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Anticipating health risks. Connecting data. Turning evidence into action.
PEDIL integrates epidemiology, data science, genomics, artificial intelligence, and quantitative modeling to understand, anticipate, and respond to health risks across human, animal, and environmental systems.
55+
Peer-reviewed publications
6+
Countries represented in our research
20+
Research collaborators
6
Interactive tools and platforms
What We Do
UNDERSTAND
Population health & complex systems
We integrate epidemiologic, clinical, environmental, genomic, spatial, and network data to understand patterns of health, disease, exposure, and risk across populations.
ANTICIPATE
Predictive epidemiology & data science
We use statistical modeling, machine learning, and AI to identify emerging risks, forecast health outcomes, and understand how conditions may change over time and space.
TRANSLATE
Decision support & capacity
We turn data and analytical methods into practical tools, evidence, and training that help researchers, practitioners, and decision-makers act more effectively.
Featured research
Featured research
Anticipating Health Risks
Predictive epidemiology, AI & early warning
We combine surveillance, environmental, behavioral, and population data with statistical modeling and AI to identify emerging risks and support earlier, more targeted intervention.
Connecting Genomes to Transmission & Immunity Genomic epidemiology, evolution & predictive immunology
We integrate genomic, evolutionary, spatial, and machine-learning approaches to understand how biological populations change, spread, and interact with immunity; and translate those insights into better surveillance and intervention strategies
Understanding People & Systems
Population health, behavior & intervention science
We study how behavior, environment, management, social conditions, and system structure shape health outcomes; and uses those insights to design and evaluate interventions that work in real-world settings.
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