Serious adverse event following immunization and thromboembolic events associated with COVID19 vaccination: An analysis of nationwide causality assessment from India.

BACKGROUND: Vaccines against the COVID-19 pandemic were introduced in late 2020. The present study has been conducted to study the serious Adverse Events Following Immunization (AEFIs) reported for COVID-19 vaccines from India. METHODS: Secondary data analysis of the causality assessment reports for the 1112 serious AEFIs published by the Ministry of Health & Family Welfare, Government of India, was conducted. For the current analysis, all the reports published till 29.03.2022 were included. The primary outcome variables analyzed were the consistent causal association and the thromboembolic events. RESULTS: The majority of the serious AEFIs assessed were either coincidental (578, 52%) or vaccine product related (218, 19.6%). All the serious AEFIs were reported among the Covishield (992, 89.2%) and COVAXIN (120, 10.8%) vaccines. Among these, 401 (36.1%) were deaths, and 711 (63.9%) were hospitalized and recovered. On adjusted analysis, females, the younger age group and non-fatal AEFIs showed a statistically significant consistent causal association with COVID-19 vaccination. Thromboembolic events were reported among 209 (18.8%) of the analyzed participants, with a significant association with higher age and case fatality rate. CONCLUSION: Deaths reported under serious AEFIs were found to have a relatively lower consistent causal relationship with the COVID-19 vaccines than the recovered hospitalizations in India. No consistent causal association was found between the thromboembolic events and the type of COVID-19 vaccine administered in India.

Evaluation of risk factors associated with SARS-CoV-2 transmission.

OBJECTIVE: Coronavirus disease 2019 (COVID-19) has caused high morbidity and mortality worldwide. Since there is not enough evidence of risk factors of SARS-CoV-2 transmission, this study aimed to evaluate them. METHODS: This survey-based study was conducted across 66 countries from May to November 2020 among suspected and confirmed individuals with COVID-19. The stepwise AIC method was utilized to determine the optimal multivariable logistic regression to explore predictive factors of SARS-CoV-2 transmission. RESULTS: Among 2372 respondents who participated in the study, there were 1172 valid responses. The profession of non-healthcare-worker (OR: 1.77, 95%CI: 1.04-3.00, p = .032), history of SARS-CoV or MERS-CoV infection (OR: 4.78, 95%CI: 2.34-9.63, p < .001), higher frequency of contact with colleagues (OR: 1.17, 95%CI: 1.01-1.37, p = .041), and habit of hugging when greeting (OR: 1.25, 95%CI: 1.00-1.56, p = .049) were associated with an increased risk of contracting COVID-19. Current smokers had a lower likelihood of having COVID-19 compared to former smokers (OR: 5.41, 95%CI: 1.93-17.49, p = .002) or non-smokers (OR: 3.69, 95%CI: 1.48-11.11, p = .01). CONCLUSIONS: Our study suggests several risk factors for SARS-CoV-2 transmission including the profession of non-healthcare workers, history of other coronavirus infections, frequent close contact with colleagues, the habit of hugging when greeting, and smoking status.

Since there is not enough evidence of risk factors of SARS-CoV-2 transmission, this study aimed to evaluate them. The risk of SARS-CoV-2 infection was higher among non-healthcare workers and among those who had a history of being tested positive for SARS-CoV or MERS-CoV before the COVID-19 outbreak. The habit of frequent contact with colleagues or hugging when greeting significantly increased the risk of being infected with SARS-CoV-2. The current smokers had a lower risk of getting infected with SARS-CoV-2 than others who had a habit of smoking tobacco in the past or who had never smoked.

Lockdowns, Community Mobility Patterns, and COVID-19: A Retrospective Analysis of Data from 16 Countries.

