Strategy for COVID-19 vaccination in India: the country with the second highest population and number of cases

Next-Generation Adenoviral Vector-Based Vaccines for Severe Acute Respiratory Syndrome Coronavirus-2

This review systematically revises adenovirus (Ad) biology, vector structure, immune responses, and currently available Ad vector COVID-19 vaccines. It analyzes the challenges associated with the Ad vector-based vaccines, including preexisting vector immunity and other side effects. Moreover, this review explores novel and innovative strategies to overcome these constraints for developing next-generation vaccines for broad protection to cover emerging SARS-CoV-2 variants. The future refinement of Ad vaccine platforms will be pivotal in achieving durable immunity against emerging variants for global preparedness.

Post COVID Condition and Long-Term COVID-19 Impact on Hepatic Decompensation and Survival in Cirrhosis: A Propensity Matched Observational Study

Aims

Patients with cirrhosis are susceptible to decompensation events, including ascites, variceal bleeding (VB), hepatic encephalopathy, or death after COVID-19 infection. Patients may experience post-COVID condition (PCC) with multisystem involvement that persists for at least 2 months.

Methods

Hospitalized patients with cirrhosis and COVID-19 between January 2021 and January 2023 were assessed for decompensation events and mortality and compared to a propensity-matched cohort of cirrhosis and non-COVID-19 sepsis. Both groups were followed for outcomes over 1 year.

Results

Of 252 patients with Cirrhosis+ COVID-19 (73% men, aged 48.9 ± 13.7 years, 31%-diabetes, 44%-hypertension, 35%-alcohol-associated, 34.5%-metabolic dysfunction-associated steatotic liver disease; MASLD), 72 (28.6%) died in hospital and 180 (71.4%) recovered, similar to Cirrhosis+ non-COVID-sepsis (58/214, 27.1%). Finally,60 (33.3%) met criteria for PCC, 19 (10.5%) had no post COVID-19 sequelae and 101 (56.1%) patients died (N = 45) or were lost to follow up (N = 56). Late Mortality was higher in Cirrhosis+ COVID-19 than non-COVID-sepsis (56.1% vs. 35.3%, p = 0.026). Patients with PCC were aged 47.6 years, 63.3%-men, Charlson Comorbidity Index > 4 (51.7%), 45%-diabetes, 56.7%-hypertension, with 33.3%, 23.3%, and 43.3% in Child-Turcotte-Pugh class A, B and C, respectively. PCC symptoms included persistent dyspnea (34, 43%), cognitive impairment (20, 25.3%), and anxiety (47, 59.4%). On multivariable analysis, predictors of the development of PCC were baseline MELDNa (HR 1.12, 95% CI: 1.05-1.17, p < 0.001) and age (HR 0.9, 95% CI: 0.91-0.99, p = 0.012). Predictors of mortality following COVID-19 recovery were MELDNa (HR 1.03, 95% CI: 1.01-1.05, p = 0.008), age (HR 1.2, 95% CI: 1.1-1.5, p = 0.002) and hypertension (HR 1.63, 95% CI: 1.07-2.49, p = 0.025).

Conclusion

COVID-19 is associated with long-term mortality in cirrhosis even after recovery from respiratory infection. Long COVID is seen in a third of COVID-19 survivors in patients with cirrhosis.

The response of the benchmark healthcare index of India to COVID-19 pandemic: a return volatility approach

PURPOSE

From poor healthcare infrastructure to vaccine donors, India has traveled a long way. In this study, the author tried to find the investment certainty and persistence of volatility in the Indian healthcare system due to COVID-19.

DESIGN/METHODOLOGY/APPROACH

Using the Generalized Autoregressive Conditional Heteroskedasticity (GARCH 1,1) model, this study quantifies the change in the conditional variance after the first case report of COVID-19. The author has used the S&P BSE HEALTHCARE index time series to analyze India's healthcare infrastructure and practices.

FINDINGS

The author found evidence of a decrease in investment certainty in investments related to India's healthcare infrastructure and practices after the first case report of COVID-19. Furthermore, the estimation of the econometric model suggests the presence of a large degree of volatility persistence in the S&P BSE HEALTHCARE index.

ORIGINALITY/VALUE

This research would be the first of its kind where the return volatility of the Indian healthcare sector has been discussed. Also, this research quantifies the return volatility of the healthcare sector during the pre- and post-COVID-19 period.

CoWIN twitter dataset: A comprehensive collection of public discourse on India's COVID-19 vaccination platform

The CoWIN Twitter Dataset offers a wide-ranging collection of public opinions on India's COVID-19 vaccination platform CoWIN. The raw dataset has 635,000 tweets that mention "cowin," collected over the period of January to December 2021. The dataset was extracted by employing the Twitter Academic API. It addition to the raw data, it also included a cleaned and processed set of 419,409 English tweets, and a labeled subset with sentiment analysis. The raw data file has tweet details like ID, text, timestamp, user ID, and language. The processed dataset is devoid of URLs and hashtags and other noise, and also adds month and category groupings. Finally,the labelled dataset gives sentiment classifications of positive or negative the relevant tweets. This dataset enables researchers to analyse themes and sentiments related to India's vaccination administration. It can help policymakers gain insights around issues related to large-scale health initiatives and digital health systems. The mix of languages in the data also makes it useful for language processing research.

Unveiling vaccine safety: a narrative review of pharmacovigilance in India's COVID-19 vaccination

In India, a robust vaccine pharmacovigilance system is essential to the effective implementation of COVID-19 immunization programs, ensuring the safety and efficacy of the administered vaccines. The National Expert Group on Vaccine Administration for COVID-19 and the Pharmacovigilance Programme of India have played vital roles in monitoring and analyzing adverse events following immunization (AEFIs). These tools have made it easier to gather, assess, and report information about different adverse drug reactions connected to COVID-19 vaccines. However, there are several issues with India's vaccination pharmacovigilance, including underreporting and sluggish data gathering. To improve the efficiency of the pharmacovigilance system, it is crucial to address these issues and encourage active reporting by healthcare professionals and the general public. This insightful review article serves as a critical resource for shedding light on India's vaccine pharmacovigilance efforts throughout the COVID-19 vaccination drive. It also elucidates how these efforts are pivotal in bolstering public confidence in vaccines. The comprehensive coverage of reported AEFIs not only showcases the commitment to vaccine safety but also helps healthcare professionals and policymakers make informed decisions to enhance the overall vaccination program.

BharatSim: An agent-based modelling framework for India

BharatSim is an open-source agent-based modelling framework for the Indian population. It can simulate populations at multiple scales, from small communities to states. BharatSim uses a synthetic population created by applying statistical methods and machine learning algorithms to survey data from multiple sources, including the Census of India, the India Human Development Survey, the National Sample Survey, and the Gridded Population of the World. This synthetic population defines individual agents with multiple attributes, among them age, gender, home and work locations, pre-existing health conditions, and socio-economic and employment status. BharatSim's domain-specific language provides a framework for the simulation of diverse models. Its computational core, coded in Scala, supports simulations of a large number of individual agents, up to 50 million. Here, we describe the design and implementation of BharatSim, using it to address three questions motivated by the COVID-19 pandemic in India: (i) When can schools be safely reopened given specified levels of hybrid immunity?, (ii) How do new variants alter disease dynamics in the background of prior infections and vaccinations? and (iii) How can the effects of varied non-pharmaceutical interventions (NPIs) be quantified for a model Indian city? Through its India-specific synthetic population, BharatSim allows disease modellers to address questions unique to this country. It should also find use in the computational social sciences, potentially providing new insights into emergent patterns in social behaviour.

Quantification of uncertainty in short-term tropospheric column density risks for a wide range of carbon monoxide

The short-term risks associated with atmospheric trace gases, particularly carbon monoxide (CO), are critical for ecological security and human health. Traditional statistical methods, which still dominate the assessment of these risks, limit the potential for enhanced accuracy and reliability. This study evaluates the performance of traditional models (ARIMA), machine learning models (LightGBM, ConvLSTM2D), and optimized machine learning solutions (Bayes residual optimization ConvLSTM2D LightGBM, Bayes_CL) in predicting Sentinel 5P columnar CO levels. This study findings demonstrate that machine learning models and their optimized versions significantly outperform traditional ARIMA models in cross-validation (CV), visualization, and overall prediction performance. Notably, machine learning model based on Bayes and residual optimization (Bayes_CL) achieved the highest CV score (Bayes_CL R2 = 0.8, LightGBM R2 = 0.79, ConvLSTM2D R2 = 0.75, ARIMA R2 = 0.61), along with superior visualization and other metrics. Using Bayes_CL, we effectively quantified a 2.4% increase in columnar CO levels in mainland China in the second half of 2023, following the complete lifting of COVID-19 lockdowns. This study confirms that machine learning models can effectively replace traditional methods for short-term risk assessment of Sentinel 5P columnar CO. This transition holds significant implications for policy formulation, greenhouse effect assessment, and population health risk evaluation, especially in uncertain situations where human activities are severely disrupted, thereby affecting environmental safety.

