Collection 

Epidemiological data

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Epidemiological data collection plays a crucial role in advancing public health research and guiding evidence-based interventions. These datasets serve as foundational resources for studying disease patterns, risk factors, and health outcomes across populations, species, and environments. This Collection presents a series of articles describing epidemiological datasets spanning diverse populations, ecosystems, and disease contexts. Data are presented without hypotheses or significant analyses, and can be derived from population surveys, health registries, electronic health records, field sampling, or other sources. All described datasets are assessed to ensure their open availability (where possible) or secure access controls (where required) via Scientific Data’s editorial and peer review processes.

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Man holding large magnifying glass on cartoon world, showing multiple bacteria in varying colours, cartoon female doctor holding large syringe and another female doctor holding a stethoscope with leaves and plants in the background.

Editors

Francesco Branda, PhD, Campus Bio-Medico University of Rome, Italy

Francesco Branda is an Adjunct Professor at the Faculty of Medicine and Surgery at the Campus Bio-Medico University of Rome. His research interests are diverse, spanning various domains such as data analytics, epidemic intelligence systems, and public health risk studies. To address these questions, he developed novel methods that combine techniques from mathematical modelling, and statistical inference (including AI and Machine Learning). His work focuses to epidemiological and statistical consulting in hospital settings, applying statistical and molecular methods in clinical settings, and analyzing climate-sensitive diseases like Dengue and Chikungunya and outbreaks and pandemics such as SARS-CoV-2, Mpox, and Ebola. Notably, Dr. Francesco Branda has been an Editorial Board Member for Scientific Data since 2024.

Amélie Desvars-Larrive, PhD, University of Veterinary Medicine Vienna, Austria; Complexity Science Hub Vienna, Austria

Amélie Desvars-Larrive is a veterinarian by training and an Associate Professor in Infectious Disease Epidemiology at the University of Veterinary Medicine Vienna, Austria. She is also a Faculty Member at Complexity Science Hub Vienna. Her work bridges field epidemiology and data science, with a primary focus on infectious diseases of animals, zoonotic and emerging diseases, prioritising applied research, FAIR data practices, and One Health approaches. Professor Desvars-Larrive has been an Editorial Board Member for Scientific Data since 2023.

 

Michele Tizzoni, PhD, University of Trento, Italy

Michele Tizzoni is an Assistant Professor at the Department of Sociology and Social Research of the University of Trento. His research interests lie at the intersection of computational social science and infectious disease epidemiology with a focus on using digital trace data to investigate behavioral responses during epidemic outbreaks. Dr Tizzoni has been an Editorial Board Member for Scientific Data since 2017.