A5066994350- Complex Network Analysis Techniques
- Animal Disease Management and Epidemiology
- Mental Health Research Topics
- Viral Infections and Vectors
- Vector-borne infectious diseases
- Mathematical and Theoretical Epidemiology and Ecology Models
- Opinion Dynamics and Social Influence
- Vector-Borne Animal Diseases
- Evolutionary Game Theory and Cooperation
- Evolution and Genetic Dynamics
- Sports Analytics and Performance
- Data Visualization and Analytics
- Insect and Pesticide Research
- Zoonotic diseases and public health
- COVID-19 epidemiological studies
- Hepatitis Viruses Studies and Epidemiology
- Prion Diseases and Protein Misfolding
- Bioinformatics and Genomic Networks
- Osteomyelitis and Bone Disorders Research
- Health, Environment, Cognitive Aging
- Sports, Gender, and Society
- Chemical Safety and Risk Management
- Infective Endocarditis Diagnosis and Management
- Evolution and Paleontology Studies
- Animal Ecology and Behavior Studies
University of Turin
2011-2019
National Research Council
2007
Institute of Electronics, Computer and Telecommunication Engineering
2007
The time variation of contacts in a networked system may fundamentally alter the properties spreading processes and affect condition for large-scale propagation, as encoded epidemic threshold. Despite great interest problem physics, applied mathematics, computer science, epidemiology communities, full theoretical understanding is still missing currently limited to cases where time-scale separation holds between network dynamics or specific temporal models. We consider Markov chain...
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The spread of tick-borne pathogens represents an important threat to human and animal health in many parts Eurasia. Here, we analysed a 9-year time series Ixodes ricinus ticks feeding on Apodemus flavicollis mice (main reservoir-competent host for encephalitis, TBE) sampled Trentino (Northern Italy). tail the distribution number per was fitted by three theoretical distributions: Negative Binomial (NB), Poisson-LogNormal (PoiLN), Power-Law (PL). fit with distributions indicated that tick...
The structure of a network dramatically affects the spreading phenomena unfolding upon it. contact distribution nodes has long been recognized as key ingredient in influencing outbreak events. However, limited knowledge is currently available on role weight edges persistence pathogen. At same time, recent works showed strong influence temporal dynamics disease spreading. In this work we provide an analytical understanding, corroborated by numerical simulations, about conditions for infected...
Abstract In order to investigate the behaviour of athletes in choosing sports, we analyse data from part We‐Sport ® database, a vertical social network that links through sports. particular, explore connections between people sharing common sports and role age gender by applying “network science” approaches methods. The results show disassortative tendency negative correlation number chosen positive connected athletes. Some interesting patterns connection classes are depicted. addition,...