Efficient diagnosis and ICU patient monitoring model

Healthcare is a sector that is expeditiously developing in technology and services. In recent years, the Covid-19 pandemic has drastically affected the working of the healthcare sector;people are apprehended to visit hospitals for any treatment. But evolution in modern technologies has opened multiple paths to improve and modernize the working of the healthcare sector. The proposed system is a multi-layered disease prediction model that analyzes numerous factors for predicting diseases. The system analyzes the symptoms using a modified decision tree algorithm that predicts the possible illness and suggests the test accordingly. The model is trained individually for each type of test format. For image type, reports were classified with convolutional neural networks. For PDF type, the data was extracted using optical character recognition (OCR). The model uses the Levenshtein distance to find unigrams and bigrams. The match is further analyzed, and a detailed summary of the report gets generated. Report summary and the predicted disease are provided to the patient with the list of home remedies. Further, a specialized doctor receives all the medical diagnosis details when a patient books an appointment. Hospitals usually face the problem of patient versus nurse ratio. It creates management issues to the critical ward. Patients are left unattended and can cause death threats. The proposed system analyzes multiple and dynamic factors. It increases the accuracy of the prediction. The proposed hospital monitoring system observes the vital signs on the patient monitors beside the ICU beds and notifies the hospital staff after encountering the abnormality. The model dynamically calculates the threshold value for each vital sign considering multiple factors like age, gender, and medical history of the patient. By understanding the patient's current medical condition, the model responds to change in vital signs and gives an idea about the organ's condition. Machine learning algorithm-random forest regression helps in calculating the threshold values of heart rate (HR) and respiratory rate (RR). Equations for blood pressure (BP) get the threshold values depending on age and gender. These custom thresholds for specific patients reduce false alarms, which was a significant concern in the previous monitoring system. © 2023 River Publishers.

Translating Telemedicine to Thoracic Surgical Oncological Care: Performance Analysis and Patient Perceptions During the COVID-19 Pandemic.

OBJECTIVE: The objective is to determine how the COVID-19 pandemic affected care for patients undergoing thoracic surgery for cancer. BACKGROUND: The COVID-19 pandemic accelerated the adoption of telemedicine. METHODS: Characteristics and outcomes of new patients seen between March 1 and June 30, 2019, and the same period in 2020 were compared. Patients who did not undergo surgery were excluded. Patients who had a telemedicine visit (new and established) in the 2020 period were asked to complete a survey. RESULTS: In total, 624 new patients were seen in 2019 versus 299 in 2020 (52% reduction); 45% of patients (n=136) in 2020 were seen via telemedicine. There was no statistically significant difference in time to surgery, pathological upstaging, or postsurgical complications between 2019 and 2020. In total, 1085 patients (new and established) had a telemedicine visit in 2020; 239 (22%) completed the survey. A majority replied that telemedicine was equivalent to in-person care (77%), did not impair care quality (84%), resulted in less stress (69%) and shorter waits (86%), was more convenient (92%), saved money and commuting time (93%), and expanded who could attend visits (91%). Some patients regretted the loss of human interaction (71%). Most would opt for telemedicine after the pandemic (60%), although some would prefer in-person format for initial visits (55%) and visits with complex discussions (49%). Only 21% were uncomfortable with the telemedicine technology. CONCLUSIONS: Telemedicine enabled cancer care to continue during the COVID-19 pandemic without delays in surgery, cancer progression, or worsened postoperative morbidity and was generally well received.

