vaccination.

Health-Seeking Behaviour for Childhood Ailments in Caregivers of Under-Five Children in an Urban Resettlement Colony in Delhi, India.

This explorative qualitative study assesses the health-seeking behaviour for childhood ailments in caregivers of under-five children in a low-income neighbourhood in Delhi, India during July-September 2021. A total of 17 caregivers (mothers) of eight male and nine female under-five children were enrolled, with the mother being the caregiver in most (94%) cases. Caregivers consulted on common childhood ailments from multiple sources, including family, neighbours, healthcare providers (both licensed and unlicensed), frontline workers, and local pharmacists. The internet was often used as a source of child health information due to its ease of access but often "confused" caregivers due to the presence of too much information. Health-seeking behaviour of caregivers for childhood ailments could range from self-medication, local pharmacist dispensing, and private and public healthcare providers. Factors that influenced preference for the healthcare facility or provider were accessibility issues (waiting time, queuing), perceived physician competence, and associated out-of-pocket expenses. Caregivers reported dissatisfaction with government health facilities because of shorter operational hours, overcrowding, suboptimal sanitation, queuing with limited seating arrangements, and occasionally discourteous health staff. Self-medication and over-the-counter use of antibiotics was high due to a lack of awareness of the challenges of antibiotic resistance or any perceived side effects. Preference for unlicensed practitioners for medical treatment was low and based on long-term familial beliefs and acceptance. However, traditional practitioners enjoyed a high level of trust in the community from shared cultural values, enjoining attenuation of the perceived non-biological agents of childhood illnesses through non-medical supernatural interventions.

Perceptions of Good Health and Impact of COVID-19 Among Adolescents in a Low-Income Urban Agglomerate in Delhi, India: A Qualitative Study.

Adolescents constitute 16% of the global population and are susceptible to adverse health and illness from substance abuse, unhealthy diet, physical inactivity, and high-risk sexual behaviors. We conducted this study to assess the perceptions of good health, health-seeking behavior, and health service utilization among adolescents living in a low-income urban neighborhood after the second wave of the COVID-19 pandemic. A total of 23 adolescents, including 12 males and 11 females, were interviewed. Adolescents' perceived body image and size considerations apart from functioning at an optimum physical capacity as the principal attributes of good health, which was possible through the intake of a healthy diet and exercise. Adolescents were likely to be aware of the addiction potential and risk of cancer from using tobacco and alcohol, but attitudes towards eschewing their use were ambivalent. Adolescents perceived themselves as lacking access to reliable, adequate, and validated sources of sexual and reproductive health information. Knowledge and utilization of adolescent health services in this area were negligible, suggestive of the need to strengthen these services and improve the program outreach.

Second Wave of the COVID-19 Pandemic in Delhi, India: High Seroprevalence Not a Deterrent?

Background We report the findings of a large follow-up, community-based, cross-sectional serosurvey and correlate it with the coronavirus disease (COVID-19) test-positivity rate and the caseload observed between the peaks of the first and the second wave of the COVID-19 pandemic in Delhi, India. Methodology Individuals aged five and above were recruited from 274 wards of the state (population approximately 19.6 million) from January 11 to January 22, 2021. A total of 100 participants each were included from all wards for a net sample size of approximately 28,000. A multistage sampling technique was employed to select participants for the household serosurvey. Anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) immunoglobulin (IgG) antibodies were detected by using the VITROS® (Ortho Clinical Diagnostics, Raritan, NJ, USA) assay (90% sensitivity, 100% specificity). Results Antibody positivity was observed in 14,298 (50.76%) of 28,169 samples. The age, sex, and district population-weighted seroprevalence of the SARS-CoV-2 IgG was 50.52% (95% confidence interval [CI] = 49.94-51.10), and after adjustment for assay characteristics, it was 56.13% (95% CI = 55.49-56.77). On adjusted analysis, participants aged ≥50 years, of female gender, housewives, having ever lived in containment zones, urban slum dwellers, and diabetes or hypertensive patients had significantly higher odds of SARS-CoV-2 antibody positivity. The peak infection rate and the test-positivity rate since October 2020 were initially observed in mid-November 2020, with a subsequent steep declining trend, followed by a period of persistently low case burden lasting until the first week of March 2021. This was followed by a steady increase followed by an exponential surge in infections from April 2021 onward culminating in the second wave of the pandemic. Conclusions The presence of infection-induced immunity from SARS-CoV-2 even in more than one in two people can be ineffective in protecting the population. Despite such high seroprevalence, population susceptibility to COVID-19 can be accentuated by variants of concern having the ability for rapid transmission and depletion of antibody levels with the threat of recurrent infections, signifying the need for mass vaccination.

