This study aimed to investigate the association between lifetime occupational history and risk of buccal mucosa cancer (BMC).
We utilized a multi-centric, hospital-based case-control study across ...five centres of Tata Memorial Centre, Mumbai, India. Cases included men aged 20–75-years with histological confirmed primary cancer of the buccal mucosa. Visitor controls were frequency matched to cases for age (10 years interval) and current residential zone. Study participants were interviewed face-to-face. Logistic regression was performed to estimate odds ratio (OR) and 95 % confidence intervals (CI).
Among ever employed males, we identified 1969 BMC cases and 2145 controls. We observed an increased risk of BMC in ‘Craft and Related Trades Workers’ (OR 1.37; 95 % CI 1.13–1.65), ‘Plant and Machine Operators and Assemblers’ (OR: 1.26; 95 % CI 1.01–1.56), and ‘Elementary Occupations’ (OR:1.33; 95 % CI 1.12–1.58). More specifically, the increased risk was observed for ‘Metal, Machinery and Related Trades Workers’, ‘Handicraft and Printing Workers’, ‘Drivers and Mobile Plant Operators’, and ‘Laborers in Mining, Construction, Manufacturing and Transport’.
Our findings suggest that certain occupations may be at a higher risk of BMC. Some fraction of BMC can be prevented by reducing exposure to hazardous agents used in these occupations. Further research is needed to identify which exposures are responsible for the increased risk. Moreover, tobacco control and early detection activities can be focused towards these occupations as tobacco consumption is also high in them, which may also be the reason for increased risk observed in these groups.
•We observed an increased risk of BMC in ‘Craft and Related Trades Workers’, ‘Plant and Machine Operators and Assemblers’, and ‘Elementary Occupations’.•More specifically, the increased risk was observed for ‘Metal, Machinery and Related Trades Workers’, ‘Handicraft and Printing Workers’, ‘Drivers and Mobile Plant Operators’, and ‘Labourers in Mining, Construction, Manufacturing and Transport’.•Even though we adjusted for tobacco use, the rates of chewing were high in these occupations, which may explain some of the associations that we observed.
Data science has been an invaluable part of the COVID-19 pandemic response with multiple applications, ranging from tracking viral evolution to understanding the vaccine effectiveness. Asymptomatic ...breakthrough infections have been a major problem in assessing vaccine effectiveness in populations globally. Serological discrimination of vaccine response from infection has so far been limited to Spike protein vaccines since whole virion vaccines generate antibodies against all the viral proteins. Here, we show how a statistical and machine learning (ML) based approach can be used to discriminate between SARS-CoV-2 infection and immune response to an inactivated whole virion vaccine (BBV152, Covaxin). For this, we assessed serial data on antibodies against Spike and Nucleocapsid antigens, along with age, sex, number of doses taken, and days since last dose, for 1823 Covaxin recipients. An ensemble ML model, incorporating a consensus clustering approach alongside the support vector machine model, was built on 1063 samples where reliable qualifying data existed, and then applied to the entire dataset. Of 1448 self-reported negative subjects, our ensemble ML model classified 724 to be infected. For method validation, we determined the relative ability of a random subset of samples to neutralize Delta versus wild-type strain using a surrogate neutralization assay. We worked on the premise that antibodies generated by a whole virion vaccine would neutralize wild type more efficiently than delta strain. In 100 of 156 samples, where ML prediction differed from self-reported uninfected status, neutralization against Delta strain was more effective, indicating infection. We found 71.8% subjects predicted to be infected during the surge, which is concordant with the percentage of sequences classified as Delta (75.6%–80.2%) over the same period. Our approach will help in real-world vaccine effectiveness assessments where whole virion vaccines are commonly used.
•Covaxin or BBV152 induces antibodies to all viral proteins.•Differentiating infection vs vaccine induced immunity is thus difficult.•This poses difficulty in determining vaccine effectiveness.•A hybrid ML based approach utilizing serology was developed.•Covaxin was observed to have 55.67% effectiveness.
Seroepidemiology and genomic surveillance are valuable tools to investigate infection transmission during a pandemic. North East (NE) India is a strategically important region being the gateway ...connecting the country with Southeast Asia. Here, we examined the spread of SARS-CoV-2 in NE India during the first and second waves of COVID-19 using serological and whole genome sequencing approaches.
qRT-PCR analysis was performed on a selected population (n = 16,295) from June 2020 to July 2021, and metadata was collected. Immunoassays were studied (n = 2026) at three-time points (August 2020, February 2021, and June 2021) and in a cohort (n = 35) for a year. SARS-CoV-2 whole genomes (n = 914) were sequenced and analyzed with those obtained from the databases.
Test positivity rates (TPR) in the first and second waves were 6.34% and 6.64% in Assam, respectively, and a similar pattern was observed in other NE states. Seropositivity in the three time points was 10.63%, 40.3%, and 46.33%, respectively, and neutralizing antibody prevalence was 90.91%, 52.14%, and 69.30%, respectively. Persistence of pan-IgG-N SARS-CoV-2 antibody for over a year was observed among three subjects in the cohort group. Normal variants dominated the first wave, while B.1.617.2 and AY-sublineages dominated the second wave in the region. The prevalence of the variants co-related well with high TPR and seropositivity rate in the region and identified mostly among vaccinated individuals.
The COVID-19 first wave in the region witnessed low transmission with the evolution of diverse variants. Seropositivity increased during the study period with over half of the individuals carrying neutralizing antibodies against SARS-CoV-2. High infection and seroprevalence in NE India during the second wave were associated with the dominant emergence of variants of concern.