Importance of IP-10 as a biomarker of host immune response: Critical perspective as a target for biosensing

While the exploration into biomolecules for diagnostic and prognostic devices continues to develop, many molecules continue to be examined for individual diseases or treatments. Consequently, it can be difficult to fully understand the scope of one individual molecule's current and potential clinical utilization. The scope of this study aimed to assess the potential of Interferon Gamma-induced Protein 10 (IP-10) as a biomarker in a wide variety of diseases, both as a main and supplemental indicator of disease infection and progression. IP-10 is a chemokine secreted in response to IFN-gamma playing a major role in the activation and regulation of inflammatory and immune responses within the body. Currently, IP-10 has displayed potential application in diseases such as COVID-19, tuberculosis, sepsis, Kawasaki disease, cancer, and many more. Molecular assays developed for the detection of IP-10 take longer testing time, sophisticated instrument utilization, and need more sample volumes. These cannot be utilized for bedside patient monitoring during the illness state of the patient. Biosensing tools are alternative methods used at clinical sites due to their rapid results. Though many types of sensing mechanisms established for the detection of disease biomarkers such as optical, piezoelectric sensors, and electrochemical biosensors are far beyond the other sensing methods due to their ease of mechanism, rapid results, and portable nature. IP-10 has been a promising biomarker in different diseases, evaluation of IP-10 levels at different time points of treatments is necessary. To achieve this, current conventional methods cannot be used and thus a portable device that provides rapid results is in demand. Such point-of-care (POC) device development for IP-10 analysis is very crucial in the current scenario. Beyond this, the clarification of its physiological role in healthy and infected individuals could allow for more proper utilization in clinical diagnoses, prognoses, treatment monitoring, and more. Overall, this study was developed to summarize the associations currently created between levels of IP-10 and other biomolecules and diseases.Copyright © 2023 The Author(s)

Clinico-epidemiological and vaccination profile of patients attending flu clinic of a tertiary health care institution in Eastern India during the third wave of COVID-19 pandemic

Introduction and aim. With the third wave of COVID-19 hitting the country, there is an urgent need to systematically document the clinical-epidemiological and vaccination details of the patients to formulate evidence-based decisions. So, this study was planned to describe the profile of patients attending the flu clinic of a tertiary care hospital in eastern India. Material and methods. This hospital-based cross-sectional study was done for 6 weeks (Jan-Feb 2022) among 623 patients using a pre-tested, structured questionnaire related to COVID-19. An unadjusted odds ratio was calculated and statistical significance was attributed to a p-value <0.05. Results. Out of 623 patients, almost 90% of the patients were vaccinated against COVID-19 with at least one dose of any vaccine. Cough (57.8%) was the most common complaint. Patients aged > 60 years and those having one or more than one comorbidity suffered from moderate-severe COVID-19 infection when compared to their counterparts (p<0.001). Also, 2.1% of fully vaccinated, 3.8% of one dose vaccinated and 10.9% of unvaccinated patients suffered from moderate-severe COVID-19. Conclusion. During the third wave of the COVID-19 pandemic, a smaller number of elderlies compared to the previous two waves were affected indicating age shifting. The severity of COVID-19 was less among vaccinated individuals compared to unvaccinated highlighting the importance of COVID-19 vaccination. © 2022 Universidad Nacional de Colombia, , Department of Linguistics. All rights reserved.

Safety outcomes associated with the moderna COVID-19 vaccine (mRNA-1273): a literature review.

INTRODUCTION: Current safety data from Phase 3 clinical trials have concluded that apart from transient local and systemic reactions, no safety concerns were identified for the Moderna COVID-19 vaccine (mRNA-1273). However, Phase 3 studies are insufficient to detect rare adverse events (AEs). A literature search of the two major electronic databases, Embase and PubMed, was performed to enable the identification and characterization of all relevant articles from December 2020 to November 2022. AREAS COVERED: This narrative review summarizes the key safety outcomes associated with the mRNA-1273 vaccine to inform healthcare decisions and increase public awareness of mRNA-1273 vaccine safety. The primary adverse events (AEs) reported within a diverse population, receiving the mRNA-1273 vaccine, were; localized injection site pain, fatigue, headache, myalgia, and chills. In addition, the mRNA-1273 vaccine was also associated with; less than a 1-day change in the menstrual cycle, a 10-fold higher risk of myocarditis and pericarditis within young males aged 18-29 years and increased levels of anti-polyethylene glycol (PEG) antibodies. EXPERT OPINION: The transient nature of commonly observed AEs and the rare occurrence of severe events within mRNA-1273 recipients show no significant safety concerns which should prevent vaccination. However, large-scale epidemiological studies with longer follow-up periods are required to surveillance rare safety outcomes.

