The main objective of RESILIENCE is to investigate Ethical eXplainable neuro-symbolic AI agents, knowledge representation and data acquisition techniques to model the epidemiological evolution and propagation of pandemics, including but not limited to SARS-CoV-2, and generalize them to predict future pandemics and support decisionmaking of health authorities and professionals, aiming at reaching Pandemic Resilience for future crises.

RESILIENCE’s main objective is decomposed in general and specific objectives:

O1 To design and populate an ontology to model public health and sociological data from heterogeneous sources that allows to infer the relevant factors underlying pandemic propagation, including COVID-19

O2 To design models based on eXplainable Artificial Intelligent agents that explain the propagation and epidemiological evolution of past pandemics, including SARS-COV-2

O3 To generalize the research prediction models for unknown future pandemics, creating a common framework that allows to predict propagation of potential future outbreaks

O4 To validate the RESILIENCE AIbased pandemic spread models in a set of controlled lab scenarios (TRL4) using simulated and past pandemic data addressing different granularity areas and demographic segments