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
- end stage renal disease
- randomized controlled trial
- systematic review
- copy number
- ejection fraction
- newly diagnosed
- chronic kidney disease
- respiratory syndrome coronavirus
- papillary thyroid
- stem cells
- escherichia coli
- peritoneal dialysis
- staphylococcus aureus
- squamous cell carcinoma
- dna methylation
- high glucose
- risk assessment
- bone marrow
- machine learning
- oxidative stress
- small molecule
- electronic health record
- squamous cell
- climate change
- endothelial cells
- cystic fibrosis
- young adults
- genome wide
- amino acid
- biofilm formation
- candida albicans