Mathematical modelling of infectious disease dynamics



G-nous Tech provides consultancy services to research institutions and pharmaceuticals industries for activities regarding mathematical modelling and numerical simulations of dynamics and containment of diseases.


Global mitigation strategies to tackle the threat posed by SARS-CoV-2 have produced a significant decrease of the severity of 2020/21 seasonal influenza, which might result in a reduced population natural immunity for the upcoming influenza seasons.
To predict the spread of influenza virus in Italy and the impact of prevention and control measures, mathematical approaches to model the dynamic of the epidemic are essential to assess and compare the effectiveness of public health measures to control the epidemic . The insights stemming from this analysis can be used to infer valuable information for public health policymakers.


The study mission was to explore a wide range of influenza epidemic scenarios for the winter seasons 2023 in Italy by taking into account the impact of single and multiple control/prevention measures in the spread of the disease for different seasonal severity.
The characteristics of the epidemic scenarios have been assessed through an age-structured deterministic Susceptible-Exposed-Infectious-Recovered epidemiological model, suitably extended in order to properly model age-structured social mixing and the impact of age-stratified vaccination strategies and Non-Pharmaceutical Interventions (NPIs) such as school closures, partial lockdown, as well as the adoption of personal protective equipment.


G-nous Tech has carried out the formal and mathematical analysis of the problem to be investigated, as well as the conceptualization and development of the mathematical model and the exploration analysis of epidemiological scenarios by means of numerical simulations .
G-nous Tech presented the findings of the study in a research paper that has been peer-reviewed and published in the high-impact journal PLOS ONE.


G-nous Tech found that vaccination campaigns with standard coverage would produce a remarkable mitigation of the spread of the disease in moderate influenza seasons, making the adoption of NPIs unnecessary. However, in case of severe seasonal epidemics, a standard vaccination coverage would not be sufficiently effective in fighting the epidemic, thus implying that a combination with the adoption of NPIs is necessary to contain the disease. Alternatively, the results show that the enhancement of vaccination coverage would reduce the need to adopt NPIs, thus limiting the economic and social impacts that NPIs might produce.


Research Institutions, Healthcare Companies, Governments, pharmaceuticals industries



  • BIP Life Sciences
  • University of Milan
  • University of Genoa
  • University of Bari
  • San Martino Policlinico Hospital-IRCCS for Oncology and Neurosciences

Link to research paper published in PLOS ONE:


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