Prevention Lab: a predictive model for estimating the impact of prevention interventions in a simulated Italian cohort
We propose a Markovian model to estimate how interventions on smoking and sedentary lifestyle can affect the reduction of the disease burden, and validate the model on historical data. The model is flexible and allows to extend the analysis to consider more risk factors in future research. However, we are aware that, given the ever-increasing availability of data, it is necessary in the future to increase the complexity of the model, to be closer to reality and to provide decision-making support to the policy-makers.
Authors
- Giulia Carreras (ORCID: https://orcid.org/0000-0002-1427-637X)
- Cristiano Piccinelli
- Costanza Catalano (ORCID: https://orcid.org/0000-0002-0333-3615)
- Giacomo Como (ORCID: https://orcid.org/0000-0002-2176-9586)
- Eva Pagano (ORCID: https://orcid.org/0000-0001-7552-2901)
- Carlo Senore (ORCID: https://orcid.org/0000-0003-1023-7477)
- Nereo Segnan
- Leonardo Cianfanelli (ORCID: https://orcid.org/0000-0001-5345-5381)
- Stefania Vasselli
- Mariano Tomatis (ORCID: https://orcid.org/0000-0003-0129-8104)
- Fabio Fagnani (ORCID: https://orcid.org/0000-0001-5757-8194)
Institutions
- Bank of Italy (IT)
- Politecnico di Torino (IT)
- Ministero della Salute (IT)
- Azienda Ospedaliera Citta' della Salute e della Scienza di Torino (IT)
Publication Details
- Journal
- BMC Public Health
- Published
- 2024-10-12
- DOI
- https://doi.org/10.1186/s12889-024-20212-6
- Primary Topic
- Health Policy Implementation Science
- Type
- article
- Field-Weighted Citation Impact
- 0.00