Digital Twins are like virtual doppelgangers of physical objects, helping in predicting diseases, evaluating climate policies, and conserving resources. EPFL's DIGIPREDICT project used digital twins to anticipate how COVID-19 might progress in individuals, aiding in better healthcare decisions.

Digital Twins involve creating virtual copies of real objects for real-time monitoring and analysis. These replicas are utilized in various fields like disease prediction, climate policy assessment, and resource conservation. EPFL's DIGIPREDICT consortium used digital twins to forecast COVID-19 progression in patients.