Non-COVID Admissions to the ICU After COVID Vaccination: A Multicenter Study

INTRODUCTION

The vaccination drive for COVID-19 was launched in India after the authorization of ChAdOx1 nCov-19 (Covishield), an adenoviral vector vaccine, and BBV152 COVID-19 (Covaxin), an inactivated virus vaccine. As stated by the CDC, vaccine-related adverse events can happen. In this study, we aimed to assess the timing of the COVID vaccination and admission diagnosis and their effect on ICU mortality. The time from vaccination can help identify adverse events directly related to vaccination.  Methods: A retrospective cohort study was conducted across four centers in India. Patients who took the first or second dose of any vaccines and were admitted with non-COVID illness to the ICU were included in the study. Patients were categorized based on the time interval from vaccination as ≤42 days or >42 days. The primary outcome was ICU mortality. The secondary outcomes were the length of ICU stay and duration of mechanical ventilation.

RESULTS

A total of 175 patients were included in the study. The mean age was 53.49 (15.89) years, and 61.14% were males. The ICU mortality was 24.57% (18.38% to 31.63%). Thromboembolic events such as acute coronary syndrome (ACS), cerebrovascular accident (CVA), and mesenteric ischemia were seen in 7.43%, 7.43%, and 1.14% of patients, respectively. Six patients (3.43%) developed neuromuscular illness. The mortality was higher in patients >66 years, followed by ≤35 years of age when admitted ≤42 days of vaccination (p=0.008). The mortality was higher in cerebrovascular disorders and was clinically significant (p<0.001).

CONCLUSION

Patients developed thromboembolic events and neuromuscular diseases requiring ICU admission post-COVID vaccination. We observed a significantly higher mortality in the age groups >66 years and ≤35 years when admitted within 42 days of COVID vaccination. Patients admitted with cerebrovascular diseases also had higher mortality.

COVID-19 Vaccine Hesitancy among Adults in India: A Systematic Review and Meta-analysis

SUMMARY

The global health crisis triggered by the SARS-CoV-2 in 2019, known as the COVID-19 pandemic, prompted vaccination drives worldwide, including in India, to address the crisis. However, vaccine hesitancy remains a significant challenge to achieving vaccination goals. Hence, we conducted a systematic review and meta-analysis during 2021-2023 to estimate the prevalence of COVID-19 vaccine hesitancy among adults in India and identify associated factors. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were followed. Quality assessment was performed using the Joanna Briggs Institute checklist. Pooled prevalence estimates were calculated using a random-effects model. A total of 265 articles were identified, of which 21 full-text articles were included in the review. The pooled estimated prevalence of COVID-19 vaccine hesitancy among adults in India was found to be 28% (95% confidence interval: 27-29). Subgroup analysis revealed variations in hesitancy rates across different states, with higher rates observed in Jammu and Kashmir (44%), West Bengal (49%), and Maharashtra (39%). Gender-based analysis indicated higher hesitancy among males (36%) compared to females (26%). Among different study populations, medical students showed the lowest hesitancy rate (13%), whereas the general population exhibited the highest (34%). The findings suggest that vaccine hesitancy remains a significant concern in India, with one in four adults expressing hesitancy toward COVID-19 vaccination. Hesitancy rates vary across states, genders, and study populations. Addressing the factors contributing to hesitancy, such as safety concerns, lack of evidence, and misinformation, is crucial to enhance vaccine acceptance.

India's Potential as a Leader in Cancer Care Progress in the Future: A Synthetic Interdisciplinary Perspective

This paper comprehensively analyzes India's potential to become a leader in cancer care in the Global South, particularly in precision population cancer medicine (PPCM). Through an interdisciplinary lens, it examines the current landscape of cancer care in India, highlighting its strengths, weaknesses, opportunities, and threats in this domain. This review explores the concept of knowledge translation and its importance in bridging the gap between knowledge generation and implementation in medical sciences and applies this to the Indian healthcare scenario. The review then delves into India's technological prowess, exemplified by its digital health initiatives such as the CoWIN (winning over COVID-19) app and the Ayushman Bharat Digital Mission, which provide a strong foundation for leveraging advanced technologies in healthcare. The authors discuss India's pharmaceutical industry, often referred to as the "pharmacy of the world," emphasizing its crucial role in global drug manufacturing and distribution. It also examines the country's emerging genomic research landscape, including initiatives such as GenomeIndia and the Indian Cancer Genome Atlas Foundation, which are pivotal for advancing personalized medicine. A significant portion of the review is dedicated to analyzing India's clinical trial ecosystem. It traces the evolution of regulatory frameworks governing clinical research in the country and highlights recent reforms that have made India an increasingly attractive destination for global studies, the potential adoption of innovative trial designs and artificial intelligence (AI)-driven analyses. Crucially, the authors confront the formidable obstacles inherent in India's complex healthcare landscape, illuminating the unique challenges that must be overcome. The review acknowledges India's underrepresentation in global clinical trials despite its large population and significant cancer burden. The issue of financial toxicity in cancer care is discussed, underscoring the need for affordable treatment options. The study also points out the nascent state of India's genomic databases, which account for only a small percentage of global genetic data. Despite these challenges, the authors posit that by effectively leveraging its information technology (IT) infrastructure, robust pharmaceutical sector, and large, diverse population, India has the potential to develop unique, country-specific solutions for cancer care. The study suggests that by fostering genomic research, strategically reforming its clinical trial ecosystem, and harnessing its digital capabilities, India could transform its cancer care landscape and emerge as a model for other developing nations in the Global South. In essence, this paper provides a roadmap for India's journey towards becoming a leader in PPCM, offering valuable insights for policymakers, healthcare professionals, and researchers in the field of oncology and precision medicine. Indeed, by using PPCM as a "pilot project," India can learn to use its new strategies to improve non-cancer care disease prevention, early detection, and improved and more cost-effective management. This approach could revolutionize cancer care in India and serve as a model for other developing nations in the Global South. By leveraging the strategies and technologies developed for PPCM, India could significantly enhance its healthcare system, highlighting the importance and urgency of improving cancer care in the region.

Case fatality among people with drug-susceptible TB enrolled in a private health sector TB treatment support program in Bihar, India during the first year of the COVID-19 pandemic

Experiencing 27% of the global tuberculosis (TB) burden, India's TB epidemic is the largest in the world. Due to COVID-19-related disruptions to TB programs, India has also seen the largest drop in TB case notifications of any country globally. We estimated case fatality among people treated for TB in India during the pandemic and compared these to pre-pandemic estimates. A random sample of 4,000 adults enrolled in World Health Partners (WHP), a private sector TB treatment support program (enrolling only people with drug-susceptible TB) in Bihar, India in the first year of COVID-19 (Mar 2020-Mar 2021) were contacted via phone to collect information on TB case fatality and other relevant covariates. Inverse probability of selection (IPS) weighting was used to obtain selection-bias-corrected in-treatment and post-treatment case fatality estimates. Covariates associated with (but not necessarily causal of) case fatality were identified by estimating adjusted hazard ratios (HRs) using the Cox proportional hazards model. WHP enrolled 19,826 adult drug-susceptible TB patients in the first year of COVID-19 (Mar 2020 to Mar 2021). Of our random sample of 4,000 patients, n = 2,962 (74.1%) answered the follow-up call. Unweighted and IPS-weighted in-treatment case fatality in the primary analysis were 6.12% (95%CI: 5.31-6.97%) and 6.07% (95%CI: 5.22-6.93%), respectively. Post-treatment case fatality estimates were 0.97% (95%CI: 0.61-1.33%) (unweighted) and 1.27% (95%CI: 0.79-1.79) (IPS-weighted). Our IPS-weighted estimates for in-treatment and post-treatment case fatality were similar to pre-pandemic IPS-weighted estimates (in-treatment: 7.27%, 95%CI: 5.97%- 8.49% and 12 months post-treatment: 1.23, 95%CI: 0.75-1.73). Although not higher than pre-pandemic estimates, the observed case fatality in this private sector cohort of people treated for drug-susceptible TB during COVID-19 in Bihar, India is above the level needed to reach the 2025 and 2030 End TB Strategy targets for reductions in TB deaths, underlining the extent of pandemic-related setbacks to TB elimination.

Sustaining the mobile medical units to bring equity in healthcare: a PLS-SEM approach

BACKGROUND

Equitable access to healthcare for rural, tribal, and underprivileged people has been an emerging area of interest for researchers, academicians, and policymakers worldwide. Improving equitable access to healthcare requires innovative interventions. This calls for clarifying which operational model of a service innovation needs to be strengthened to achieve transformative change and bring sustainability to public health interventions. The current study aimed to identify the components of an operational model of mobile medical units (MMUs) as an innovative intervention to provide equitable access to healthcare.

METHODS

The study empirically examined the impact of scalability, affordability, replicability (SAR), and immunization performance on the sustainability of MMUs to develop a framework for primary healthcare in the future. Data were collected via a survey answered by 207 healthcare professionals from six states in India. Partial least squares structural equation modeling (PLS-SEM) was conducted to empirically determine the interrelationships among various constructs.