OBJECTIVES: During the coronavirus disease 2019 (COVID-19) pandemic, countries around the world framed specific laws and imposed varying degrees of lockdowns to ensure the maintenance of physical distancing. Understanding changes in temporal and spatial mobility patterns may provide insights into the dynamics of this infectious disease. Therefore, we assessed the efficacy of lockdown measures in 16 countries worldwide by analyzing the relationship between community mobility patterns and the doubling time of COVID-19. METHODS: We performed a retrospective record-based analysis of population-level data on the doubling time for COVID-19 and community mobility. The doubling time for COVID-19 was calculated based on the laboratory-confirmed cases reported daily over the study period (from February 15 to May 2, 2020). Principal component analysis (PCA) of six mobility pattern-related variables was conducted. To explain the magnitude of the effect of mobility on the doubling time, a finite linear distributed lag model was fitted. The k-means clustering approach was employed to identify countries with similar patterns in the significant co-efficient of the mobility index, with the optimal number of clusters derived using Elbow's method. RESULTS: The countries analyzed had reduced mobility in commercial and social places. Reduced mobility had a significant and favorable association with the doubling time of COVID-19-specifically, the greater the mobility reduction, the longer the time taken for the COVID-19 cases to double. CONCLUSIONS: COVID-19 lockdowns achieved the immediate objective of mobility reduction in countries with a high burden of cases.

Psychological distress and burnout among healthcare worker during COVID-19 pandemic in India-A cross-sectional study.

BACKGROUND: COVID-19 has inundated the entire world disrupting the lives of millions of people. The pandemic has stressed the healthcare system of India impacting the psychological status and functioning of health care workers. The aim of this study is to determine the burnout levels and factors associated with the risk of psychological distress among healthcare workers (HCW) engaged in the management of COVID 19 in India. METHODS: A cross-sectional study was conducted from 1 September 2020 to 30 November 2020 by telephonic interviews using a web-based Google form. Health facilities and community centres from 12 cities located in 10 states were selected for data collection. Data on socio-demographic and occupation-related variables like age, sex, type of family, income, type of occupation, hours of work and income were obtained was obtained from 967 participants, including doctors, nurses, ambulance drivers, emergency response teams, lab personnel, and others directly involved in COVID 19 patient care. Levels of psychological distress was assessed by the General health Questionnaire -GHQ-5 and levels of burnout was assessed using the ICMR-NIOH Burnout questionnaire. Multivariable logistic regression analysis was performed to identify factors associated with the risk of psychological distress. The third quartile values of the three subscales of burnout viz EE, DP and PA were used to identify burnout profiles of the healthcare workers. RESULTS: Overall, 52.9% of the participants had the risk of psychological distress that needed further evaluation. Risk of psychological distress was significantly associated with longer hours of work (≥ 8 hours a day) (AOR = 2.38, 95% CI(1.66-3.41), income≥20000(AOR = 1.74, 95% CI, (1.16-2.6); screening of COVID-19 patients (AOR = 1.63 95% CI (1.09-2.46), contact tracing (AOR = 2.05, 95% CI (1.1-3.81), High Emotional exhaustion score (EE ≥16) (AOR = 4.41 95% CI (3.14-6.28) and High Depersonalisation score (DP≥7) (AOR = 1.79, 95% CI (1.28-2.51)). About 4.7% of the HCWs were overextended (EE>18); 6.5% were disengaged (DP>8) and 9.7% HCWs were showing signs of burnout (high on all three dimensions). CONCLUSION: The study has identified key factors that could have been likely triggers for psychological distress among healthcare workers who were engaged in management of COVID cases in India. The study also demonstrates the use of GHQ-5 and ICMR-NIOH Burnout questionnaire as important tools to identify persons at risk of psychological distress and occurrence of burnout symptoms respectively. The findings provide useful guide to planning interventions to mitigate mental health problems among HCW in future epidemic/pandemic scenarios in the country.

Telemedicine practice guidelines in India: Global implications in the wake of the COVID-19 pandemic.

