Math model to predict COVID-19 vaccine efficacy
Part of: Prelims and GS-III Science and Technology
Context: Researchers at the Indian Institute of Science and Queensland Brain Institute in Australia have developed a mathematical model that predicts how antibodies generated by COVID-19 vaccines confer protection against symptomatic infections.
- Several vaccines offer a high degree of protection, with some reducing the number of symptomatic infections by over 95% in clinical trials.
- The model developed by the team was able to predict the level of protection that would be available after vaccination based on the antibody ‘profile’ of the individual.
- The predictions were found to closely match efficacies reported in clinical trials for all the major approved vaccines.
- The researchers also observed that vaccine efficacy was linked to a readily measurable metric called antibody neutralisation titre.
- This opens up the possibility of using such models to test future vaccines for their efficacy before elaborate clinical trials are launched..
- This formalism is yet to be applied to the new variants, including Omicron.
Do you know?
- The reason predicting vaccine efficacies has been hard is that the processes involved are complex and operate at many interconnected levels.
- 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.
News Source: TH