RESULTS

The standardized path coefficients revealed that three factors (SAR) significantly influenced immunization performance as independent variables. Comparing the three hypothesized relationships demonstrates that replicability has the most substantial impact, followed by scalability and affordability. Immunization performance was found to have a significant direct effect on sustainability. For evaluating sustainability, MMUs constitute an essential component and an enabler of a sustainable healthcare system and universal health coverage.

CONCLUSION

This study equips policymakers and public health professionals with the critical components of the MMU operational model leading toward sustainability. The research framework provides reliable grounds for examining the impact of scalability, affordability, and replicability on immunization coverage as the primary public healthcare outcome.

Developments and Trends of Immunization in India: A Narrative Review

Immunization is a critical component of public health, and it undergoes various trends and developments over time. Immunization is considered one of humanity's most remarkable journeys. It has helped save countless lives and will help save more if the goals of the 2030 Immunization Agenda (IA2030) are achieved. India is home to one of the largest global immunization programs. Immunization trends refer to the patterns and changes in the development of vaccines, the use of vaccines, and vaccination programs within a nation. There have been various trends in vaccine development and immunization in India. Trends can be influenced by various factors, including vaccine coverage, new vaccines, vaccine hesitancy, advances in medical science, technological innovations, public-private partnerships, public health policies, and public awareness. India has the world's largest immunization program regarding the number of vaccinations delivered, the recipients, the geographic spread, and the human resources required. In this review, we give an overview of various trends in immunization in India dating from the ancient era. A search of the PubMed, Scopus, and Google Scholar databases from 1945 to February 2024 was done to conduct a narrative review. This review includes English-language publications. This narrative review was conducted to summarize the government of India's actions and strategies for immunization and vaccine development and also to trace the trends in immunization in India. It covers various vaccination programs of the Indian government and measures that were made to fight vaccine hesitancy and to enhance vaccination coverage such as developing vaccination roadmaps, scheduling vaccinations, utilizing digital health technology, monitoring vaccinations, and developing creative techniques. India has the world's largest Universal Immunization Program, vaccinating around 29 million pregnant women and 26.5 million infants annually. These trends reflect India's ongoing commitment to immunization as a component of public health policy and efforts to address existing and emerging health challenges.

COVID-19 vaccine hesitancy among adults in India: A primary study based on health behavior theories and 5C psychological antecedents model

Despite the significant success of India's COVID-19 vaccination program, a sizeable proportion of the adult population remains unvaccinated or has received a single dose of the vaccine. Despite the recommendations of the Government of India for the two doses of the COVID-19 vaccine and the precautionary booster dose, many people were still hesitant towards the COVID-19 full vaccination. Hence, this study aimed to identify the primary behavioral and psychological factors contributing to vaccine hesitancy. Cross-sectional data was collected via a multi-stage sampling design by using a scheduled sample survey in the Gorakhpur district of Uttar Pradesh, India, between 15 July 2022 to 30 September 2022. This study has utilized three health behavior models-the Health Belief Model (HBM), the Theory of Planned Behavior (TPB), and the 5C Psychological Antecedents of vaccination, and employed bivariate and multivariable binary logistic regression model to assess the level of vaccine hesitancy and predictive health behavior of the respondents. Results indicate that among the constructs of the HBM and 5C Antecedents models, "perceived benefits", "confidence" and "collective responsibility" showed a lesser likelihood of COVID-19 vaccine hesitancy. However, in the TPB model constructs, a 'negative attitude towards the vaccine' showed a four times higher likelihood of COVID-19 vaccine hesitancy. From the future policy perspective, this study suggested that addressing the issue of 'negative attitudes towards the vaccine' and increasing the trust or confidence for the vaccine through increasing awareness about the benefits of the vaccination in India may reduce vaccine hesitancy.

COVID-19 vaccine: Culprit or innocent bystander in a rare adverse gastro-intestinal surgical event? A case report with review of literature

Corona virus disease (COVID-19) initially appeared to be an exclusively respiratory ailment. While that is true in a vast majority of the cases, its evolution and later evidence have shown that it can afflict virtually any organ system in the human body after first gaining entry through the respiratory tract. The COVID-19 vaccines were one of the turning points in the campaign to control the COVID-19 pandemic. However, after their extensive use all over the world, it has emerged that they can cause some dangerous collateral damage. We, herein, report the case of a 58-year-old woman who presented to us with signs and symptoms of acute intestinal obstruction 4 months after receiving her first dose of Covishield® vaccination for COVID-19. Her blood tests showed a high D-dimer and normal platelet count. She was previously admitted to the hospital with an acute abdomen 3 months back. A contrast-enhanced computed tomography (CECT) scan of the abdomen done then had revealed thrombi in the aorta and inferior mesenteric and splenic arteries. She was started on low-molecular-weight heparin and discharged on tablet Warfarin after clinical improvement. CECT abdomen done during her present admission revealed a proximal small bowel stricture with dilated proximal and collapsed distal loops. She underwent a laparoscopic jejuno-ileal resection anastomosis. During the post-operative period, a repeat CECT abdomen done to evaluate multiple episodes of vomiting revealed pulmonary embolism in the lower chest cuts. A venous Doppler revealed extensive deep venous thrombosis of the left lower limb. A thrombophilia profile diagnosed anti-phospholipid antibody syndrome, an exacerbation of which was likely precipitated by the COVID-19 vaccine.

Self-reported side effects of COVID-19 vaccines among health professions students in India

Studies focusing on the safety and common side effects of vaccines play a crucial role in enhancing public acceptance of vaccination. Research is scarce regarding the usage of COVID-19 vaccines and the side effects experienced by health professions students in India and other countries. This study aimed to document self-reported side effects associated with COVID-19 vaccination among medical and dental students of six medical and dental colleges and teaching hospitals in four states (Tamil Nadu, Madhya Pradesh, Gujarat, and West Bengal) of India. A cross-sectional survey using purposive sampling of medical and dental students was conducted from 26 April to 26 May 2021. Data was collected using a Google Forms questionnaire capturing information regarding receiving COVID-19 vaccines, side effects and symptoms, onset and duration of symptoms, use of treatment to alleviate symptoms, awareness of haematologic risks associated with vaccination, and side effects from previous (non-COVID-19) vaccinations. The majority (94.5%) of participants received both doses of the Covishield/AstraZeneca COVID-19 vaccine. Among participants (n = 492), 45.3% (n = 223) reported one or more side effects. The most frequently reported side effects were soreness of the injected arm (80.3%), tiredness (78.5%), fever (71.3%), headache (64.1%), and hypersomnia (58.7%). The two most common severe symptoms were fever (14.8%) and headache (13%). Most side effects appeared on the day of vaccination: soreness of the injection site (57%), fever (43.1%), and tiredness (42.6%). Most reported symptoms persisted for one to three days-soreness of the injection site (53%), fever (47.1%), and headache (42.6%). Logistic regression showed that women were almost 85% less likely to report side effects. The study's findings corroborate the safety of the Covishield/AstraZeneca vaccine's first dose, evidenced by the relatively minor and transient nature of the side effects. However, the study underscores the necessity for ongoing research to assess the long-term impacts of COVID-19 vaccines, especially in the context of booster doses, thereby contributing to the global understanding of vaccine safety and efficacy.

K, Krishna NS, Kaviprawin M, Gollapalli PK, Ramamurthy S, Ganeshkumar P, Jagadeesan M, Kaur P. Face mask use in the city of Chennai, India: Results from three serial cross-sectional surveys, 2021

INTRODUCTION

The Government of Tamil Nadu, India, mandated wearing face masks in public places to combat the COVID-19 pandemic. We established face mask surveillance and estimated the prevalence of appropriate mask use (covering the nose, mouth, and chin) in the slums and non-slums of Chennai at different time points in 2021.

METHODS

We conducted three serial cross-sectional surveys in the outdoors and indoors of Chennai in March, July, and October 2021. We observed the mask wearing among 3200 individuals in the outdoors and 1280 in the indoors. We divided the outdoor and indoor locations into slums and non-slums. In October 2021, we also surveyed 150 individuals from each of the 11 shopping malls in the city. We calculated the proportions and 95% confidence interval (95%CI) for the appropriate mask use in the outdoor, indoor, and malls by age, gender, region, and setting (slum and non-slum).

RESULTS

We observed 3200 individuals in the outdoor and 1280 individuals in the indoor setting, each from a slum and non-slum, during the three rounds of the study. In outdoor and indoors, males comprised three-fourths and middle-aged individuals were half the study population. Mask compliance changed significantly with time (p-value <0.001). Males consistently demonstrated better compliance in all rounds. The south region had the highest mask compliance in slums indoors and outdoors in rounds 4 and 5. Young adults had the highest mask compliance in both outdoor slums and non-slums in all rounds. Overall mask compliance in shopping malls was 57% (95% CI: 48-65).

CONCLUSION

The mask compliance in Chennai outdoors during the COVID-19 pandemic was less than 50%, with variations across time points by gender, age groups, and geographical locations. We must develop more effective communication strategies for older age groups and crowded indoor settings.

Adverse events following Covaxin administration among adolescents (15-18 years) - A pharmacovigilance study in a district in Northern India

Introduction

The study was undertaken to observe the adverse event following immunization (AEFI) to the Covaxin vaccine in young adolescents in the age group of 15-18 years in a district in Northern India. The study was conducted to assess the safety profile of the COVAXIN vaccine.

