With the continuous emergence of SARS-CoV-2 variants of concern and implementation of mass-scale interventions like vaccination, understanding factors affecting disease transmission has critical implications for control efforts. Here we used a simple adapted N95 mask sampling method to demonstrate the impact of circulating SARS-CoV-2 variants and vaccination on 92 COVID-19 patients to expel virus into the air translating to a transmission risk. Between July and September 2021, when the Delta was the dominant circulating strain in Mumbai, we noted a two-fold increase in the proportion of people expelling virus (95%), about an eighty-fold increase in median viral load and a three-fold increase in high emitter type (41%; people expelling >1000 viral copy numbers in 30 minutes) compared to initial strains of 2020. Eight percent of these patients continued to be high emitters even after eight days of symptom onset, suggesting a probable increased transmission risk for Delta strain even at this stage. There was no significant difference in expelling pattern between partial, full and un-vaccinated individuals suggesting similar transmission risk. We noted significantly more infections among vaccinated study patients and their household members than unvaccinated, probably due to increased duration from vaccination and/or increased risk behaviour upon vaccination due to lower perceived threat. This study provides biological evidence for possible continued transmission of the Delta strain even with vaccination, emphasizing the need to continue COVID-19 appropriate behaviour. The study also indicates that the mask method may be useful for screening future vaccine candidates, therapeutics or interventions for their ability to block transmission.

The present study was initiated to understand the proportion of predominant variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in postvaccination infections during the Delta dominated second wave of coronavirus disease 2019 (COVID-19) in the Mumbai Metropolitan Region (MMR) in India and to understand any mutations selected in the postvaccination infections or showing association with any patient demographics. Samples were collected (n = 166) from severe/moderate/mild COVID-19 patients who were either vaccinated (COVISHIELD/COVAXIN-partial/fully vaccinated) or unvaccinated, from a city hospital and from home isolation patients in MMR. A total of 150 viral genomes were sequenced by Oxford Nanopore sequencing and the data of 136 viral genomes were analyzed for clade/lineage and for identifying mutations. The sequences belonged to three clades (21A, 21I, and 21J) and their lineage was identified as either Delta (B.1.617.2) or Delta+ (B.1.617.2 + K417N) or sub-lineages of Delta variant (AY.120/AY.38/AY.99). A total of 620 mutations were identified of which 10 mutations showed an increase in trend with time (May-October 2021). Associations of six mutations (two in spike, three in orf1a, and one in nucleocapsid) were shown with milder forms of the disease and one mutation (in orf1a) with partial vaccination status. The results indicate a trend toward reduction in disease severity as the wave progressed.

Vaccination against SARS-CoV-2 was launched in India in January 2021. Though vaccination reduced hospitalization and mortality due to COVID-19, vaccine breakthrough infections have become common. The present study was initiated in May 2021 to understand the proportion of predominant variants in post-vaccination infections during the Delta dominated second wave of COVID-19 in the Mumbai Metropolitan Region (MMR) in India and to understand any mutations selected in the post-vaccination infections or showing association with any patient demographics. We collected samples (n=166) from severe/moderate/mild COVID-19 patients who were either vaccinated (COVISHIELD/COVAXIN; partial/fully vaccinated) or unvaccinated, from a city hospital and from home isolation patients in MMR. A total of 150 viral genomes were sequenced by Oxford Nanopore sequencing (using MinION) and the data of 136 viral genomes were analyzed for clade/lineage and for identifying mutations in all the genomes. The sequences belonged to three clades (21A, 21I and 21J) and their lineage was identified as either Delta (B.1.617.2) or Delta+ (B.1.617.2 + K417N) or sub-lineages of Delta variant (AY.120/AY.38/AY.99). A total of 620 mutations were identified of which 10 mutations showed an increase in trend with time (May-Oct 2021). Associations of 6 mutations (2 in spike, 3 in orf1a and 1 in nucleocapsid) were shown with milder forms of the disease and one mutation (in orf1a) with partial vaccination status. The results indicate a trend towards reduction in disease severity as the wave progressed.

This study used an adapted N95 mask sampling to understand the effect of COVID‐19 vaccination in the context of circulating variants on infected individuals to emit the virus into the air, a key risk factor of transmission. Mask, swab, and blood samples were collected from 92 COVID‐19 patients vaccinated (Covishield/COVAXIN‐partial/fully) or unvaccinated between July and September 2021 during the Delta‐dominated period in Mumbai. Mask/swab samples were analysed by RT‐PCR for viral RNA. Blood was evaluated for SARS‐CoV‐2 anti‐spike and nucleocapsid antibody responses. At < 48 hours of diagnosis, 93% of the patients emitted detectable viral RNA, with 40% emitting >1000 copies in 30‐minutes (high emitters). About 8% continued to be high emitters even after eight days of symptom onset. No significant difference was observed in emission patterns between partial, full and un‐vaccinated patients. However, when vaccinated patients were stratified based on spike protein neutralisation and nucleocapsid IgG, the group with moderate/high neutralisation showed a significantly lower proportion of high emitters and viral RNA copies than the group with no/low neutralisation, which further reduced in the group having anti‐nucleocapsid IgG. In conclusion, mask sampling showed that Delta infections were associated with greater virus emission in patients, which was significantly reduced only in vaccinated patients with moderate/high SARS‐CoV2 neutralisation, especially with evidence of past infection. The study demonstrated that mask sampling could be useful for understanding the transmission risk of emerging variants, screening vaccine/booster candidates and guiding control interventions. This article is protected by copyright. All rights reserved.

The rapid dissemination of antimicrobial resistance (AMR) has emerged as a serious health problem on an unprecedented global scale. AMR is predicted to kill more than 10 million people annually by 2050 leading to huge economic losses worldwide. Therefore, urgent action is required at the national as well as international levels to avert this looming crisis. Effective surveillance can play an important role in the containment of AMR spread by providing data to help determine AMR hotspots, predict an outbreak, maintain proper stewardship and propose immediate and future plans of action in this respect. Although many existing databases provide genetic and molecular information on AMR in microorganisms, there is no dedicated database of AMR from non-clinical samples. The FEAMR database is a one-of-its-kind database to provide manually collated and curated information on the prevalence of AMR in food and the environment. For designing the FEAMR webpage, Microsoft Visual Studio with HTML, CSS, ASP.NET, Bootstrap for the front-end and C# for the back-end were used. The FEAMR database is a free access resource ( https://feamrudbt-amrlab.mu.ac.in/ ), accepting verified food- and environment-related AMR submissions from across the globe. To the best of our knowledge, it is probably the first database providing AMR-related surveillance data from non-clinical samples. It is designed from the ‘One Health Approach’ perspective to help in the containment of global AMR spread. Graphical Abstract Flowsheet of steps for making FEAMR database 1. Research articles relating to Antimicrobial Resistance (AMR) were searched on the internet. 2. Data relating to AMR were retrieved from these articles and stored in an MS-Excel sheet. 3. The web pages of the FEAMR database (DB) were created using Microsoft Visual Studio (MVS) and its various tools. HTML, CSS, ASP.NET and Bootstrap were used for the front end and C# used for the back-end of the website. 4. The DB of FEAMR was created using MS SQL Server which was controlled by SQL Server Management Studio (SSMS). 5. The data from the MS-Excel sheet in step 2 was stored in the SQL server and displayed on the web page using GridView tool of MVS and C#. The database created was then uploaded on the University of Mumbai (UoM) website, where it can be accessed by all users having the link to the DB ( https://feamrudbt-amrlab.mu.ac.in/ ).