Clinical presentation and mortality risk factors for COVID-19 among diabetic patients in a tertiary care center in South India.

BACKGROUND: Non-communicable diseases (NCD) like hypertension, diabetes, cardiovascular and cerebrovascular diseases are the most common comorbidities among COVID-19 patients. The clinical presentation and mortality pattern of COVID-19 are different for patients with comorbidities and without comorbidities. OBJECTIVE: To determine the clinical presentation of COVID-19 and risk factors for COVID-19 mortality among diabetic patients in a tertiary care hospital in South India. METHODS: A record-based cross-sectional study was conducted by reviewing the case records of COVID-19 patients admitted for treatment from June 2020 to September 2020 in a tertiary care centre in South India. Potential risk factors for COVID-19 mortality were analysed using univariate binomial logistic regression, generalized linear models (GLM) with the Poisson distribution. Survival curves were made using the Kaplan-Meier method. RESULTS: Out of 200 COVID-19 patients with diabetes with a mean (SD) age of 56.1 (11.8) years, 61% were men. The median survival time was slightly lesser in male COVID-19 patients (15 days) as compared to female patients (16 days). The risk of mortality among COVID-19 patients with diabetes is increased for patients who presented with breathlessness (aRR = 4.5 (95% CI: 2.3-8.8)), had positive history of smoking (aRR = 1.9 (95% CI: 1.1-3.8)), who had CKD (aRR = 1.8 (95% CI: 1.1-2.8)) and who had cardiac illness (aRR = 1.6 (95% CI: 0.9-2.7)). CONCLUSION: Diabetes patients with COVID-19 need to be given additional care and monitoring especially if they present with breathlessness, positive history of smoking, cardiac illness and, CKD. Public health campaigns and health education activities to control smoking is needed to reduce the COVID-19 mortality in diabetes patients.

The seroprevalence of severe acute respiratory syndrome coronavirus 2 in Delhi, India: a repeated population-based seroepidemiological study.

BACKGROUND: Three rounds of a repeated cross-sectional serosurvey to estimate the change in seroprevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) were conducted from August to October 2020 in the state of Delhi, India, in the general population ≥5 y of age. METHODS: The selection of participants was through a multistage sampling design from all 11 districts and 280 wards of the city-state, with multistage allocation proportional to population size. The blood samples were screened using immunoglobulin G (IgG) enzyme-linked immunosorbent assay kits. RESULTS: We observed a total of 4267 (N=150 46), 4311 (N=17 409) and 3829 (N=15 015) positive tests indicative of the presence of IgG antibody to SARS-CoV-2 during the August, September and October 2020 serosurvey rounds, respectively. The adjusted seroprevalence declined from 28.39% (95% confidence interval [CI] 27.65 to 29.14) in August to 24.08% (95% CI 23.43 to 24.74) in September and 24.71% (95% CI 24.01 to 25.42) in October. On adjusted analysis, participants with lower per capita income, living in slums or overcrowded households and those with diabetes comorbidity had significantly higher statistical odds of having antibody positivity (p<0.01). CONCLUSIONS: Nearly one in four residents in Delhi, India ≥5 y of age had the SARS-CoV-2 infection during August-October 2020.

Evolving an ethical framework for Covid-19 management in India.

The Covid-19 pandemic has caused millions of cases and deaths worldwide and has caused a massive global economic contraction. Governments, policymakers, and medical professionals have been confronted with several complex bioethical dilemmas during these exceptional circumstances. In developing countries like India, having a large population base, inadequate preexisting public health infrastructure, and a multi-level government system with complex administrative mechanisms imposes enormous barriers and challenges in the effective and ethical management of the pandemic. Furthermore, endemic corruption, limited bureaucratic and organisational accountability, and weak oversight, especially among stakeholders in the vast private and non-government health and allied services sector, complicate the assessment of their adherence to ethical public health practices.

Outcomes among 10,314 hospitalized COVID-19 patients at a tertiary care government hospital in Delhi, India.

