Concept illustration of vaccine with numbers.

The mathematical model reflects how the booster effect can fade quickly in patients with suppressed immune responses, including cancer patients receiving immunosuppressive treatment.

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Health

Measuring the power of vaccines

3 min read

Comparison of booster effectiveness shows that different patient groups have different needs

Researchers have designed a mathematical model that can predict the course of vaccine-induced immunity against COVID-19 in different patient populations — including otherwise-healthy individuals and those who have cancer or suppressed immune responses — over the long term.

The model, which was developed by a Massachusetts General Hospital-led team in collaboration with scientists at the University of Cyprus, also makes predictions under potential future scenarios (such as the emergence of variants with greater immune evasion) and reveals the benefits of the new bivalent vaccines.

The model builds on a previously developed mathematical framework that researchers used to understand why treatment responses vary widely among people with COVID-19 and to identify biological markers related to these different responses, published in PNAS in 2021.

In the new study, also published in PNAS, the scientists addressed the need for predictions of vaccine effectiveness over time.

“We used this model to simulate how differences in viral, patient, and vaccine characteristics may affect COVID-19 outcomes,” said senior author Rakesh K. Jain, director of the E.L. Steele Laboratories for Tumor Biology at MGH and the Andrew Werk Cook Professor of Radiation Oncology at Harvard Medical School.

For example, the model incorporates different COVID variants, including hypothetical ones; original and bivalent forms of the vaccine; and different considerations for certain patients — such as interactions between the virus, immune cells, and tumor cells in a person with cancer.

The model predicts that a booster dose of either the Pfizer-BioNTech or Moderna mRNA vaccine can induce robustly enhanced antibody- and immune-cell-based responses to provide sufficient protection for more than a year in healthy individuals. However, the booster effect can fade quickly in patients with suppressed immune responses, including cancer patients receiving immunosuppressive treatment.

The analysis also revealed that the optimal schedule for booster doses is not the same for all variants.

“Our results could help inform the timing of booster vaccinations in individuals with different characteristics and comorbidities, as well as for novel viral variants,” Jain said. “As we approach an endemic phase of SARS-CoV-2, a rational approach to vaccine booster utilization may help ensure equitable access to vaccines and help prevent further outbreaks and development of new variants.”

Co-corresponding authors are Lance L. Munn, MGH, and Triantafyllos Stylianopoulos, University of Cyprus. Other MGH authors are Chrysovalantis Voutouri, C. Corey Hardin, Vivek Naranbhai, Mohammad R. Nikmaneshi, Melin J. Khandekar, and Justin F. Gainor.

Jain’s research is supported by grants from National Institutes of Health, the National Foundation for Cancer Research, Jane’s Trust Foundation, Niles Albright Research Foundation, and Harvard Ludwig Cancer Center. Munn’s research is supported by a National Institutes of Health grant. Stylianopoulos’ research is supported by the European Research Council and Cyprus Research and Innovation Foundation.