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

Abstract

To understand the spread of SARS-CoV2, in August and September 2020, the Council of Scientific and Industrial Research (India), conducted a sero-survey 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 sero-positivity was higher in densely populated cities and was inversely correlated with a 30 day change in regional test positivity rates (TPR). Regional seropositivity above 10% was associated with declining TPR. Personal factors associated with higher odds of sero-positivity were high-exposure work (Odds Ratio, 95% CI, 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).

Seroprevalence of IgG antibodies against SARS-CoV-2 in India, March 2020 to August 2021: a systematic review and meta-analysis

“…Murhekar et al, 2020; M. V. M. V. Murhekar, et al, 2021;Naushin et al, 2021;Padma et al, 2021;Parai et al, 2021;Prakash et al, 2021a. ;Prakash et al, 2021b;Prakash et al, 2021c;Prakash et al, 2021d;Rafi et al, 2021;Ray et al, 2020;Satpati et al, 2020;Selvaraju et al, 2021;Sen et al, 2021;N.…”

Cross-sectional genomic perspective of epidemic waves of SARS-CoV-2: A pan India study

“…Pan India study of 1000 sequences across ten states suggests the widespread presence of the several lineages of SARS-CoV-2 [13] . Pan India sero survey suggested average seropositivity to be 10.14% (among 10,427 subjects) [22] . Unfortunately, the spread of lineages across India and seropositivity rate is very complex due to the vast population and landmass.…”

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

“…In contrast, serology-based assessment of vaccine effectiveness becomes more pertinent in the context of the general population, especially where RT-PCR testing is infrequent and viral load is insignificant [ 13 , 14 ]. Vaccines targeted specifically to the spike protein (anti-S) do not pose a problem since antibodies against Nucleocapsid proteins (anti-NC) is taken as a marker of infection [ 15 ]. However, for whole virion vaccines, anti-NC is induced by the vaccine itself [ 7 ] that poses challenges in identifying infection status and hence ascertaining the vaccine protection effectiveness.…”