Telemedicine is the delivery of healthcare services from a distance, by use of information and communication technology. There have been no statutory regulations or official guidelines in India specific for telemedicine practice and allied matters so far. For the first time, the government of India released telemedicine practice guidelines for Registered Medical Practitioners on March 25, 2020, amid the COVID-19 outbreak. This review would initiate the discussion on the features of the guidelines, their limitations, and their significance in times of the COVID-19 pandemic. The guidelines are with a restricted scope for providing medical consultation to patients, excluding other aspects of telemedicine such as research and evaluation and the continuing education of healthcare workers. The guidelines have elaborated on the eligibility for practicing Telemedicine in India, the modes and types of teleconsultations, delved into the doctor-patient relationship, consent, and management protocols, and touched upon the data security and privacy aspects of Teleconsultation. After releasing the guidelines, the telescreening of the public for COVID-19 symptoms is being advocated by the government of India. COVID-19 National Teleconsultation Centre (CoNTeC) has been initiated, which connects the doctors across India to All India Institute of Medical Sciences (AIIMS) in real-time for accessing expert guidance on the treatment of the COVID-19 patients.

La telemedicina es la prestación de servicios de salud a distancia, mediante el uso de las TIC. No ha habido regulaciones legales o pautas oficiales en India específicas para la práctica de la telemedicina y asuntos relacionados hasta el momento. Por primera vez, el gobierno de India publicó pautas de práctica de telemedicina para médicos registrados el 25 de marzo de 2020, en medio del brote de COVID­19. Esta revisión iniciaría la discusión sobre las características de las guías, sus limitaciones y su importancia en tiempos de la pandemia de COVID­19. Las pautas tienen un alcance restringido para brindar consultas médicas a los pacientes, excluyendo otros aspectos de la telemedicina, como la investigación y la evaluación y la educación continua de los trabajadores de la salud. Las pautas han detallado la elegibilidad para practicar Telemedicina en India, los modos y tipos de teleconsultas, profundizado en la relación médico­paciente, consentimiento y protocolos de gestión, y tocado los aspectos de seguridad y privacidad de datos de Teleconsulta. Después de publicar las pautas, el gobierno de la India aboga por la teleevaluación del público para detectar síntomas de COVID­19. Se ha iniciado el Centro Nacional de Teleconsulta COVID­19 (CoNTeC), que conecta a los médicos de toda la India con el Instituto de Ciencias Médicas de toda la India (AIIMS) en tiempo real para acceder a la orientación de expertos sobre el tratamiento de los pacientes con COVID­19.

Population Mobility, Lockdowns, and COVID-19 Control: An Analysis Based on Google Location Data and Doubling Time from India.

OBJECTIVES: Physical distancing is a control measure against coronavirus disease 2019 (COVID-19). Lockdowns are a strategy to enforce physical distancing in urban areas, but they are drastic measures. Therefore, we assessed the effectiveness of the lockdown measures taken in the world's second-most populous country, India, by exploring their relationship with community mobility patterns and the doubling time of COVID-19. METHODS: We conducted a retrospective analysis based on community mobility patterns, the stringency index of lockdown measures, and the doubling time of COVID-19 cases in India between February 15 and April 26, 2020. Pearson correlation coefficients were calculated between the stringency index, community mobility patterns, and the doubling time of COVID-19 cases. Multiple linear regression was applied to predict the doubling time of COVID-19. RESULTS: Community mobility drastically fell after the lockdown was instituted. The doubling time of COVID-19 cases was negatively correlated with population mobility patterns in outdoor areas (r = -0.45 to -0.58). The stringency index and outdoor mobility patterns were also negatively correlated (r = -0.89 to -0.95). Population mobility patterns (R2 = 0.67) were found to predict the doubling time of COVID-19, and the model's predictive power increased when the stringency index was also added (R2 = 0.73). CONCLUSIONS: Lockdown measures could effectively ensure physical distancing and reduce short-term case spikes in India. Therefore, lockdown measures may be considered for tailored implementation on an intermittent basis, whenever COVID-19 cases are predicted to exceed the health care system's capacity to manage.

Severe Acute Respiratory Syndrome Coronavirus 2 and Dengue Virus Co-infection: Indian Perspectives.

