Mathematical model predicts effectiveness of COVID-19 vaccines

15 March 2022



Researchers at The University of Queensland have developed a mathematical model that can predict the efficacy of COVID-19 vaccines, potentially speeding-up the development of new vaccines.

Dr Pranesh Padmanabhan
Dr Pranesh Padmanabhan.

The Queensland Brain Institute’s (QBI) Dr Pranesh Padmanabhan, working with researchers from the Indian Institute of Science, produced a model that predicts the effectiveness of the antibody response in patients receiving one of eight major vaccines. 

Dr Padmanabhan said the research established a framework for predicting the efficacy of new vaccines against future strains of the SARS CoV-2 virus.

“The ability to predict vaccine efficacies could expedite vaccine development by helping shortlist promising candidates and minimise reliance on expensive and time-consuming clinical trials,” Dr Padmanabhan said.

Model predicts antibody response

Since the start of the COVID 19 pandemic, researchers and scientists have been scrambling to develop vaccines candidates to protect against the SARS-CoV-2 virus and keep ahead of its mutations. 

Dr Padmanabhan and his colleague analysed 80 individual antibodies from 20 studies to construct a mathematical model of SARS-CoV-2 antibodies.

“The model we developed reliably predicted the diversity of the antibody response within and across vaccinated individuals,” he said.

They then analysed clinical trial data for eight major vaccines and found a relationship between vaccine protection against SARS CoV-2 and the potential antibody response.

“The main predictions are the influence of vaccination on the severity of disease and the population-level protection conferred by the eight approved COVID-19 vaccines,” Dr Padmanabhan said. 

“Using this model, we aim to predict the efficacies of new vaccines against different variants without relying heavily on clinical trials.” 

Understanding variables of vaccine response

Professor Narendra Dixit from the Indian Institute of Science said the major challenge was to understand and describe the vast variability in the antibody responses elicited by the vaccine.

“Overcoming this challenge would allow predicting the fraction of the vaccinated individuals who would generate strong enough responses to be protected from serious infection,” Professor Dixit said.

“By deducing links between the activity of antibodies, its variability, antibody generation by vaccination, and the resulting protection conferred upon populations, our study offers exciting insights into the workings of COVID-19 vaccines.”

This research was a result of an international collaboration between the QBI and the Indian Institute of Science and was published in Nature Computational Science.

Media: QBI Communications,; Merrett Pye,, + 61 (0) 422 096 049; Elaine Pye,, + 61 (0) 415 222 606.