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1.
Comput Biol Med ; 146: 105419, 2022 07.
Article in English | MEDLINE | ID: covidwho-1803804

ABSTRACT

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.


Subject(s)
COVID-19 , Viral Vaccines , COVID-19/epidemiology , COVID-19/prevention & control , COVID-19 Vaccines/therapeutic use , Humans , Machine Learning , Pandemics , SARS-CoV-2 , Vaccines, Inactivated , Virion
2.
Science ; 374(6570): 995-999, 2021 Nov 19.
Article in English | MEDLINE | ID: covidwho-1526449

ABSTRACT

Delhi, the national capital of India, experienced multiple severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreaks in 2020 and reached population seropositivity of >50% by 2021. During April 2021, the city became overwhelmed by COVID-19 cases and fatalities, as a new variant, B.1.617.2 (Delta), replaced B.1.1.7 (Alpha). A Bayesian model explains the growth advantage of Delta through a combination of increased transmissibility and reduced sensitivity to immune responses generated against earlier variants (median estimates: 1.5-fold greater transmissibility and 20% reduction in sensitivity). Seropositivity of an employee and family cohort increased from 42% to 87.5% between March and July 2021, with 27% reinfections, as judged by increased antibody concentration after a previous decline. The likely high transmissibility and partial evasion of immunity by the Delta variant contributed to an overwhelming surge in Delhi.


Subject(s)
COVID-19/epidemiology , COVID-19/virology , Genome, Viral , Adolescent , Adult , COVID-19/immunology , COVID-19/transmission , Child , Humans , Immune Evasion , India/epidemiology , Molecular Epidemiology , Phylogeny , Reinfection , Seroepidemiologic Studies , Young Adult
3.
IJID Reg ; 2: 1-7, 2022 Mar.
Article in English | MEDLINE | ID: covidwho-1521056

ABSTRACT

Background: COVID-19 emerged as a global pandemic in 2020, spreading rapidly to most parts of the world. The proportion of infected individuals in a population can be reliably estimated via serosurveillance, making it a valuable tool for planning control measures. Our serosurvey study aimed to investigate SARS-CoV-2 seroprevalence in the urban population of Hyderabad at the end of the first wave of infections. Methods: This cross-sectional survey, conducted in January 2021 and including males and females aged 10 years and above, used multi-stage random sampling. 9363 samples were collected from 30 wards distributed over six zones of Hyderabad, and tested for antibodies against SARS-CoV-2 nucleocapsid antigen. Results: Overall seropositivity was 54.2%, ranging from 50% to 60% in most wards. Highest exposure appeared to be among those aged 30-39 and 50-59 years, with women showing greater seropositivity. Seropositivity increased with family size, with only marginal differences among people with varying levels of education. Seroprevalence was significantly lower among smokers. Only 11% of the survey subjects reported any COVID-19 symptoms, while 17% had appeared for COVID-19 testing. Conclusion: Over half the city's population was infected within a year of onset of the pandemic. However, ∼ 46% of people remained susceptible, contributing to subsequent waves of infection.

7.
Elife ; 102021 04 20.
Article in English | MEDLINE | ID: covidwho-1194809

ABSTRACT

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).


Subject(s)
Antibodies, Neutralizing/blood , Antibodies, Viral/blood , COVID-19 Serological Testing , COVID-19/epidemiology , SARS-CoV-2/immunology , Biomarkers/blood , COVID-19/diagnosis , COVID-19/immunology , COVID-19/virology , Female , Host-Pathogen Interactions , Humans , Immunity, Humoral , India/epidemiology , Longitudinal Studies , Male , Predictive Value of Tests , Risk Assessment , Risk Factors , Seroepidemiologic Studies , Time Factors
8.
Open Forum Infect Dis ; 7(11): ofaa434, 2020 Nov.
Article in English | MEDLINE | ID: covidwho-926341

ABSTRACT

BACKGROUND: From an isolated epidemic, coronavirus disease 2019 has now emerged as a global pandemic. The availability of genomes in the public domain after the epidemic provides a unique opportunity to understand the evolution and spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus across the globe. METHODS: We performed whole-genome sequencing of 303 Indian isolates, and we analyzed them in the context of publicly available data from India. RESULTS: We describe a distinct phylogenetic cluster (Clade I/A3i) of SARS-CoV-2 genomes from India, which encompasses 22% of all genomes deposited in the public domain from India. Globally, approximately 2% of genomes, which to date could not be mapped to any distinct known cluster, fall within this clade. CONCLUSIONS: The cluster is characterized by a core set of 4 genetic variants and has a nucleotide substitution rate of 1.1 × 10-3 variants per site per year, which is lower than the prevalent A2a cluster. Epidemiological assessments suggest that the common ancestor emerged at the end of January 2020 and possibly resulted in an outbreak followed by countrywide spread. To the best of our knowledge, this is the first comprehensive study characterizing this cluster of SARS-CoV-2 in India.

9.
Biol Methods Protoc ; 5(1): bpaa017, 2020.
Article in English | MEDLINE | ID: covidwho-722724

ABSTRACT

Rigorous testing is the way forward to fight the coronavirus disease 2019 pandemic. Here we show that the currently used and most reliable reverse transcription-polymerase chain reaction-based severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) procedure can be further simplified to make it faster, safer, and economical by eliminating the RNA isolation step. The modified method is not only fast and convenient but also at par with the traditional method in terms of accuracy, and therefore can be used for mass screening. Our method takes about half the time and is cheaper by ∼40% compared to the currently used method. We also provide a variant of the new method that increases the efficiency of detection by ∼30% compared to the existing procedure. Taken together, we demonstrate a more effective and reliable method of SARS-CoV-2 detection.

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