The CEPH lab focuses on five main research lines in infectious disease epidemiology and public health. Select a card below to read more about what we do.

Main Research Lines

Human Social Interactions

Social mixing patterns drive respiratory pathogen transmission leading to heterogeneous exposure risks across different socio-demographic groups. Our objective is to understand why, where, when, how often, and with whom individuals interact to better characterize transmission pathways.

Learn More
Mosquito Ecology and Behavior

The relative abundance and behavior of mosquito vector species are main determinants of human risks for mosquito-borne diseases. Our objective is to investigate the drivers of seasonal and diel trends in mosquito population dynamics and behavior across space and time to identify the underlying mechanisms. Through a mechanistic understanding of these processes, we carry out model-based evaluations to inform mosquito-control and public health authorities.

Learn More
Infectious Disease Dynamics

The transmission of infectious pathogens is a complex process driven by the interplay of biological, behavioral, and socio-economic factors. Our objective is to characterize the fundamental mechanisms of pathogen spread, ranging from the clinical progression of individual infections to the broad patterns observed at the population level. We also aim to understand how cross-scale (within-host, between-host) interactions and socio-economic drivers shape the heterogeneous landscape of infectious disease epidemiology.

Learn More
Situational Awareness

Situational awareness is key for public health policy-making as it allows anticipating surges in disease burden (e.g., hospitalizations) and trigger early warnings. Our objective is to enhance situational awareness through nowcasting and forecasting of epidemic trajectories using a variety of approaches from mechanistic, to semi-mechanistic, and stastical/machine learning approaches. We also aim at improving situational awareness of mosquito control authorities by forecasting mosquito population dynamics.

Learn More
Public Health Planning

Mathematical and computational models have increasingly been used to inform epidemic preparedness and response. Our objective is to support public health decision-making through the scenario analysis and model-based evaluations of pharmaceutical and non-pharmaceutical interventions. We provide actionable insights to our national and international public health partners and conduct fundamental research in this area.

Learn More