Mathematical model to predict COVID-19 vaccine efficacy
June 9, 2026
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Home Bharat

Mathematical model to predict COVID-19 vaccine efficacy

WEBDESKWEBDESK
Mar 4, 2022, 01:05 am IST
in Bharat, Delhi, Sci & Tech
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An artist’s rendition of SARS-CoV-2 viral particles with spike proteins blocked by antibodies (Image: Lensmedical)

An artist’s rendition of SARS-CoV-2 viral particles with spike proteins blocked by antibodies (Image: Lensmedical)

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 The team developed a mathematical model to simulate infections in a virtual patient population of about 3,500 people with different antibody profiles and to predict how many of them would be protected from symptomatic infection following vaccination.

 

New Delhi, March 03: Vaccines have been a game-changer in the current COVID-19 pandemic. Several vaccine candidates have conferred a high degree of protection, with some even bringing down the number of symptomatic infections by over 95% in clinical trials. But what determines this extent of protection? An answer to this question would help optimise available vaccines and speed up the development of new ones.

A team of researchers at the Bengaluru-based Indian Institute of Science (IISc) and Queensland Brain Institute (QBI) in Australia have addressed this question by developing a mathematical model that predicts how antibodies are generated by COVID-19 vaccines confer
protection against symptomatic infections. The team has published a report of their study in Nature Computational Science.

The researchers began by analysing over 80 different neutralising antibodies reported to be generated after vaccination against the surface spike protein of SARS-CoV-2, the virus that causes COVID-19. These antibodies are typically present in the blood for months and prevent virus entry by blocking the spike protein. The researchers hypothesised that these 80 antibodies constitute a ‘landscape’ or ‘shape space’, and each individual produces a unique ‘profile’ of antibodies, a small, random subset of this landscape.

The team then developed a mathematical model to simulate infections in a virtual patient population of about 3,500 people with different antibody profiles and to predict how many of them would be protected from symptomatic infection following vaccination. The predictions were found to closely match efficacies reported in clinical trials for all the major approved vaccines.

Professor at the Department of Chemical Engineering, IISc, and the senior author of the study, Narendra Dixit, however, cautions that the study is based on current vaccines designed to work on the original SARS-CoV-2 strain. “Our formalism is yet to be applied to the new variants, including Omicron, where other arms of the immune system and not just antibodies appear to be contributing to vaccine efficacies. Studies are ongoing to address this,” he said. (India Science Wire)

 

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