Acute renal failure and cardiac arrhythmias associated with remdesivir use in patients with COVID-19 infections: Analysis using the US FDA adverse event reporting system.

BACKGROUND: Recently, antivirals, including remdesivir, have been repurposed to treat COVID-19 infections. Initial concerns have been raised about the adverse renal and cardiac events associated with remdesivir. OBJECTIVE: This study aimed to analyse the adverse renal and cardiac events associated with remdesivir in patients with COVID-19 infections using the US FDA adverse event reporting system. METHOD: A case/non-case method was used to determine adverse drug events associated with remdesivir as the primary suspect drug between January 1, 2020, and November 11, 2021, for patients with COVID-19 infections. Cases were reports for remdesivir with ≥1 ADEs as preferred terms included in the Medical Dictionary of Regulatory Activities (MedDRA) system organ classes 'Renal and urinary disorders' or 'cardiac' disorders. To measure disproportionality in reporting of ADEs, frequentist approaches, including the proportional reporting ratio (PRR) and reporting odds ratio (ROR), were used. The empirical Bayesian Geometric Mean (EBGM) score and information component (IC) value were calculated using a Bayesian approach. A signal was defined as the lower limit of 95% confidence intervals of ROR ≥ 2, PRR ≥ 2, IC > 0, and EBGM > 1 for ADEs with ≥4 reports. Sensitivity analyses were undertaken by excluding reports for non-Covid indications and medications strongly associated with AKI and cardiac arrhythmias. RESULTS: In the main analysis for remdesivir use in patients with COVID-19 infections, we identified 315 adverse cardiac events comprising 31 different MeDRA PTs and 844 adverse renal events comprising 13 different MeDRA PTs. Regarding adverse renal events, disproportionality signals were noted for "renal failure" (ROR = 2.8 (2.03-3.86); EBGM = 1.92 (1.58-2.31), "acute kidney injury" (ROR = 16.11 (12.52-20.73); EBGM = 2.81 (2.57-3.07), "renal impairment" (ROR = 3.45 (2.68-4.45); EBGM = 2.02 (1.74-2.33). Regarding adverse cardiac events, strong disproportionality signals were noted for "electrocardiogram QT prolonged" (ROR = 6.45 (2.54-16.36); EBGM = 2.04 (1.65-2.51), "pulseless electrical activity" (ROR = 43.57 (13.64-139.20); EBGM = 2.44 (1.74-3.33), "sinus bradycardia" (ROR = 35.86 (11.16-115.26); EBGM = 2.82 (2.23-3.53), "ventricular tachycardia" (ROR = 8.73 (3.55-21.45); EBGM = 2.52 (1.89-3.31). The risk of AKI and cardiac arrythmias were confirmed by sensitivity analyses. CONCLUSION: This hypothesis-generating study identified AKI and cardiac arrhythmias associated with remdesivir use in patients with COVID-19 infections. The relationship between AKI and cardiac arrhythmias should be further investigated using registries or large clinical data to assess the impact of age, genetics, comorbidity, and the severity of Covid infections as potential confounders.

Mpox in persons living with HIV: Results from an international dermatologic registry

