Infectious diseases

Description

• Understanding and prediction of epidemiological dynamics of infectious diseases. Study of SARS-CoV-2, influenza, respiratory syncytial virus, tuberculosis and malaria, among others, to improve their control in different contexts. Methods: data analyses, statistical modelling, compartmental models, agent-based models, empiric models, machine learning and artificial intelligence algorithms.

• Natural history of tuberculosis: from latent infection to active disease. Modelling of its dynamics in virtual lungs of macaques and humans. Methods: experimental data analysis, image processing of CT scan images, reaction-diffusion equations, agent-based models. (also: V. PATT REC IN BIOMED IM)