Methodology

This was a prospective observational study conducted at rural and urban health centers of a district in Northern India. We included the beneficiaries of the COVAXIN between the age of 15 and 18 years. The administration of the COVAXIN occurred in our district from January 2022. Periodic visits were conducted to the urban and rural health centers of the city to record any suspected adverse drug reaction following immunization in the defined population. The study was conducted for a period of 1 year (January 2022 to December 2022).

Results

A total of 72,771 adolescents (15-18 years) received the first dose of Covaxin and 49,046 received the second dose. No adverse drug event following immunization was reported during the study.

Conclusion

Thus, it can be concluded that Covaxin was found to be safe in adolescents (15-18 years).

Parity of esteem: A global COVID-19 vaccination approach for people with mental illnesses, based on facts from 34 countries; recommendations and solutions

Background

The coronavirus disease (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has detrimental effects on physical and mental health. Patients with severe mental illness are at higher risk of contracting the virus due to social determinants of health. Vulnerable populations include the elderly, people with pre-existing conditions, and those exposed to SARS-CoV-2. Unfortunately, only a few countries have updated vaccination strategies to prioritize patients with mental illnesses. Therefore, we aimed to explore whether individuals with mental disorders are prioritized in vaccine allocation strategies in different world regions. They are often neglected in policymaking but are highly vulnerable to the threatening complications of COVID-19.

Methods

A questionnaire was developed to record details regarding COVID-19 vaccination and prioritizations for groups of persons with non-communicable diseases (NCDs), mental disorders, and substance use disorders (SUDs). NCDs were defined according to the WHO as chronic diseases that are the result of a combination of genetic, physiological, environmental, and behavioral factors such as cardiovascular diseases, cancer, respiratory diseases, and diabetes.

Results

Most countries surveyed (80%) reported healthcare delivery via a nationalized health service. It was found that 82% of the countries had set up advisory groups, but only 26% included a mental health professional. Most frequently, malignancy (68%) was prioritized followed by diabetes type 2 (62%) and type 1 (59%). Only nine countries (26%) prioritized mental health conditions.

Conclusion

The spread of the coronavirus has exposed both the strengths and flaws of our healthcare systems. The most vulnerable groups suffered the most and were hit first and faced most challenges. These findings raise awareness that patients with mental illnesses have been overlooked in immunization campaigns. The range of their mortality, morbidity, and quality of life could have widened due to this delay.

Increased Frequency of Low Back Pain in Recent Times: Does the Answer Lie in COVID-19?

Background The COVID-19 pandemic has impacted many people's activities of daily living and health. It has also created economic burdens and caused mental turmoil across the world. Musculoskeletal symptoms, especially low back pain, have been observed in subjects of post-COVID-19 infection and post-vaccination. Aim In this study, we aimed to investigate the relationship between low back pain and COVID-19 infection and vaccination, as well as associated factors and characteristics. Methods We conducted a questionnaire-based cross-sectional observational study at All India Institute of Medical Science (AIIMS) Bibinagar between September 2021 and March 2022. We collected data from individuals through physical and Google Forms (Google, Mountain View, California).  Results We included a total of 535 individuals in the study: 274 (51.2%) were previously positive for COVID-19 infection (group A), and 261 (48.8%) were vaccinated against COVID-19 without a history of COVID-19 infection (group B). Each group was divided into two categories based on whether they had low back pain before COVID-19 infection or vaccination. In group A, 90.1% of individuals experienced an aggravation of low back pain after COVID-19 infection, which was found to be significant (p<0.001). In group B, there was an insignificant increase in low back pain following COVID-19 vaccination (p=0.275). The study also revealed a significant association between comorbidities and low back pain in both groups (p<0.001). Additionally, several differences were observed between the two groups, including duration (p<0.001), severity (p=0.012), and intensity (p<0.001) of low back pain, usage of a back support or brace (p=0.043), and intake of vitamin D (p=0.002).  Conclusion Low back pain is an ignored feature of one of the musculoskeletal symptoms of COVID-19 and was aggravated by COVID-19 infection in our patients compared to those who received the vaccination. The findings of this study have implications for raising awareness, improving management and rehabilitation, and guiding future research in this area.

Role of leadership and incentive-based programs in addressing vaccine hesitancy in India

The current study goes beyond the popular 5Cs model of vaccine hesitancy to explore perceived social norms, role of leadership and the role of incentive-based intervention for improving the likelihood of vaccination, in a population-representative sample of adults in India (N = 1129). We investigated differences in socio-demographic status, perceived descriptive norms like vaccine behaviours, beliefs, experience and perceived injunctive norms like community and political leadership within the context of the COVID-19 pandemic are related to vaccination. Further, we examined the role of incentive-based intervention as a potentially salient predictor of adults' vaccine uptake. The study is based on a cross-sectional survey conducted in July-November 2021, which included questions about impacts of pandemic collected by phone call interview from adults' beneficiaries of Government free food schemes, across 11 states in India. The data include 81 % vaccinated and 19 % vaccine hesitant participants, with a higher proportion of business or self-employed (53.1 %) as vaccine hesitant. We performed the t-test to assess the variation between vaccinated and vaccine hesitant adults, and Exploratory Factor Analysis to uncover the underlying dimension of vaccine hesitancy. Subsequently, Binary Logistic Regression model probed the factors associated with likelihood of vaccination uptake. In contrast to the prevailing evidence, results demonstrated community and political leadership has significant negative impact on vaccination (p-value < 0.06, 95 % CI, 0.57-1.01). Incentive-based intervention offer a vital leverage to enhance positive attitude towards vaccination (p-value < 0.05, 95 % CI, 1.01-1.80). The results thus broadly highlight the limited role of political and community leaders in leveraging their influence on vaccination, the role of timely, accurate information, applications of telemedicine as an important tool to provide healthcare and the need for optimal design of incentive-based vaccination programs recommended by trusted sources.

Balancing Routine and Pandemic: The Synergy of India's Universal Immunization Program and COVID-19 Vaccination Program

The COVID-19 pandemic posed substantial challenges to healthcare systems globally and severely disrupted essential health services, including routine immunization programs. In India, these disruptions were exacerbated due to the sudden emergence of the pandemic and lockdown measures, leading to mass migrations and a shortage of healthcare workers. Caregivers' concerns about routine immunization sessions further compounded the problem, resulting in a sharp increase in zero-dose children. This review paper examines India's strategies for conducting one of the world's largest COVID-19 vaccination programs while effectively restoring and perpetuating its Universal Immunization Program (UIP). The UIP played a pivotal role in sustaining immunization services during the pandemic, ultimately improving immunization coverage compared to pre-pandemic levels. India's accomplishments in this regard are highlighted through key performance indicators, the reach of immunization services, a reduction in zero-dose children, and antigen-wise coverage. The paper also discusses the successful integration of COVID-19 vaccination within the UIP framework, underscoring the significance of existing infrastructure, technology, and capacity building. India's dedication to concurrently managing routine immunization and COVID-19 vaccination showcases the adaptability and resilience of its healthcare system. India's journey serves as a global example of efficient mass immunization during challenging times, emphasizing the importance of political will, healthcare infrastructure investment, skilled healthcare workforces, and comprehensive vaccination programs. In a world grappling with the dual challenge of COVID-19 and routine immunization, India's experience provides a roadmap for strengthening healthcare systems and promoting public health as the critical agenda in challenging times.

Healthcare provider perspectives on COVID-19 vaccination for children in India

BACKGROUND

The rapid development and deployment of effective COVID-19 vaccines have been critical to halt the spread of the pandemic. India started vaccinating children in early 2022, however, vaccine uptake has been suboptimal.

METHODS

Between September and November 2022, we conducted an online survey that was disseminated to eligible participants via email, text messages and social media platforms across India. The survey aimed to gather the perspectives of Indian healthcare providers regarding key factors related to the rollout of paediatric COVID-19 vaccines. Descriptive statistics were used to analyse participant demographics and responses on knowledge about paediatric COVID-19 vaccines, perceived risks and benefits, and vaccine rollout strategies.

RESULTS

The survey yielded 805 respondents from 23 Indian states; 63.5% were men, 97.3% were paediatricians, median age was 44 years (IQR 25-81). Eighty-one per cent and 65.2% respondents had heard about the most common paediatric COVID-19 vaccines in India, Covaxin and Corbevax, but only 52.9%, 53.7% and 62.1% felt adequately informed about their safety, efficacy and vaccination schedules, respectively. Thirty per cent of respondents were unaware of vaccination guidelines. Eighty-five per cent of respondents felt that vaccines would reduce the incidence of severe disease, hospitalisation and deaths, and 60.6% felt children with comorbidities should be prioritised for vaccination. Perceived supply side barriers included lack of enforcement of guidelines (45.2%) and adverse effects following immunisation monitoring systems (37.6%), and on the demand side, parental vaccine hesitancy (64.4%). Eighty-one per cent believed that school-based vaccination strategies would be highly effective in increasing uptake.