Severe acute respiratory syndrome Coronavirus 2 (SARS CoV-2) and Dengue virus (DENV) Coinfection can be a pertinent issue in a country like India, where Dengue is endemic, and Coronavirus disease 19 (COVID-19) is also reported from all states of the country. The coinfection of these viruses has already been reported in different dengue-endemic countries like Singapore, Thailand, and Bangladesh. The outcome and the dynamics of each of the diseases may be altered in the presence of coinfection. We highlighted the critical characteristic similarities and differences between COVID-19 and Dengue infection & the specific point, which may challenge diagnosing and managing these coinfections. COVID-19 and Dengue coinfection can be deadly in combination with an atypical presentation, providing diagnostic and therapeutic challenges. A high index of suspicion, early recognition of symptoms, and warning signs are vital to prevent double jeopardy.

Perception and attitude towards COVID-19 vaccination: A preliminary online survey from India.

CONTEXT: Coronavirus disease 2019 (COVID-19) has rapidly become a global pandemic taking more than 1.7 million lives. While many developed countries are starting their vaccination drive, India is not far behind but still not much is known about the willingness to get a vaccination in India. AIMS: To find out the perception and attitude toward vaccination against COVID-19 among the adult population of India in order to know the proportion of people who are willing to get vaccinated against COVID-19. METHOD: A cross-sectional study was conducted between October 26, 2020 and November 10, 2020. Data were collected online using a self-administered and semi-structured questionnaire among adults aged 18 years or more in India via web-based links. The minimum sample size was calculated by considering the proportion of willingness to take the vaccination as 50%, 95% confidence interval, and 5% alpha error-the calculated sample size was 384. However, 467 participants completed the survey during the study period. Data were analyzed using SPSS version 21. RESULTS: A total of 467 participants responded, out of which 329 (70.44%) showed a willingness to get vaccinated and 138 (29.55%) were hesitant to get vaccinated against COVID-19. Only 49.4% believed that people can be protected by the vaccine; 63.1% of the people were willing to get their children vaccinated; and 59.31% felt the vaccine should be free for all. CONCLUSIONS: The pan India survey conducted online revealed that approximately 3 in 10 adults were not willing to get vaccinated against COVID-19. This can guide policymakers to make multipronged efforts to increase the willingness to get a vaccination against COVID-19.

Psychosocial impact of COVID-19 pandemic on healthcare workers in India & their perceptions on the way forward - A qualitative study.

Background & objectives: The healthcare system across the world has been overburdened due to the COVID-19 pandemic impacting healthcare workers (HCWs) in different ways. The present study provides an insight into the psychosocial challenges faced by the HCWs related to their work, family and personal well-being and the associated stigmas. Additionally, the coping mechanisms adopted by them and their perceptions on the interventions to address these challenges were also explored. Methods: A qualitative study was conducted between September and December 2020 through in-depth telephonic interviews using an interview guide among 111 HCWs who were involved in COVID-19 management across 10 States in India. Results: HCWs report major changes in work-life environment that included excessive workload with erratic timings accentuated with the extended duration of inconvenient personal protection equipment usage, periods of quarantine and long durations of separation from family. Family-related issues were manifold; the main challenge being separated from family, the challenge of caregiving, especially for females with infants and children, and fears around infecting family. Stigma from the community and peers fuelled by the fear of infection was manifested through avoidance and rejection. Coping strategies included peer, family support and the positive experiences manifested as appreciation and recognition for their contribution during the pandemic. Interpretation & conclusions: The study demonstrates the psychological burden of HCWs engaged with COVID-19 care services. The study findings point to need-based psychosocial interventions at the organizational, societal and individual levels. This includes a conducive working environment involving periodic evaluation of the HCW problems, rotation of workforce by engaging more staff, debunking of false information, community and HCW involvement in COVID sensitization to allay fears and prevent stigma associated with COVID-19 infection/transmission and finally need-based psychological support for them and their families.