A significant proportion of patients with coronavirus disease 2019 (COVID-19) require timely hospitalization to reduce the risk of complications and mortality. We describe the trends of the age and gender stratified outcomes among hospitalized COVID-19 patients with moderate to severe illness at the largest dedicated tertiary care COVID-19 government hospital in New Delhi, India. A retrospective cohort study through secondary data analysis from in-patient hospital data of patients admitted from April 1 to November 15, 2020 was conducted. The data of 10,314 laboratory-confirmed patients with COVID-19 was analyzed, of which 8899 (86.28%) were discharged after recovery, and 1415 (13.72%) died. The mean (SD) age of the hospitalized patients was 46.43 (18.74) years (n = 10,309) including 6031 (58.50%) male and 4278 (41.50%) female patients (n = 10,309). On bivariate analysis, increasing age was associated with significantly higher odds of mortality in both gender (p < .001). The mortality rate in female patients was lower (11.92%) compared with male patients (15.75%) (p = .675). However, elderly women had the highest odds of mortality (p < .001), indicating the possible role of delayed health seeking behavior, secondary to familial, and social neglect. Mortality in the patients with COVID-19 also occurred early after admission suggesting rapid deterioration, delayed reporting by patients, or their late referral from other health facilities. However, the overall statewide recovery rate showed steady improvement since the onset of the pandemic. In contrast, the recovery rate among the moderate-severe cases that were hospitalized at this tertiary care center during the same period reflected a lower nonspecific zigzag pattern indicating limited effectiveness of the COVID-19 treatment regimens.

Longitudinal Serology of SARS-CoV-2-Infected Individuals in India: A Prospective Cohort Study.

Clinical and epidemiological characteristics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are now widely available, but there are few data regarding longitudinal serology in large cohorts, particularly those from low-income and middle-income countries. We established an ongoing prospective cohort of 3,840 SARS-CoV-2-positive individuals according to RT-PCR in the Delhi-National Capital Region of India to document clinical and immunological characteristics during illness and convalescence. The immunoglobulin G (IgG) responses to the receptor binding domain (RBD) and nucleocapsid were assessed at 0 to 7 days, 10 to 28 days, and 6 to 10 weeks after infection. The clinical predictors of seroconversion were identified by multivariable regression analysis. The seroconversion rates during the postinfection windows of 0 to 7 days, 10 to 28 days, and 6 to 10 weeks were 46%, 84.7%, and 85.3%, respectively (N = 743). The proportion with a serological response increased with the severity of coronavirus disease 2019 (COVID-19). All participants with severe disease, 89.6% with mild to moderate infection, and 77.3% of asymptomatic participants had IgG antibodies to the RBD antigen. The threshold values for the nasopharyngeal viral RNA RT-PCR of a subset of asymptomatic and symptomatic seroconverters were comparable (P = 0.48) to those of nonseroconverters (P = 0.16) (N = 169). This is the first report of longitudinal humoral immune responses to SARS-CoV-2 over a period of 10 weeks in South Asia. The low seropositivity of asymptomatic participants and differences between assays highlight the importance of contextualizing the understanding of population serosurveys.

Clinical characteristic and epidemiological features of SARS CoV -2 disease patients from a COVID 19 designated Hospital in New Delhi.

SARS CoV -2 infection is rapidly evolving as a serious global pandemic. The present study describes the clinical characteristics of SARS CoV-2 infection patients. The Samples were subjected to RT - PCR or Rapid Antigen test for diagnosis of SARS CoV- 2. A cohort of 3745 patients with confirmed diagnosis of SARS CoV -2 infection in a tertiary care center in New Delhi, India were included in this study. Data was collected from offline and online medical records over a period of six months. Amongst 3745 SARS CoV -2 infected patients, 2245 (60%) were symptomatic and 1500 (40%) were asymptomatic. Most common presenting symptom was cough (49.3%) followed febrile episodes (47.1%), breathlessness (42.7%) and sore throat (35.1%). Cough along with breathlessness (24.1) was the most common combination of symptoms followed by fever with cough (22.7). The most common comorbidity found among symptomatic group was diabetes (42.5%) followed by hypertension (21.4%) and chronic kidney disease (18%). Comorbidities like diabetes mellitus, chronic diseases of lungs, heart and kidneys were found to be common in symptomatic group and this was found to be statistically significant (p<0.05). COVID-19 is an evolving disease and data from our study help in understanding the clinic-epidemiological profile of patients. This article is protected by copyright. All rights reserved.

Development of a Fast SARS-CoV-2 IgG ELISA, Based on Receptor-Binding Domain, and Its Comparative Evaluation Using Temporally Segregated Samples From RT-PCR Positive Individuals.