CONCLUSIONS

Most respondents were in support of the COVID-19 paediatric vaccination, although just over half did not feel adequately informed. Concerns about vaccine hesitancy among caregivers were the leading reported barrier. Targeted interventions are needed to provide adequate knowledge support to healthcare providers and evidence-based public health messaging to reduce vaccine hesitancy among caregivers.

Drivers of vaccine hesitancy among vulnerable populations in India: a cross-sectional multi-state study

Objectives

India's Covid-19 vaccination campaign engaged frontline workers (FLWs) to encourage vaccination among vulnerable segments of society. The FLWs report encountering a variety of barriers to vaccination and are often unsuccessful despite multiple visits to the same person. This cross-sectional study aims to pinpoint which of these barriers drive vaccine hesitancy among these segments, to help streamline vaccine communication, including FLW training, to better safeguard the population.

Methods

Trained field enumerators contacted 893 individuals from five states across India and collected self-reported assessments of fifteen vaccination barriers (identified through discussions with FLWs), current vaccination status and future vaccination intentions, and covariates (demographics/comorbidities). Factor analysis of the fifteen barriers yielded two factors, one relating to fear of vaccine adverse effects and a second focused on peripheral concerns regarding the vaccine. The covariates significantly associated with current vaccination status were combined under a latent class regime to yield three cluster types (health access, financial strength, and demographics). The primary analysis examined the effect of the two barrier factors, the covariate clusters, and comorbidity, on current vaccination status and future vaccine intentions.

Results

Fear of vaccine adverse effects was the primary driver of vaccine hesitancy; peripheral concerns frequently mentioned by the FLWs had no impact. Although cluster membership and the presence of comorbidities predicted vaccine uptake, neither of them materially altered the effect of fear of vaccine adverse effects with the following exception: fear of adverse effects was not associated with vaccination status among young Muslim men.

Conclusion

Subject to limitations, these results indicate that interventions to decrease vaccine hesitancy should focus primarily on fear associated with vaccines rather than spend resources trying to address peripheral concerns.

Vaccine Breakthrough Infections Among Healthcare Workers in a COVID-19-Designated Tertiary Care Government Hospital in Sikkim

Introduction Since the emergence of the coronavirus disease 2019 (COVID-19) virus at the beginning of 2020, the world has gone through various waves of pandemics. The health care workers (HCWs) or the COVID warriors as they were termed were the first line of defense against the virus. They were armed with personal protective equipment and prophylactic doses of the COVID-19 vaccine. Despite these precautions, some of the HCWs still contracted the disease and a few others succumbed to it. The objective of this study was to estimate the prevalence of COVID-19 infections and vaccine breakthrough infections (BTIs) in HCWs after receiving the COVID-19 vaccine during the second wave of the pandemic. Methods This was a cross-sectional, hospital-based study conducted over a period of four months from September 2021 to December 2021 on HCWs aged 18 years and above working at the COVID-19-designated tertiary care government hospital in Sikkim. A structured coded questionnaire with no patient identifiers was used to gather details on demographics, vaccination history, breakthrough infection, and other social details. HCWs who had received at least one dose of the COVID-19 vaccine at the time of initiation of the study and were >18 years of age were included in this study. Results A total of 678 HCWs were screened, out of which 229 (33%) participants tested positive for COVID-19 and the rest of the participants (455; 67%) tested negative. COVID-19 infections and vaccine BTIs (COVID-19 infection >14 days after the second vaccination) were recorded and 137 (20%) respondents had a post-vaccination COVID-19 infection out of which 115 (18.5%) were BTI. The majority of the participants were females and of the age group of 26-35 years. The correlation of COVID-19 infections with the dose gap between vaccination, gender, age, profession, department, area posted during COVID duty, cycles of duty performed, hospitalization due to infection, influenza vaccination, and comorbidity was analyzed. Conclusion COVID-19 vaccines are disease-modifying and they decrease the severity of BTIs in HCWs. Pandemics and outbreaks cannot be predicted; therefore, it becomes very important to have healthy frontline workers who are constantly exposed to infectious agents. Monitoring of health and surveillance of infectious diseases among the HCWs should be encouraged.

COVID Variants, Villain and Victory: A Bioinformatics Perspective

The SARS-CoV-2 virus, a novel member of the Coronaviridae family, is responsible for the viral infection known as Coronavirus Disease 2019 (COVID-19). In response to the urgent and critical need for rapid detection, diagnosis, analysis, interpretation, and treatment of COVID-19, a wide variety of bioinformatics tools have been developed. Given the virulence of SARS-CoV-2, it is crucial to explore the pathophysiology of the virus. We intend to examine how bioinformatics, in conjunction with next-generation sequencing techniques, can be leveraged to improve current diagnostic tools and streamline vaccine development for emerging SARS-CoV-2 variants. We also emphasize how bioinformatics, in general, can contribute to critical areas of biomedicine, including clinical diagnostics, SARS-CoV-2 genomic surveillance and its evolution, identification of potential drug targets, and development of therapeutic strategies. Currently, state-of-the-art bioinformatics tools have helped overcome technical obstacles with respect to genomic surveillance and have assisted in rapid detection, diagnosis, and delivering precise treatment to individuals on time.

Deep learning for COVID-19 topic modelling via Twitter: Alpha, Delta and Omicron

Topic modelling with innovative deep learning methods has gained interest for a wide range of applications that includes COVID-19. It can provide, psychological, social and cultural insights for understanding human behaviour in extreme events such as the COVID-19 pandemic. In this paper, we use prominent deep learning-based language models for COVID-19 topic modelling taking into account data from the emergence (Alpha) to the Omicron variant in India. Our results show that the topics extracted for the subsequent waves had certain overlapping themes such as governance, vaccination, and pandemic management while novel issues aroused in political, social and economic situations during the COVID-19 pandemic. We also find a strong correlation between the major topics with news media prevalent during the respective time period. Hence, our framework has the potential to capture major issues arising during different phases of the COVID-19 pandemic which can be extended to other countries and regions.

Translating the COVID-19 experience in widening the HPV vaccination campaign for cervical cancer in India

India has proven by the success of COVID vaccination that it has a huge production and distribution capacity, availability of professionally trained medical staff, world renowned digital infrastructure to enrol people, conduct camps and maintain records, and a positive mindset among the people towards vaccination. There is an unmet need to enforce that cervical cancer is a "preventable tragedy," and vaccination is an invaluable way ahead. With this article, we hope to attract attention to translating India's successful COVID-19 vaccination campaign experience to developing the HPV vaccination campaign.

An assessment of the strategy and status of COVID-19 vaccination in India

The COVID-19 disease continues to cause devastation for almost 3 years of its identification. India is one of the leading countries to set clinical trials, production, and administration of COVID-19 vaccination. Recent COVID-19 vaccine tracker record suggests that 12 vaccines are approved in India, including protein subunit, RNA/DNA, non-replicating viral vector, and inactivated vaccine. Along with that 16 more vaccines are undergoing clinical trials to counter COVID-19. The availability of different vaccines gives alternate and broad perspectives to fight against viral immune resistance and, thus, viruses escaping the immune system by mutations. Using the recently published literature on the Indian vaccine and clinical trial sites, we have reviewed the development, clinical evaluation, and registration of vaccines trial used in India against COVID-19. Moreover, we have also summarized the status of all approved vaccines in India, their associated registered clinical trials, manufacturing, efficacy, and their related safety and immunogenicity profile.

An update on vaccine status and the role of nanomedicine against SARS-CoV-2: A narrative review

Background and Aims

Coronavirus disease 2019 (COVID-19), caused by the SARS-CoV-2 novel coronavirus, is a highly communicable disease that gave rise to the ongoing pandemic. Despite prompt action across many laboratories in many countries, effective management of this disease is still out of reach. The focus of this review is to describe various vaccination approaches and nanomedicine-based delivery systems against COVID-19.

Methods

The articles included in this study were searched and added from different electronic databases, including PubMed, Scopus, Cochrane, Embase, and preprint databases.

Results

Mass immunization with vaccines is currently at the forefront of COVID-19 infection control. Such vaccines are live attenuated vaccines, inactivated vaccines, nucleic acid-based vaccines, protein subunit vaccines, viral-vector vaccines, and virus-like particle platforms. However, many promising avenues are currently being explored in laboratory and clinical settings, including treatment options, prevention, diagnosis, and management of the disease. Soft nanoparticles like lipid nanoparticles (solid lipid nanoparticles (SLNPs), liposomes, nanostructured lipid carriers, nanoemulsions, and protein nanoparticles play an essential role in nanomedicine. Because of their unique and excellent properties, nanomedicines have potential applications in treating COVID-19 disease.

Conclusions

This review work provides an overview of the therapeutic aspects of COVID-19, including vaccination and the role of nanomedicines in the diagnosis, treatment, and prevention of COVID-19.

COVID-19 Booster Dose Coverage and Hesitancy among Older Adults in an Urban Slum and Resettlement Colony in Delhi, India

BACKGROUND

The high prevalence of vaccine booster hesitancy, with the concomitant waning of humoral vaccine or hybrid immunity, and the emergence of SARS-CoV-2 variants of concern can accentuate COVID-19 morbidity and mortality. The study objective was to ascertain the COVID-19 vaccination coverage, including the administration of precaution (booster) dose vaccination, among the older population in an urban slum and resettlement colony population in Delhi, India.

