A Computational Model that Simulates the Human Immune System’s Response to Measles Vaccination

Measles is a highly contagious viral disease that poses a substantial public health risk. Vaccination is the primary strategy for measles prevention, requiring a 95% global coverage with two doses of the MMR (measles, mumps, and rubella) vaccine. Although the vaccine is 98% effective, the spread of anti-vaccine sentiment and misinformation about immunization mechanisms has significantly reduced vaccination rates, allowing the virus to persist. In 2016, there were 132,490 reported cases of measles globally; this number increased to 837,922 in 2019. This work presents a computational model, based on a previously established model from the literature, that simulates the immune response to measles vaccination. The objectives are to: (1) create an effective simulation tool that can model diverse vaccination scenarios, thereby reducing dependence on extensive clinical trials; (2) assess the immunological response to the measles vaccine through computational simulations, conserving both time and resources; and (3) conduct sensitivity analysis of the model’s parameters to identify key immune components and their interactions, leading to the most effective immune response.