In 2022, mpox virus spread globally with 99% of cases in non-endemic countries. People living with HIV (PLHIV) are disproportionally affected, often with more severe clinical features and outcomes. The AAD/ILDS Dermatology COVID-19, Monkeypox (mpox), and Emerging Infections registry captured mpox cases from 13 non-endemic countries in a de-identified REDCap registry. We aimed to examine cutaneous symptomatology and outcomes in cases of mpox in PLHIV. Of 119 reported cases, 44 were PLHIV (35%). Cases were 98% male, with a median age of 38 years, located in Europe (57%) and the U.S. (39%). Nearly half of PLHIV reported skin lesions as their initial sign (45%), and 43 (98%) reported skin lesions during illness. The primary initial lesion locations were peri-anal (34%) and genito-inguinal (34%). Co-infection with other sexually transmissible infections (STI) was more common in PLHIV, 57% vs. 38% in all-registry cases (p<0.01). The most common co-infections were gonorrhea, syphilis, and chlamydia. Time to resolution was 17 days, 3 days shorter than all-registry cases, which may be due to higher use of Tecovirimat in PLHIV (36% vs. 25% in all-registry cases;p<0.01). There were no differences in the frequency of hospitalization or scarring. One death was reported. Overall, cutaneous lesion count was similar in PLHIV and all-registry cases. Lesion location was more frequently reported in the peri-anal and genito-inguinal regions. Sample size was insufficient to detect differences in length of infection, hospitalization, or scarring in PLHIV. Co-infections were more common in PLHIV, highlighting a need for co-testing for STIs during mpox evaluation.Copyright © 2023

Mpox first skin lesion location: A reflection of mode of transmission?

The 2022 mpox outbreak affected 84,318 individuals in 110 countries. Mpox is transmitted by multiple modalities, including direct contact, respiratory droplets, and fomites among others. Identifying skin lesions aids prompt diagnosis. Variation in initial skin lesion location is not well understood;it is hypothesized that mode of transmission may determine primary inoculation site and subsequent clinical presentation. This study sourced healthcare provider-reported data from the AAD/ILDS Dermatology COVID-19, Mpox, and Emerging Infections Registry to explore factors related to the location of the first skin lesion in mpox cases. Out 119 mpox cases,115 had primary lesion location data. 97% were male with a median age of 37. Most (83/115, 72%) patients had first skin lesions in the genito-anal area, and 32/115 (27%) had lesions elsewhere or had morbilliform rash. 74% of males had the first lesion in the genito-anal region compared to females (25%, p=0.03). Males in same-sex relationships had ano-genital lesions more often than men in other relationships (77% vs. 44%, p=0.03). The type of mpox exposure was also associated with first lesion location: 83% of patients who contracted mpox from a spouse or other sexual contact had ano-genital lesions as compared to a non-sexual contact (0%, p=<0.01). This analysis characterized factors associated with the first mpox skin lesion location, which can aid healthcare providers in diagnosis and shed light on transmission. This data suggests that type of exposure and mode of transmission may be associated with primary lesion location;patients who contracted mpox from sexual contact were more likely to have ano-genital lesions.Copyright © 2023

A Model to Detect Face Mask Using Deep Learning

Coronavirus pandemic started spreading in 2019 and is still spreading until now in 2021 all over the world. Due to this the healthcare sectors are going on crisis all over the world. One basic protective measure that we can implement in our daily life is wearing a face mask. Wearing a mask properly can control the spread of this virus to a great extent. Various regions have made wearing face mask mandatory to prevent spread of this virus. In this paper we have proposed a deep learning-based model to detect face mask using python, OpenCV, TensorFlow and it can be used in our health care sectors. © 2022 IEEE.

Transformative e-Learning: An IT Perspective on Education During Covid-19

The intensity of Covid-19's spread created havoc in humankind, where WHO warned to declare it a pandemic for the world. The pandemic's severity and its fast spread in society pressured the government to declare a lockdown and shutdown of various activities in several parts of the country. The pandemic adversely affected social gatherings and congregations aside from educational institutions and other modes of assembly of teachers and students. This resulted in the creation of a platform for online education to reduce the burden on students and teachers for the annual completion of various courses. It is highly essential to make an innovative platform for students and teachers to enhance the effectiveness of learning along with sustainability to face the challenges of the pandemic for a long duration. Various issues related to students and teachers are identified through the various e-learning platforms. A transformation of e-learning platforms is developed to minimize the huddles, especially among the economically backward students without appropriate infrastructure. © 2023 selection and editorial matter, Zdzislaw Polkowski, Samarjeet Borah, Sambit Kumar Mishra, and Darshana Desai;individual chapters, the contributors.

