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 effectiveness of interventions. Asymptomatic breakthrough infections have been a major problem during the ongoing surge of Delta variant globally. Serological discrimination of vaccine response from infection has so far been limited to Spike protein vaccines used in the higher-income regions. Here, we show for the first time how statistical and machine learning (ML) approaches can discriminate SARS-CoV-2 infection from immune response to an inactivated whole virion vaccine (BBV152, Covaxin, India), thereby permitting real-world vaccine effectiveness assessments from cohort-based serosurveys in Asia and Africa where such vaccines are commonly used. Briefly, we accessed serial data on Anti-S and Anti-NC antibody concentration values, along with age, sex, number of doses, and number of days since the last vaccine dose for 1823 Covaxin recipients. An ensemble ML model, incorporating a consensus clustering approach alongside the support vector machine (SVM) model, was built on 1063 samples where reliable qualifying data existed, and then applied to the entire dataset. Of 1448 self-reported negative subjects, 724 were classified as infected. Since the vaccine contains wild-type virus and the antibodies induced will neutralize wild type much better than Delta variant, we determined the relative ability of a random subset of such samples to neutralize Delta versus wild type strain. In 100 of 156 samples, where ML prediction differed from self-reported uninfected status, Delta variant, was neutralized more effectively than the wild type, which cannot happen without infection. The fraction rose to 71.8% (28 of 39) in 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.
Subject(s)
COVID-19 , Breakthrough PainABSTRACT
BackgroundIndia has been amongst the most affected nations during the SARS-CoV2 pandemic, with sparse data on country-wide spread of asymptomatic infections and antibody persistence. This longitudinal cohort study was aimed to evaluate SARS-CoV2 sero-positivity rate as a marker of infection and evaluate temporal persistence of antibodies with neutralization capability and to infer possible risk factors for infection. MethodsCouncil of Scientific and Industrial Research, India (CSIR) with its more than 40 laboratories and centers in urban and semi-urban settings spread across the country piloted the pan country surveillance. 10427 adult individuals working in CSIR laboratories and their family members based on voluntary participation were assessed for antibody presence and stability was analyzed over 6 months utilizing qualitative Elecsys SARS CoV2 specific antibody kit and GENScript cPass SARS-CoV2 Neutralization Antibody Detection Kit. Along with demographic information, possible risk factors were evaluated through self to be filled online forms with data acquired on blood group type, occupation type, addiction and habits including smoking and alcohol, diet preferences, medical history and transport type utilized. Symptom history and information on possible contact and compliance with COVID 19 universal precautions was also obtained. Findings1058 individuals (10{middle dot}14%) had antibodies against SARS-CoV2. A follow-up on 346 sero-positive individuals after three months revealed stable to higher antibody levels against SARS-CoV2 but declining plasma activity for neutralizing SARS-CoV2 receptor binding domain and ACE2 interaction. A repeat sampling of 35 individuals, at six months, revealed declining antibody levels while the neutralizing activity remained stable compared to three months. Majority of sero-positive individuals (75%) did not recall even one of nine symptoms since March 2020. Fever was the most common symptom with one-fourth reporting loss of taste or smell. Significantly associated risks for sero-positivity (Odds Ratio, 95% CI, p value) were observed with usage of public transport (1{middle dot}79, 1{middle dot}43 - 2{middle dot}24, 2{middle dot}81561E-06), occupational responsibilities such as security, housekeeping personnel etc. (2{middle dot}23, 1{middle dot}92 - 2{middle dot}59, 6{middle dot}43969E-26), non-smokers (1{middle dot}52, 1{middle dot}16 - 1{middle dot}99, 0{middle dot}02) and non-vegetarianism (1{middle dot}67, 1{middle dot}41 - 1{middle dot}99, 3{middle dot}03821E-08). An iterative regression analysis was confirmatory and led to only modest changes to estimates. Predilections for sero-positivity was noted with specific ABO blood groups -O was associated with a lower risk. InterpretationIn a first-of-its-kind study from India, we report the sero-positivity in a country-wide cohort and identify variable susceptible associations for contacting infection. Serology and Neutralizing Antibody response provides much-sought-for general insights on the immune response to the virus among Indians and will be an important resource for designing vaccination strategies. FundingCouncil of Scientific and Industrial Research, India (CSIR)