Mechanistic model for booster doses effectiveness in healthy, cancer, and immunosuppressed patients infected with SARS-CoV-2.
Chrysovalantis VoutouriC Corey HardinVivek NaranbhaiMohammad R NikmaneshiMelin J KhandekarJustin F GainorTriantafyllos StylianopoulosLance L MunnRakesh K JainPublished in: Proceedings of the National Academy of Sciences of the United States of America (2023)
SARS-CoV-2 vaccines are effective at limiting disease severity, but effectiveness is lower among patients with cancer or immunosuppression. Effectiveness wanes with time and varies by vaccine type. Moreover, previously prescribed vaccines were based on the ancestral SARS-CoV-2 spike-protein that emerging variants may evade. Here, we describe a mechanistic mathematical model for vaccination-induced immunity. We validate it with available clinical data and use it to simulate the effectiveness of vaccines against viral variants with lower antigenicity, increased virulence, or enhanced cell binding for various vaccine platforms. The analysis includes the omicron variant as well as hypothetical future variants with even greater immune evasion of vaccine-induced antibodies and addresses the potential benefits of the new bivalent vaccines. We further account for concurrent cancer or underlying immunosuppression. The model confirms enhanced immunogenicity following booster vaccination in immunosuppressed patients but predicts ongoing booster requirements for these individuals to maintain protection. We further studied the impact of variants on immunosuppressed individuals as a function of the interval between multiple booster doses. Our model suggests possible strategies for future vaccinations and suggests tailored strategies for high-risk groups.
Keyphrases
- sars cov
- randomized controlled trial
- end stage renal disease
- copy number
- systematic review
- newly diagnosed
- ejection fraction
- chronic kidney disease
- respiratory syndrome coronavirus
- papillary thyroid
- peritoneal dialysis
- prognostic factors
- escherichia coli
- staphylococcus aureus
- stem cells
- current status
- patient reported outcomes
- drug induced
- electronic health record
- big data
- radiation therapy
- transcription factor
- dna methylation
- deep learning
- amino acid
- data analysis
- stress induced
- candida albicans