SARS-CoV-2 antibody detection assays are crucial for gathering seroepidemiological information and monitoring the sustainability of antibody response against the virus. The SARS-CoV-2 Spike protein's receptor-binding domain (RBD) is a very specific target for anti-SARS-CoV-2 antibodies detection. Moreover, many neutralizing antibodies are mapped to this domain, linking antibody response to RBD with neutralizing potential. Detection of IgG antibodies, rather than IgM or total antibodies, against RBD is likely to play a larger role in understanding antibody-mediated protection and vaccine response. Here we describe a rapid and stable RBD-based IgG ELISA test obtained through extensive optimization of the assay components and conditions. The test showed a specificity of 99.79% (95% CI: 98.82-99.99%) in a panel of pre-pandemic samples (n = 470) from different groups, i.e., pregnancy, fever, HCV, HBV, and autoantibodies positive. Test sensitivity was evaluated using sera from SARS-CoV-2 RT-PCR positive individuals (n = 312) and found to be 53.33% (95% CI: 37.87-68.34%), 80.47% (95% CI: 72.53-86.94%), and 88.24% (95% CI: 82.05-92.88%) in panel 1 (days 0-13), panel 2 (days 14-20) and panel 3 (days 21-27), respectively. Higher sensitivity was achieved in symptomatic individuals and reached 92.14% (95% CI: 86.38-96.01%) for panel 3. Our test, with a shorter runtime, showed higher sensitivity than parallelly tested commercial ELISAs for SARS-CoV-2-IgG, i.e., Euroimmun and Zydus, even when equivocal results in the commercial ELISAs were considered positive. None of the tests, which are using different antigens, could detect anti-SARS-CoV-2 IgGs in 10.5% RT-PCR positive individuals by the fourth week, suggesting the lack of IgG response.

Design and rationale of an intelligent algorithm to detect BuRnoUt in HeaLthcare workers in COVID era using ECG and artificiaL intelligence: The BRUCEE-LI study.

BACKGROUND: There is no large contemporary data from India to see the prevalence of burnout in HCWs in covid era. Burnout and mental stress is associated with electrocardiographic changes detectable by artificial intelligence (AI). OBJECTIVE: The present study aims to estimate the prevalence of burnout in HCWs in COVID-19 era using Mini Z-scale and to develop predictive AI model to detect burnout in HCWs in COVID-19 era. METHODS: This is an observational and cross-sectional study to evaluate the presence of burnout in HCWs in academic tertiary care centres of North India in the COVID-19 era. At least 900 participants will be enrolled in this study from four leading premier government-funded/public-private centres of North India. Each study centre will be asked to recruit HCWs by approaching them through various listed ways for participation in the study. Interested participants after initial screening and meeting the eligibility criteria, will be asked to fill the questionnaire (having demographic and work related with Mini Z questionnaire) to assess burnout. The healthcare workers will include physicians at all levels of training, nursing staff and paramedical staff who are involved directly or indirectly in COVID-19 care. The analysis of the raw electrocardiogram (ECG) data and development of algorithm using convolutional neural networks (CNN) will be done by experts. CONCLUSIONS: In Summary, we propose that ECG data generated from the people with burnout can be utilized to develop AI-enabled model to predict the presence of stress and burnout in HCWs in COVID-19 era.

COVID-19 and tuberculosis: A mathematical model based forecasting in Delhi, India.

BACKGROUND: There is emerging evidence that patients with Latent Tuberculosis Infection(LTBI) and Tuberculosis(TB) disease have an increased risk of the SARS-CoV-2 infection and predisposition towards developing severe COVID-19 pneumonia. In this study we attempted to estimate the number of TB patients infected with SARS-CoV-2 and have severe disease during the COVID-19 epidemic in Delhi, India. METHODS: Susceptible-Exposed-Infectious-Recovered (SEIR) model was used to estimate the number of COVID-19 cases in Delhi. Assuming the prevalence of TB in Delhi to be 0.55%, 53% of SARS-CoV2 infected TB cases to present with severe disease we estimated the number of SARS-CoV2 infected TB cases and the number of severe patients. The modelling used estimated R0 for two scenarios, without any intervention and with public health interventions. RESULTS: We observed that the peak of SARS-CoV-2-TB co-infected patients would occur on the 94th day in absence of public health interventions and on 138th day in presence of interventions. There could be 20,880 SARS-CoV-2 infected TB cases on peak day of epidemic when interventions are implemented and 27,968 cases in the absence of intervention. Among them, there could be 14,823 patients with severe disease when no interventions are implemented and 11,066 patients with severe disease in the presence of intervention. CONCLUSION: The importance of primary prevention measures needs to be emphasized especially in TB patients. The TB treatment centres and hospitals needs to be prepared for early diagnosis and management of severe COVID-19 in TB patients.