Addressing Online-Learning Challenges Through Smartphone-Based Gamified Learning Platform

Remote learning has been in the shadows of mainstream higher education institutions (HEI), with classroom/physical presence taking center stage. The Covid-19 pandemic disrupted the prevalent modes of education and pushed remote learning to the forefront. While remote learning has its advantages, there are also downsides, such as lack of learner engagement, learning fatigue, etc., resulting in less than satisfying learning outcomes. The pandemic also showed that simply moving existing teaching artifacts and methods to the virtual realm is not entirely adequate, especially for topics requiring experiential learning such as innovation and entrepreneurship. This project attempts to address some of these critical challenges by building a smartphone application platform for remote learning, emphasizing personalized and gamified learning. The project team adopted a creative approach to realize this ambitious project during the challenging pandemic by engaging current university students in all the implementation teams, eliminating the need to obtain external resources and funding. The student teams were motivated as the project was integrated with their regular university coursework. The gamified smartphone application with Design Thinking as the first learning module was developed and tested for functionality and usability. This project has received encouraging user feedback and provides a platform for developing and testing more engaging methods in the future for personalized remote learning, using artificial intelligence (AI) and machine learning (ML). © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Psychosocial Determinants of Covid Vaccine Hesitancy And Stage of Motivation In Lactating Women

Background: The Government of India recommends pregnant and lactating women to get vaccinated against the Novel Coronavirus Disease 2019 (COVID-19). However, vaccine hesitancy in this population adversely affects the uptake of vaccination. There is an urgent need for assessing extent of vaccine hesitancy in this group and study its determinants, motivation stages and barriers. Objective(s): To determine psychosocial Factors affecting uptake of COVID-19 Vaccination in lactating women and their attitude towards infant vaccination in general and stage of motivation for vaccination. Method(s): A cross-sectional analysis survey was conducted amongst 80 women visiting postnatal OPD or immunization clinic of a tertiary care hospital of Delhi using Oxford COVID-19 vaccine hesitancy scale (OC19-VHS) and participants were classified as hesitant, non-hesitant, and unsure. Result(s): We enrolled 80 postnatal women with mean age of 25.3 ((SD, 9.6) years. The vaccine hesitancy rate was 44% acceptance rate in the participants. Regression analysis showed young age group (20-45 years), low socioeconomic status and no past history of COVID infection were factors independently associated with Vaccine hesitancy. Doubts on vaccine safety and concerns about its impact on lactation were primary barriers affecting vaccine uptake. Amongst participants in vaccine hesitancy group only 40% had got their children completely vaccinated for age. Conclusion(s): Nearly 40% lactating women visiting hospital had vaccine hesitancy and concern for its impact on lactation and vaccine safety were the primary determinants for reduced vaccine uptake in lactating women.

Large-Scale Knowledge Synthesis and Complex Information Retrieval from Biomedical Documents

Recent advances in the healthcare industry have led to an abundance of unstructured data, making it challenging to perform tasks such as efficient and accurate information retrieval at scale. Our work offers an all-in-one scalable solution for extracting and exploring complex information from large-scale research documents, which would otherwise be tedious. First, we briefly explain our knowledge synthesis process to extract helpful information from unstructured text data of research documents. Then, on top of the knowledge extracted from the documents, we perform complex information retrieval using three major components- Paragraph Retrieval, Triplet Retrieval from Knowledge Graphs, and Complex Question Answering (QA). These components combine lexical and semantic-based methods to retrieve paragraphs and triplets and perform faceted refinement for filtering these search results. The complexity of biomedical queries and documents necessitates using a QA system capable of handling queries more complex than factoid queries, which we evaluate qualitatively on the COVID-19 Open Research Dataset (CORD-19) to demonstrate the effectiveness and value-add. © 2022 IEEE.