METHODS

We conducted a cross-sectional survey in an urban resettlement colony, slum, and village cluster in the Northeast district of Delhi among residents aged ≥50 years.

RESULTS

A total of 2217 adults (58.28%) had obtained a COVID-19 booster (precaution) dose vaccine, 1404 (36.91%) had received two doses of a COVID-19 vaccine without booster dose, 121 (3.18%) were unvaccinated, while 62 (1.63%) participants received a single dose. Based on adjusted analysis, older adults (>65 years), higher education, and higher per-capita income were statistically significant predictors of booster dose vaccination.

CONCLUSIONS

More than four in ten adults in an urban slum and resettlement colony in Delhi lacked COVID-19 booster dose vaccination despite high rates of double-dose vaccination (~95%). Public health programming should provide an enhanced focus on reducing complacency with renewed prioritization for improving ease of access to COVID-19 vaccination services, particularly in underserved areas.

Intertwined Dysregulation of Ribosomal Proteins and Immune Response Delineates SARS-CoV-2 Vaccination Breakthroughs

Globally, COVID-19 vaccines have emerged as a boon, especially during the severe pandemic phases to control the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections, saving millions of lives. However, mixed responses to vaccination with breakthrough challenges provided a rationale to explore the immune responses generated postvaccination, which plausibly alter the subsequent course of infection. In this regard, we comprehensively profiled the nasopharyngeal transcriptomic signature of double-dose-vaccinated individuals with breakthrough infections in comparison to unvaccinated infected persons. The vaccinated individuals demonstrated a gross downregulation of ribosomal proteins along with immune response genes and transcription/translational machinery that methodically modulated the entire innate immune landscape toward immune tolerance, a feature of innate immune memory. This coordinated response was orchestrated through 17 transcription factors captured as differentially expressed in the vaccination breakthroughs, including epigenetic modulators of CHD1 and LMNB1 and several immune response effectors, with ELF1 emerging as one of the important transcriptional regulators of the antiviral innate immune response. Deconvolution algorithm using bulk gene expression data revealed decreased T-cell populations with higher expression of memory B cells in the vaccination breakthroughs. Thus, vaccination might synergize the innate immune response with humoral and T-cell correlates of protection to more rapidly clear SARS-CoV-2 infections and reduce symptoms within a shorter span of time. An important feature invariably noted after secondary vaccination is downregulation of ribosomal proteins, which might plausibly be an important factor arising from epigenetic reprogramming leading to innate immune tolerance. IMPORTANCE The development of multiple vaccines against SARS-CoV-2 infection is an unprecedented milestone achieved globally. Immunization of the mass population is a rigorous process for getting the pandemic under control, yet continuous challenges are being faced, one of them being breakthrough infections. This is the first study wherein the vaccination breakthrough cases of COVD-19 relative to unvaccinated infected individuals have been explored. In the context of vaccination, how do innate and adaptive immune responses correspond to SARS-CoV-2 infection? How do these responses culminate in a milder observable phenotype with shorter hospital stay in vaccination breakthrough cases compared with the unvaccinated? We identified a subdued transcriptional landscape in vaccination breakthroughs with decreased expression of a large set of immune and ribosomal proteins genes. We propose a module of innate immune memory, i.e., immune tolerance, which plausibly helps to explain the observed mild phenotype and fast recovery in vaccination breakthroughs.

A deep learning predictive model for public health concerns and hesitancy toward the COVID-19 vaccines

Throughout the pandemic era, COVID-19 was one of the remarkable unexpected situations over the past few years, but with the decentralization and globalization of efforts and knowledge, a successful vaccine-based control strategy was efficiently designed and applied worldwide. On the other hand, excused confusion and hesitation have widely impacted public health. This paper aims to reduce COVID-19 vaccine hesitancy taking into consideration the patient's medical history. The dataset used in this study is the Vaccine Adverse Event Reporting System (VAERS) dataset which was created as a corporation between the Food and Drug Administration (FDA) and Centers for Disease Control and Prevention (CDC) to gather reported side effects that may be caused by PFIEZER, JANSSEN, and MODERNA vaccines. In this paper, a Deep Learning (DL) model has been developed to identify the relationship between a certain type of COVID-19 vaccine (i.e. PFIEZER, JANSSEN, and MODERNA) and the adverse reactions that may occur in vaccinated patients. The adverse reactions under study are the recovery condition, possibility to be hospitalized, and death status. In the first phase of the proposed model, the dataset has been pre-proceesed, while in the second phase, the Pigeon swarm optimization algorithm is used to optimally select the most promising features that affect the performance of the proposed model. The patient's status after vaccination dataset is grouped into three target classes (Death, Hospitalized, and Recovered). In the third phase, Recurrent Neural Network (RNN) is implemented for both each vaccine type and each target class. The results show that the proposed model gives the highest accuracy scores which are 96.031% for the Death target class in the case of PFIEZER vaccination. While in JANSSEN vaccination, the Hospitalized target class has shown the highest performance with an accuracy of 94.7%. Finally, the model has the best performance for the Recovered target class in MODERNA vaccination with an accuracy of 97.794%. Based on the accuracy and the Wilcoxon Signed Rank test, we can conclude that the proposed model is promising for identifying the relationship between the side effects of COVID-19 vaccines and the patient's status after vaccination. The study displayed that certain side effects were increased in patients according to the type of COVID-19 vaccines. Side effects related to CNS and hemopoietic systems demonstrated high values in all studied COVID-19 vaccines. In the frame of precision medicine, these findings can support the medical staff to select the best COVID-19 vaccine based on the medical history of the patient.

Heart Rate Variability in Normotensive and Hypertensive Adults After a Year of Receiving Oxford/AstraZeneca COVID-19 Vaccine: A Cross-Sectional Observational Study

Background and aim Heart rate variability (HRV) helps in assessing the autonomic nervous system's function, which has been implicated in cardiovascular disease risk. HRV has been found to be deranged in hypertension. In addition, studies have shown that COVID-19 infection and vaccination can affect HRV. However, the long-term effect of HRV on hypertension has not been explored after COVID-19 vaccination. The objective of this study was to observe the HRV in hypertensive adults after one year of receiving the Oxford/AstraZeneca COVID-19 vaccine and to compare it with normotensive adults. Methods The study included 105 normotensives (blood pressure below 120/80 mmHg) and 75 hypertensive participants who had received the Oxford/AstraZeneca COVID-19 vaccine one year prior. HRV was measured using the PowerLab system (ADInstruments) with the participants in a sitting posture. The HRV parameters assessed included the time domain, frequency domain, and nonlinear measures. Data were presented in descriptive and inferential statistical terms, and the parameters of two groups of individuals were compared by either an unpaired t-test or the Mann-Whitney U test. Results A total of 105 normotensive participants with a mean age of 42.51 ± 9.28 years and 75 hypertensive participants with a mean age of 44.24 ± 10.19 years comprised the sample (p=0.24). Normotensive individuals had a higher standard deviation of RR intervals, a higher coefficient of variation of RR intervals, a higher standard deviation of heart rate, and a higher percentage of successive differences in RR intervals in the time domain. They also had higher values of very low-frequency power, low-frequency (LF) power, and high-frequency (HF) power in the frequency domain. The LF/HF ratio was not significantly different between the two groups. In nonlinear analysis, SD2, a measure of long-term heart rate variability, was higher in normotensive individuals. Conclusion The Oxford/AstraZeneca COVID-19 vaccine did not have a significant effect on HRV parameters in normotensive and hypertensive adults one year after vaccination. However, changes in HRV parameters were observed between supine and standing positions, suggesting the importance of postural changes in HRV assessment.

The efficacy and effectiveness of COVID-19 vaccines around the world: a mini-review and meta-analysis

OBJECTIVES

This meta-analysis evaluated the Efficacy and Effectiveness of several COVID-19 vaccines, including AstraZeneca, Pfizer, Moderna, Bharat, and Johnson & Johnson, to better estimate their immunogenicity, benefits, or side effects.

METHODS

Studies reporting the Efficacy and Effectiveness of COVID-19 vaccines from November 2020 to April 2022 were included. The pooled Effectiveness/Efficacy with a 95% confidence interval (95% CI) with Metaprop order was calculated. The results were presented in forest plots. Predefined subgroup analyses and sensitivity analyses were also performed.

RESULTS

A total of twenty articles were included in this meta-analysis. After the first dose of the vaccine, the total effectiveness of all COVID-19 vaccines in our study was 71% (95% CI 0.65, 0.78). The total effectiveness of vaccines after the second dose was 91% (95% CI 0.88, 0.94)). The total efficacy of vaccines after the first and second doses was 81% (95% CI 0.70, 0.91) and 71% (95% CI 0.62, 0.79), respectively. The effectiveness of the Moderna vaccine after the first and second dose was the highest among other studied vaccines ((74% (95% CI, 0.65, 0.83) and 93% (95% CI, 0.89, 0.97), respectively). The highest first dose overall effectiveness of the studied vaccines was against the Gamma variant (74% (95% CI, 0.73, 0.75)), and the highest effectiveness after the second dose was observed against the Beta variant (96% (95% CI, 0.96, 0.96)). The Efficacy for AstraZeneca and Pfizer vaccines after the first dose was 78% (95% CI, 0.62, 0.95) and 84% (95% CI, 0.77, 0.92), respectively. The second dose Efficacy for AstraZeneca, Pfizer, and Bharat was 67% (95% CI, 0.54, 0.80), 93% (95% CI, 0.85, 1.00), and 71% (95% CI, 0.61, 0.82), respectively. The overall efficacy of first and second dose vaccination against the Alfa variant was 84% (95% CI, 0.84, 0.84) and 77% (95% CI, 0.57, 0.97), respectively, the highest among other variants.

