Covid: IISc, Australia researchers develop math model to predict vaccination efficacy

BENGALURU: Researchers from the Indian Institute of Science (IISc) and Queensland Brain Institute (QBI) in Australia have developed a mathematical model that predicts how antibodies generated by Covid-19 vaccines confer protection against symptomatic infections.
In a study published in Nature Computational Science, the researchers, while pointing out how Covid-19 vaccines have been a game-changer in the current pandemic with several candidates having conferred a high degree of protection and some reducing the number of symptomatic infections by over 95% in clinical trials, asked "But what determines this extent of protection?"
The answer to this question, they said would help optimise the use of available vaccines and speed up the development of new ones.
"Researchers at IISc and QBI in Australia have now addressed this question by developing a mathematical model," IISc said in a statement.
The researchers first analysed more than 80 different neutralising antibodies reported to be generated after vaccination against the surface spike protein of SARS-CoV-2.
"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 which is a small, random subset of this landscape," IISc added.
The team, it said, then developed a mathematical model to simulate infections in a virtual patient population of about 3,500 with different antibody profiles, and to predict how many of them would be protected from symptomatic infection following vaccination.
“The reason predicting vaccine efficacies has been hard is that the processes involved are complex and operate at many interconnected levels,” Narendra Dixit, professor at the Department of Chemical Engineering, IISc, and the senior author of the study, said.
“Vaccines trigger a number of different antibodies, each affecting virus growth in the body differently. This in turn affects the dynamics of the infection and the severity of the associated symptoms. Further, different individuals generate different collections of antibodies and in different amounts," Dixit added.
Pranesh Padmanabhan, Research Fellow at QBI, the first author of the study said the diversity of antibody responses was a challenge to comprehend and quantify.
"The model developed by the team was able to predict the level of protection that would be conferred after vaccination based on the antibody ‘profile’ of the individual, and the predictions were found to closely match efficacies reported in clinical trials for all the major approved vaccines," IISc said.
The researchers, who also observed that vaccine efficacy was linked to a readily measurable metric called antibody neutralization titre, said this opens up the possibility of using such models to test future vaccines for their efficacies before elaborate clinical trials.
Dixit, however, cautions that the study is based on current vaccines which have been 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.