Researchers from India’s Indian Institute of Science (IISc.) and Australia’s Queensland Brain Institute (QBI) have developed a mathematical model that predicts how COVID-19 vaccination antibodies confer protection against symptomatic illnesses. Nature Computational Science published the research. Vaccination has been hailed as a key component in limiting the damage caused by the third wave of Covid-19 infections. Several vaccinations provide substantial levels of protection, with some clinical trials showing that they can reduce the number of symptomatic infections by up to 95%. What, however, defines the scope of protection?
IISc researchers look over 80 antibodies
The IISc researchers looked at over 80 distinct neutralizing antibodies that were known to be produced following vaccination against SARS-CoV-2, the virus that causes COVID-19. These antibodies can stay in the blood for months and block the spike protein, preventing viral entry. According to the researchers, these 80 antibodies form a ‘landscape’ or shape space,’ and each person develops a unique ‘profile’ of antibodies that is a small, random subset of this landscape.
The IIsc researchers then created a mathematical model to simulate illnesses in a simulated patient population of roughly 3,500 people with various antibody profiles and forecast how many of them would be protected from symptomatic infection after immunization.
“Predicting vaccine efficacies has been difficult since the systems involved are complicated and operate at multiple levels.” Vaccines produce a variety of antibodies, each of which has a different effect on virus growth in the body. This, in turn, has an impact on the infection’s dynamics and the severity of its symptoms. According to Narendra Dixit, a professor at the Department of Chemical Engineering at IISc and the study’s senior author, “different individuals generate various collections of antibodies and in varied numbers.”
“Understanding and quantifying the variability of antibody responses was a challenge,” said Pranesh Padmanabhan, a Research Fellow at QBI and the study’s first author.
The team’s model was able to estimate the level of protection imparted after vaccination based on an individual’s antibody ‘profile,’ and the predictions were found to closely match efficacies observed in clinical trials for all of the major licensed vaccines. Vaccine efficacy was also connected to an easily observable parameter termed antibody neutralization titer, according to the researchers. This opens up the option of utilizing such models to assess the efficacy of future vaccines before launching large-scale clinical trials.
Prof. Dixit, on the other hand, stated that the research is based on current vaccinations that are meant to act on the original SARS-CoV-2 strain. “We have yet to apply our formalism to the novel varieties, such as Omicron, where additional immune system arms, not only antibodies, appear to be contributing to vaccine efficacies.” “Studies are being conducted to remedy this,” he explained.