CONCLUSION

mRNA-based vaccines against COVID-19 showed the highest total efficacy and effectiveness than other vaccines. In general, administering the second dose produced a more reliable response and higher effectiveness than a single dose.

Potential treatments of COVID-19: Drug repurposing and therapeutic interventions

The coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The infection is caused when Spike-protein (S-protein) present on the surface of SARS-CoV-2 interacts with human cell surface receptor, Angiotensin-converting enzyme 2 (ACE2). This binding facilitates SARS-CoV-2 genome entry into the human cells, which in turn causes infection. Since the beginning of the pandemic, many different therapies have been developed to combat COVID-19, including treatment and prevention. This review is focused on the currently adapted and certain other potential therapies for COVID-19 treatment, which include drug repurposing, vaccines and drug-free therapies. The efficacy of various treatment options is constantly being tested through clinical trials and in vivo studies before they are made medically available to the public.

Spatial shifting of COVID-19 clusters and disease association with environmental parameters in India: A time series analysis

BACKGROUND

The viability and virulence of COVID-19 are complex in nature. Although the relationship between environmental parameters and COVID-19 is well studied across the globe, in India, such studies are limited. This research aims to explore long-term exposure to weather conditions and the role of air pollution on the infection spread and mortality due to COVID-19 in India.

METHOD

District-level COVID-19 data from April 26, 2020 to July 10, 2021 was used for the study. Environmental determinants such as land surface temperature, relative humidity (RH), Sulphur dioxide (SO₂), Nitrogen dioxide (NO₂), Ozone (O₃), and Aerosol Optical Depth (AOD) were considered for analysis. The bivariate spatial association was used to explore the spatial relationship between Case Fatality Rate (CFR) and these environmental factors. Further, the Bayesian multivariate linear regression model was applied to observe the association between environmental factors and the CFR of COVID-19.

RESULTS

Spatial shifting of COVID-19 cases from Western to Southern and then Eastern parts of India were well observed. The infection rate was highly concentrated in most of the Western and Southern regions of India, while the CFR shows more concentration in Northern India along with Maharashtra. Four main spatial clusters of infection were recognized during the study period. The time-series analysis indicates significantly more CFR with higher AOD, O₃, and NO₂ in India.

CONCLUSIONS

COVID-19 is highly associated with environmental parameters and air pollution in India. The study provides evidence to warrant consideration of environmental parameters in health models to mediate potential solutions. Cleaner air is a must to mitigate COVID-19.

Nucleic acid-based vaccine platforms against the coronavirus disease 19 (COVID-19)

The coronavirus disease 2019 (COVID-19) pandemic has infected 673,010,496 patients and caused the death of 6,854,959 cases globally until today. Enormous efforts have been made to develop fundamentally different COVID-19 vaccine platforms. Nucleic acid-based vaccines consisting of mRNA and DNA vaccines (third-generation vaccines) have been promising in terms of rapid and convenient production and efficient provocation of immune responses against the COVID-19. Several DNA-based (ZyCoV-D, INO-4800, AG0302-COVID19, and GX-19N) and mRNA-based (BNT162b2, mRNA-1273, and ARCoV) approved vaccine platforms have been utilized for the COVID-19 prevention. mRNA vaccines are at the forefront of all platforms for COVID-19 prevention. However, these vaccines have lower stability, while DNA vaccines are needed with higher doses to stimulate the immune responses. Intracellular delivery of nucleic acid-based vaccines and their adverse events needs further research. Considering re-emergence of the COVID-19 variants of concern, vaccine reassessment and the development of polyvalent vaccines, or pan-coronavirus strategies, is essential for effective infection prevention.

Real-time updating of dynamic social networks for COVID-19 vaccination strategies

Vaccination strategy is crucial in fighting the COVID-19 pandemic. Since the supply is still limited in many countries, contact network-based interventions can be most powerful to set an efficient strategy by identifying high-risk individuals or communities. However, due to the high dimension, only partial and noisy network information can be available in practice, especially for dynamic systems where contact networks are highly time-variant. Furthermore, the numerous mutations of SARS-CoV-2 have a significant impact on the infectious probability, requiring real-time network updating algorithms. In this study, we propose a sequential network updating approach based on data assimilation techniques to combine different sources of temporal information. We then prioritise the individuals with high-degree or high-centrality, obtained from assimilated networks, for vaccination. The assimilation-based approach is compared with the standard method (based on partially observed networks) and a random selection strategy in terms of vaccination effectiveness in a SIR model. The numerical comparison is first carried out using real-world face-to-face dynamic networks collected in a high school, followed by sequential multi-layer networks generated relying on the Barabasi-Albert model emulating large-scale social networks with several communities.

Barriers and Facilitators of COVID-19 Vaccination Outreach Program in Rural India: A Qualitative Study

Background Primary health centres are in charge of effectively implementing the COVID-19 vaccination program in rural areas. So, the study was planned to seek insight into the challenges faced by health personnel in the effective implementation of the COVID-19 vaccination program. Methodology The study was conducted in a rural area of Akola district which lies in the western parts of Maharashtra State and belongs to the Vidarbha region and is said to be one of the progressive districts in the region. A qualitative study was planned to understand the barriers and facilitators of the COVID-19 vaccine implementation program at rural and tribal areas. The study participants were medical officers from rural and tribal areas who actively planned and implemented COVID-19 vaccination at the primary health centre. A total of 30 medical officers were interviewed. Interview questions were focussed on the planning of COVID-19 vaccination in their area. Other questions were the problem faced during the implementation of the COVID-19 vaccination program and how it has been tackled. Results The factors identified were grouped into three groups: Health system factors, Human resource factors and Community level factors. Health system factors like shortage of vaccines and syringes, tablet paracetamol, online digital method of vaccination registration, overcrowding at the initial stage, and inadequate infrastructure were barriers to vaccination. Fear about vaccine adverse events, even in healthcare workers (HCWs), and overburdened healthcare workers were also factors affecting vaccination. At the community level, high resistance initially and misconception about the vaccine, and also the fear about post-vaccination side effects have an impact on the COVID-19 vaccination program in rural and tribal areas. Conclusion The successful vaccination rate among the population needs community leadership and a community-centred approach when conducting outreach and strengthening primary health care in terms of infrastructure, manpower, and capacity building of healthcare staff.

Adenoviral Vector-Based Vaccine Platform for COVID-19: Current Status

The coronavirus disease (COVID-19) breakout had an unimaginable worldwide effect in the 21st century, claiming millions of lives and putting a huge burden on the global economy. The potential developments in vaccine technologies following the determination of the genetic sequence of SARS-CoV-2 and the increasing global efforts to bring potential vaccines and therapeutics into the market for emergency use have provided a small bright spot to this tragic event. Several intriguing vaccine candidates have been developed using recombinant technology, genetic engineering, and other vaccine development technologies. In the last decade, a vast amount of the vaccine development process has diversified towards the usage of viral vector-based vaccines. The immune response elicited by such vaccines is comparatively higher than other approved vaccine candidates that require a booster dose to provide sufficient immune protection. The non-replicating adenoviral vectors are promising vaccine carriers for infectious diseases due to better yield, cGMP-friendly manufacturing processes, safety, better efficacy, manageable shipping, and storage procedures. As of April 2022, the WHO has approved a total of 10 vaccines around the world for COVID-19 (33 vaccines approved by at least one country), among which three candidates are adenoviral vector-based vaccines. This review sheds light on the developmental summary of all the adenoviral vector-based vaccines that are under emergency use authorization (EUA) or in the different stages of development for COVID-19 management.

Analysis of the opinions of individuals on the COVID-19 vaccination on social media

The COVID-19 pandemic continues to threaten public health globally. To develop effective interventions and campaigns to raise vaccination rates, policy makers need to understand people's attitudes towards vaccination. We examine the perspectives of people in India, the United States, Canada, and the United Kingdom on the administration of different COVID-19 vaccines. We analyse how public opinion and emotional tendencies regarding the COVID-19 vaccines relate to popular issues on social media. We employ machine learning algorithms to forecast thoughts based on the social media posts. The prevailing emotional tendency indicates that individuals have faith in immunisation. However, there is a likelihood that significant statements or events on a national, international, or political scale influence public perception of vaccinations. We show how public health officials can track public attitudes and opinions towards vaccine-related information in a geo-aware manner, respond to the sceptics, and increase the level of vaccine trust in a particular region or community.