Expert review of global real-world data on COVID-19 vaccine booster effectiveness and safety during the omicron-dominant phase of the pandemic.

INTRODUCTION: COVID-19 vaccines have been highly effective in reducing morbidity and mortality during the pandemic. However, the emergence of the Omicron variant and subvariants as the globally dominant strains have raised doubts about the effectiveness of currently available vaccines and prompted debate about potential future vaccination strategies. AREAS COVERED: Using the publicly available IVAC VIEW-hub platform, we reviewed 52 studies on vaccine effectiveness (VE) after booster vaccinations. VE were reported for SARS-CoV-2 symptomatic infection, severe disease and death and stratified by vaccine schedule and age. In addition, a non-systematic literature review of safety was performed to identify single or multi-country studies investigating adverse event rates for at least two of the currently available COVID-19 vaccines. EXPERT OPINION: Booster shots of the current COVID-19 vaccines provide consistently high protection against Omicron-related severe disease and death. Additionally, this protection appears to be conserved for at least 3 months, with a small but significant waning after that. The positive risk-benefit ratio of these vaccines is well established, giving us confidence to administer additional doses as required. Future vaccination strategies will likely include a combination of schedules based on risk profile, as overly frequent boosting may be neither beneficial nor sustainable for the general population.

Deprescribing anticholinergic and sedative drugs to reduce polypharmacy in frail older adults living in the community: a randomized controlled trial.

BACKGROUND: Polypharmacy is associated with poor outcomes in older adults. Targeted deprescribing of anticholinergic and sedative medications may improve health outcomes for frail older adults. Our pharmacist-led deprescribing intervention was a pragmatic two-arm randomized controlled trial stratified by frailty. We compared usual care (control) with the intervention of pharmacists providing deprescribing recommendations to general practitioners. METHODS: Community-based older adults (≥65 years) from two New Zealand district health boards were recruited following a standardized interRAI needs assessment. The Drug Burden Index (DBI) was used to quantify use of sedative and anticholinergic medications for each participant. The trial was stratified into low, medium, and high frailty. We hypothesized that the intervention would increase the proportion of participants with a reduction in DBI ≥ 0.5 within six months. RESULTS: Of 363 participants, 21 (12.7%) in the control group and 21 (12.2%) in the intervention group had a reduction in DBI ≥ 0.5. The difference in the proportion of -0.4% (95%CI: -7.9% to 7.0%) provided no evidence of efficacy for the intervention. Similarly, there was no evidence to suggest the effectiveness of this intervention for participants of any frailty level. CONCLUSIONS: Our pharmacist-led medication review of frail older participants did not reduce the anticholinergic/sedative load within six months. Covid-19 lockdown measures required modification of the intervention. Subgroup analyses pre- and post-lockdown showed no impact on outcomes. Reviewing this and other deprescribing trials through the lens of implementation science may aid an understanding of the contextual determinants preventing or enabling successful deprescribing implementation strategies.

MASKED FACE RECOGNITION VIA SELF-ATTENTION BASED LOCAL CONSISTENCY REGULARIZATION

With the COVID-19 pandemic, one critical measure against infection is wearing masks. This measure poses a huge challenge to the existing face recognition systems by introducing heavy occlusions. In this paper, we propose an effective masked face recognition system. To alleviate the challenge of mask occlusion, we first exploit RetinaFace to achieve robust masked face detection and alignment. Secondly, we propose a deep CNN network for masked face recognition trained by minimizing ArcFace loss together with a local consistency regularization (LCR) loss. This facilitates the network to simultaneously learn globally discriminative face representations of different identities together with locally consistent representations between the non-occluded faces and their counterparts wearing synthesized facial masks. The experiments on the masked LFW dataset demonstrate that the proposed system can produce superior masked face recognition performance over multiple state-of-the-art methods. The proposed method is implemented in a portable Jetson Nano device which can achieve real-time masked face recognition. © 2022 IEEE.

