Data modelling of infectious disease dynamics
Highlight
The project conducted a rigorous mathematical analysis of diverse influenza epidemic scenarios for Italy's 2023 winter season, developing a comprehensive model and exploring epidemiological outcomes through numerical simulations.
Scenario
The global response to SARS-CoV-2 has inadvertently led to a marked reduction in the severity of the 2020/21 seasonal influenza. To forecast influenza transmission in Italy and assess the effectiveness of various interventions, sophisticated mathematical models could be employed. These models incorporate key factors such as social mixing patterns, age-stratified vaccination strategies, and Non-Pharmaceutical Interventions (NPIs).
Solution
The project developed a thorough approach to analyse influenza epidemic scenarios for the 2023 winter season in Italy. The core of this solution was an advanced age-structured deterministic Susceptible-Exposed-Infectious-Recovered (SEIR) epidemiological model. This sophisticated model was specifically designed to:
- explore a wide range of epidemic scenarios
- evaluate the impact of both individual and combined control and prevention measures
- account for varying levels of seasonal severity
Key features of the model include:
- age-structured social mixing patterns, for more accurate representation of disease transmission across different age groups
- age-stratified vaccination strategies, to assess the effectiveness of vaccination programs targeted at specific age demographics
- Non-pharmaceutical Interventions (NPIs), such as school closures, partial lockdowns, and the use of personal protective equipment.
Outcomes
The model provides a robust tool for forecasting influenza transmission and evaluating the potential effectiveness of various intervention strategies. This approach enables policymakers and health officials to make more informed decisions in preparing for and responding to influenza outbreaks.
The findings of the study were published in the high-impact journal PLOS ONE.
G-nous role
G-nous Tech conducted the whole mathematical analysis of the problem, conceptualised and developed a sophisticated epidemiological model, and explored various scenarios through rigorous numerical simulations.