Insights from a Pan India Sero-Epidemiological survey (Phenome-India Cohort) for SARS-CoV2

To understand the spread of SARS-CoV2, in August and September 2020, the Council of Scientific and Industrial Research (India) conducted a serosurvey across its constituent laboratories and centers across India. Of 10,427 volunteers, 1058 (10.14%) tested positive for SARS-CoV2 anti-nucleocapsid (anti-NC) antibodies, 95% of which had surrogate neutralization activity. Three-fourth of these recalled no symptoms. Repeat serology tests at 3 (n = 607) and 6 (n = 175) months showed stable anti-NC antibodies but declining neutralization activity. Local seropositivity was higher in densely populated cities and was inversely correlated with a 30-day change in regional test positivity rates (TPRs). Regional seropositivity above 10% was associated with declining TPR. Personal factors associated with higher odds of seropositivity were high-exposure work (odds ratio, 95% confidence interval, p value: 2.23, 1.92-2.59, <0.0001), use of public transport (1.79, 1.43-2.24, <0.0001), not smoking (1.52, 1.16-1.99, 0.0257), non-vegetarian diet (1.67, 1.41-1.99, <0.0001), and B blood group (1.36, 1.15-1.61, 0.001).

A machine learning-based approach to determine infection status in recipients of BBV152 (Covaxin) whole-virion inactivated SARS-CoV-2 vaccine for serological surveys

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.

Survivorship approaches to measuring and comparing cull rates for dairies

A study was undertaken to develop the use of survivorship methods in characterizing the magnitude of culling and in testing for differences in culling among dairy herds. A prospective observational study was conducted on nine herds representing 19482 cows. The cull rate derived from survivorship data was estimated as the weighted slope of the cumulative proportion of cows remaining in a herd after first parturition, where cumulative proportion was computed using a cohort life-table with intervals of 1 month. Cull rates ranged from 9.0-13.8% per 12 months of age, compared with culling density rates of 22.2-39.7 culled per 100 cow-years. Comparison of ranks of density rates, weighted-slope rates and median ages at culling among the herds illustrated that the measures were not interchangeable. An advantage of a survivorship approach to measuring culling was illustrated by the use of the Cox proportional hazards model that tested for differences in cull rates among herds. Results suggested that variation in culling among herds during the first lactation, and particularly during the first part of the first lactation, may be an important consideration in future studies of optimal culling practices. In addition to being able to compare culling among herds, a survivorship approach to measuring culling provides an estimate of the rate of removal that is not biased by age, in contrast to currently used methods.

PI and fuzzy logic controllers for shunt Active Power Filter--a report

The authors acknowledge certain errors in their recently published paper titled "PI and fuzzy logic controllers for shunt active power filter--A report.The ambiguity in band width calculation of adaptive hysteresis controller and control aspects of dc-link voltage issues are addressed. The shunt APF system is validated through extensive simulation and the results are support features of the proposed technique.