Universal checklist for COVID-19 control measures: consensus via a Delphi method

Declaration/announcement of emergency status Launching a public website for guidelines and information Establishing a 'coronavirus task force'/ expert board Conducting training programmes Government financial assistance for citizens/taxpayers Equal protection for immigrants/foreigners Regulation and stabilisation of food prices and daily necessities Require company to pay full salary to quarantined/isolated people Financial support to frontline cleaners, toilet attendants and security employees Free testing Free treatment Production/procurement of supplies (such as surgical masks, gloves, ventilators, or goods) Enhance production of sanitisers Enhancing hospital capacities (beds) Designating which hospitals can receive COVID-19 patients Equipping university housings, hotels, sports stadiums or building temporary hospitals to be ready to receive patients Guidelines for treatment of COVID-19 Application of telemedicine Research: Established in-house PCR assay Development of quick test kits Successfully identifying SARS-CoV-2 genes Launching clinical trial treatment of COVID-19 Launching vaccination development Call for research related to epidemiology, prevention and control measures Call for development or reuse of efficient low cost of PPE and medical devices such as ventilators Call for development of a new treatment or new drug discovery, PPE and medical devices such as ventilators Call for non-academic industries to join the research or give funds Box 1. Prohibition of group gathering more than (x) number of people in public places Physical distancing from each other in public (2 metres between individuals) Closure of schools Working from home Shelter in place Closure of public areas Closure of services Closure of public transport Closure of city/area hotspots (separating areas, restriction of movement) Protection of vulnerable people (elderly, people with suppressed immunities or relevant comorbidities: hypertension, heart disease, kidney disease, liver disease, chronic respiratory disease, diabetes, obesity) Supporting e-learning for students/tele-workplace Preventive and containment measures: Universal checklist of COVID-19 control measures (Continued) Using a medical declaration when having respiratory symptoms or close contact with a new confirmed patient Isolation for all confirmed cases (F0) Disinfect the workplace of the newly detected patient Closure of workplace of the newly detected patient Isolation/quarantine for patients with respiratory symptoms (flu-like illness) Isolation/quarantine for suspected cases with negative RT-PCR (who had contact with confirmed patients or came from hotspots) Protection of hospitals at outpatient units Protection of healthcare workers Guidelines for each type of health worker to prevent crosstransmission Guidelines for performing aerosol generation Guidelines regarding reuse of masks/PPE for healthcare workers Guidelines on disposal of dead bodies Guidelines for home care Guidelines for community service (public transportation, food delivery, postal, volunteer services) Additional items:

Inflammatory syndrome experiments related with COVID-19

According to the first SARS-CoV-2 pandemic reports that signs and symptoms were identified less commonly among pediatric patients than adults. The multisystem inflammatory syndrome in children (MISC), which is linked to COVID -19, was first identified in April. Fever, presented in two or more organ systems at the same time, altered inflammatory criteria, and experimental or epidemiological proof of SARSCoV-2 infection are all symptoms of MIS-C. Kawasaki disorder, toxic shock syndrome, and secondary hemophagocytic lymph histiocytosis syndrome/macrophage activation syndrome all have certain clinical elements in common with MIS-C. The clinical features of seven cases of MIS-C handled in the Republic of Moldova are described in this study.

Prediction of COVID-19 Outbreaks Using Google Trends in India: A Retrospective Analysis.

OBJECTIVE: Considering the rising menace of coronavirus disease 2019 (COVID-19), it is essential to explore the methods and resources that might predict the case numbers expected and identify the locations of outbreaks. Hence, we have done the following study to explore the potential use of Google Trends (GT) in predicting the COVID-19 outbreak in India. METHODS: The Google search terms used for the analysis were "coronavirus", "COVID", "COVID 19", "corona", and "virus". GTs for these terms in Google Web, News, and YouTube, and the data on COVID-19 case numbers were obtained. Spearman correlation and lag correlation were used to determine the correlation between COVID-19 cases and the Google search terms. RESULTS: "Coronavirus" and "corona" were the terms most commonly used by Internet surfers in India. Correlation for the GTs of the search terms "coronavirus" and "corona" was high (r > 0.7) with the daily cumulative and new COVID-19 cases for a lag period ranging from 9 to 21 days. The maximum lag period for predicting COVID-19 cases was found to be with the News search for the term "coronavirus", with 21 days, i.e., the search volume for "coronavirus" peaked 21 days before the peak number of cases reported by the disease surveillance system. CONCLUSION: Our study revealed that GTs may predict outbreaks of COVID-19, 2 to 3 weeks earlier than the routine disease surveillance, in India. Google search data may be considered as a supplementary tool in COVID-19 monitoring and planning in India.