An optimization framework for COVID-19 vaccine allocation and inventory management: A case study

As the novel coronavirus pandemic wreaked havoc globally, governments have implemented massive vaccination programs to tackle it. However, since the pandemic's emergence moves beyond the second year, some issues have stymied vaccination programs, including vaccine hesitancy, vaccine distribution inequality, new strains of the virus, and a possibility that the virus enters a stage of a requirement for cyclical vaccination. These challenges highlight the need for an appropriate mass COVID-19 vaccination program. Therefore, we attempt to address this problem by developing a bi-objective integrated vaccine allocation and inventory management framework. The goal is to minimize the system costs while maximizing the vaccination service level. Several important factors, such as multiple types of vaccines, the vaccines' perishability concept, demand uncertainty, and motivational strategy, have been addressed using dynamic planning. Besides that, the model development mechanism is carried out to be compatible and applicable to the current general vaccination program policies, forcing few strategic changes. Then, a case study concerning the vaccination program of the city of Mashhad in Iran is applied to the model. The results demonstrated significant advantages in total cost, vaccine shortage, and wastage compared to the current policy. Finally, the Lagrangian relaxation method is implemented on the model to strengthen further its capacity to handle larger-scale problems.

A pilot study of “adverse events following immunization” surveillance with COVID-19 vaccination among adolescents: A prospective observational study based on single-center experience from a tertiary care hospital

BACKGROUND:

COVID-19 vaccination was started on January 3, 2022, among children aged 15–-18 years with Covaxin vaccination. Subsequently, Corbevax was approved for age groups up to 12 years of age since March 16, 2022.

OBJECTIVES:

To know the incidence and spectrum of adverse effects following immunization (AEFI) for this newly approved COVID-19 vaccine for children.

DESIGN:

This was a prospective observational pilot study undertaken in a tertiary-level care hospital.

MATERIALS AND METHODS:

All children vaccinated at our tertiary care center in South India were enrolled after informed consent. AEFI at 30 min, up to 24 h, and 1–7 days postvaccination are noted. The causality assessment was done.

RESULTS:

A total of 36 participants were studied, out of which 24 received Covaxin and 12 received Corbevax. No immediate AEFI was noted with any vaccine. Up to 24 h, 22/36 (61%) AEFI noted where 12/24 (50%) with Covaxin and 10/12 (83.3%) with Corbevax. Postvaccination within 1–7 days, only 1 (2.8%) side effects were present with Covaxin. Fever was reported statistically more in the Corbevax vaccine (P = 0.03).

CONCLUSION:

Corbevax and Covaxin both are safer vaccines for children. None of the vaccines had any major side effects. Maximum AEFI noted were up to 24 h postvaccination.

Analysis of performance of Covid-19 vaccine supply chain in India

Purpose

This study aims to analyse the structure of the Indian vaccine supply chain (SC) during the Covid-19 crisis and explore the underlying challenges at each stage in the network. It also brings out the difference in performance of various constituent states.

Design/methodology/approach

This study relied on both primary and secondary data for the analyses. For the primary data, the study gathered experts’ opinions to validate the authors’ inferences. For the secondary data, it relies on government data provided in websites.

Findings

Based on the quartile analysis and cluster analysis of the secondary data, the authors find that the constituent states responded differently during the first and second waves. This was due to the differences in SC characteristics attributed to varied demographics and administrative efficiency.

Research limitations/implications

This paper’s analyses is primarily limited to secondary information and inferences are based on them. The study has important implications for implementing the large-scale vaccination drives by government and constituent states for better coordination and last-mile delivery.

Originality/value

The contribution is unique in studying the performance of constituent states using statistical techniques, with secondary data from authentic sources. It is also unique in combining this observation with validation from experts.

Knowledge And Attitudes Toward the COVID-19 Vaccine Among India's General Rural Population

Introduction

Even after the enforcement of the lockdown, the government was unable to control the spread of the COVID-19 infection. Vaccination is the only remaining hope for preventing and controlling COVID-19 infections. The knowledge and attitude of the recipients can influence vaccine acceptance. In this study, we aim to assess the knowledge and attitude toward the COVID-19 vaccine among the general rural population of India.

Methodology

A community-based, prospective, cross-sectional study was conducted from May 2021 to October 2021 in the rural part of the Mandya district of Karnataka, India. Individuals over the age of 18 who met the Ministry of Health and Family Welfare's vaccination eligibility criteria were included in the study. Demographic details of participants and assessment of knowledge and attitude towards the COVID-19 vaccine were done in a designed and validated data collection form.

Results

The study included 596 participants, with females dominating males by 54.9 % (327). The average age of the participants was 31 years. Among them, 81.71% (487) had adequate knowledge, and 81.5% (486) had a positive attitude towards the COVID-19 vaccine. Females (85.3%, 279) tend to have a more positive attitude than males (77%, 207). Positive attitude participants (86.86 %, 423) have a higher level of knowledge about the COVID-19 vaccine than negative attitude participants (57.79 %, 63).

Conclusion

In the study, we found that 81.71% had adequate knowledge and 81.5% had a positive attitude toward the COVID-19 vaccine.

Adverse events associated with Covishield vaccination among healthcare workers in a tertiary hospital in South India

Background

Vaccination is the most important prophylactic measure taken to curb COVID-19 pandemics. This study was undertaken to throw light on the safety of Covishield vaccine among health care workers (HCWs) and to assess the co-variates associated with incidence of adverse events.

Methods

This prospective observational study was conducted in a tertiary care center in South India as part of the HCW vaccination drive. All consenting HCWs who received the first dose of Covishield vaccine and developed ADRs were included in this study. After vaccination, all beneficiaries were monitored for AEFI for a period of half an hour and later followed up through telephone and google survey forms on day 2 and day 7 of vaccination. The data was subsequently collated into spreadsheet format and analyzed.

Results

The study included 1264 consenting healthcare workers who were predominantly youth, aged 15-24 years (n = 583, 46 %) and with a female preponderance of 76 % (n = 960). Past history of COVID-19 infections was reported among 4.6 % (58) of the study population. Postvaccination symptoms were majorly reported during the first (40 %) and second day (44 %) after vaccination with a high prevalence of both local (n = 1083, 85 %) and systemic symptoms (n = 1065, 84 %). The mean duration of symptoms was observed to be 1.4 ± 0.81 days post vaccination. Symptoms were observed significantly high among females (76.7 %, p = 0.013). The prevalence of systemic (88 % vs 80 %) (p < 0.001) and allergic symptoms (7 % vs 3 %; p = 0.03) were observed to be significantly high among respondents with <25 years of age. The systemic and allergic symptoms following vaccination were reported to be low among healthcare workers who had a previous history of COVID-19 infection.

Conclusion

COVID vaccination has been observed to be safe and well tolerated with more systemic symptoms reported among younger age group and females.

Epidemiological impact of COVID-19 in India: Country with second foremost positive cases in the world

The WHO tentatively called the new virus 2019 novel corona virus (COVID-19), which is become a effectively contagious disease in global health concern. India is the world's seventh-largest country, with twenty-eight (28) states and eight (8) union territories. In India, the highest COVID-19 case was recorded on 6th may 2021 which is 4,14,433 cases in the single day. On September 2020th, Maharashtra (11,45,840), Tamil Nadu (5,25,420) and Delhi (2,34,701) have the foremost COVID-19, and on May 2021st, Maharashtra (51,01,737), Tamil Nadu (13,80,259) and Delhi (13,23,567) have the foremost COVID-19 in India. Also, these states show the high death rate than other states. The positive COVID-19 cases are very drastically increased and death cases in these states due to the high population density. Hand hygiene, social distancing, and quarantine are some of the precautions that must be taken to prevent the virus from spreading in society. By increasing the detecting and testing capacity of the COVID-19 positive patients are also the way to enable the reduction of secondary cases with stricter quarantine rules.

A COVID-19 model incorporating variants, vaccination, waning immunity, and population behavior

Vaccines for COVID-19 have allowed countries to combat the spread of the disease. However, new variants have resulted in significant spikes in cases and raised severe health and economic concerns. We present a COVID-19 model to predict coupled effects of vaccine multiple-dose roll-out strategies, vaccine efficacy, waning immunity, population level of caution, sense of safety, under-reporting of cases, and highly prevalent variants such as the Delta (B.1.617.2) and Omicron (B.1.1.529). The modeling framework can incorporate new variants as they emerge to give critical insights into the new cases and guide public policy decision-making concerning vaccine roll-outs and reopening strategies. The model is shown to recreate the history of COVID-19 for five countries (Germany, India, Japan, South Africa, and the United States). Parameters for crucial aspects of the pandemic, such as population behavior, new variants, vaccination, and waning immunity, can be adjusted to predict pandemic scenarios. The model was used to conduct trend analysis to simulate pandemic dynamics taking into account the societal level of caution, societal sense of safety, and the proportions of individuals vaccinated with first, second, and booster doses. We used the results of serological testing studies to estimate the actual number of cases across countries. The model allows quantification of otherwise hard to quantify aspects such as the infectious power of variants and the effectiveness of government mandates and population behavior. Some example cases are presented by investigating the competitive nature of COVID variants and the effect of different vaccine distribution strategies between immunity groups.