Managing the Pandemic in the South Asian (SAARC) Countries

This paper explores the coronavirus pandemic response from a South Asian perspective. When their case numbers were still relatively low, the South Asian Association for Regional Cooperation (SAARC) countries adopted lockdowns at the same time or before India did. On 24 March 2020, when there were just two confirmed cases, Nepal went into lockdown, and Sri Lanka locked down on 22 March, when there were 78 cases. India locked down the day after Nepal, with all countries imposing some form of restrictions on people's movement. This paper draws its data from the first year of the pandemic that loomed in the SAARC nations. The regional cooperation provided by SAARC has allowed the sharing of resources and a strengthening of the region's self-reliance. Notably, the commitment made by India to ensure its neighbours are supplied with vaccines, many of these donated. The eight-member SAARC states are Afghanistan, Bangladesh, Bhutan, India, Maldives, Nepal, Pakistan, and Sri Lanka. This paper draws on the knowledge and perceptions of academics and social workers in the SAARC countries. It provides insight into the responses, impacts, vulnerabilities, and challenges faced by the region and in each specific country since the beginning of COVID-19. This paper also offers a discussion on vaccines, PPE, as well as the role of cooperation across the region. The relationship between India and the SAARC countries and its ‘neighbourhood first' policy are also discussed. © 2022 Pulla et al. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Safety and immunogenicity of SII-NVX-CoV2373 (COVID-19 vaccine) in adults in a phase 2/3, observer-blind, randomised, controlled study.

Background: NVX-CoV2373, a Covid-19 vaccine was developed in the USA with ∼90% efficacy. The same vaccine is manufactured in India after technology transfer (called as SII-NVX-CoV2373), was evaluated in this phase 2/3 immuno-bridging study. Methods: This was an observer-blind, randomised, phase 2/3 study in 1600 adults. In phase 2, 200 participants were randomized 3:1 to SII-NVX-CoV2373 or placebo. In phase 3, 1400 participants were randomized 3:1 to SII-NVX-CoV2373 or NVX-CoV2373 (940 safety cohort and 460 immunogenicity cohort). Two doses of study products (SII-NVX-CoV2373, NVX-CoV2373 or placebo) were given 3 weeks apart. Primary objectives were to demonstrate non-inferiority of SII-NVX-CoV2373 to NVX-CoV2373 in terms of geometric mean ELISA units (GMEU) ratio of anti-S IgG antibodies 14 days after the second dose (day 36) and to determine the incidence of causally related serious adverse events (SAEs) through 180 days after the first dose. Anti-S IgG response was assessed using an Enzyme-Linked Immunosorbent Assay (ELISA) and neutralizing antibodies (nAb) were assessed by a microneutralization assay using wild type SARS CoV-2 in participants from the immunogenicity cohort at baseline, day 22, day 36 and day 180. Cell mediated immune (CMI) response was assessed in a subset of 28 participants from immunogenicity cohort by ELISpot assay at baseline, day 36 and day 180. The total follow-up was for 6 months. Trial registration: CTRI/2021/02/031554. Findings: Total 1596 participants (200 in Phase 2 and 1396 in Phase 3) received the first dose. SII-NVX-CoV2373 was found non-inferior to NVX-CoV2373 (anti-S IgG antibodies GMEU ratio 0.91; 95% CI: 0.79, 1.06). At day 36, there was more than 58-fold rise in anti-S IgG and nAb titers compared to baseline in both the groups. On day 180 visit, these antibody titers declined to levels slightly lower than those after the first dose (13-22 fold-rise above baseline). Incidence of unsolicited and solicited AEs was similar between the SII-NVX-CoV2373 and NVX-CoV2373 groups. No adverse event of special interest (AESI) was reported. No causally related SAE was reported. Interpretation: SII-NVX-CoV2373 induced a non-inferior immune response compared to NVX-CoV2373 and has acceptable safety profile. Funding: SIIPL, Indian Council of Medical Research, Novavax.