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Emilio Zagheni
Researcher at Max Planck Society
Publications - 123
Citations - 2640
Emilio Zagheni is an academic researcher from Max Planck Society. The author has contributed to research in topics: Population & Social media. The author has an hindex of 25, co-authored 103 publications receiving 1856 citations. Previous affiliations of Emilio Zagheni include University of California, Berkeley & City University of New York.
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Proceedings ArticleDOI
Inferring international and internal migration patterns from Twitter data
TL;DR: Geolocated Twitter data can be used to predict turning points in migration trends, which are particularly relevant for migration forecasting, and can substantially improve the understanding of the relationships between internal and international migration.
Journal ArticleDOI
What types of contacts are important for the spread of infections?: using contact survey data to explore European mixing patterns.
TL;DR: It is found that intimate types of contacts explain the pattern of acquisition of serological markers by age better than other types of social contacts.
Journal ArticleDOI
Leveraging Facebook's Advertising Platform to Monitor Stocks of Migrants
TL;DR: In this article, the authors present an approach to estimate stocks of migrants using a previously untapped data source: Facebook's advertising platform, which allows advertisers and researchers to query information about socio-demographic characteristics of Facebook users, aggregated at various levels of geographic granularity.
Journal ArticleDOI
Using Time-Use Data to Parameterize Models for the Spread of Close-Contact Infectious Diseases
Emilio Zagheni,Francesco C. Billari,Piero Manfredi,Alessia Melegaro,Joël Mossong,W. John Edmunds +5 more
TL;DR: The possibilities offered by time-use surveys to measure contact patterns and to explain observed seroprevalence profiles are discussed and models based on the estimated age-specific transmission parameters fit the observed patterns of infection of endemically circulating varicella in a satisfactory way.
Journal ArticleDOI
Little Italy: An Agent-Based Approach to the Estimation of Contact Patterns- Fitting Predicted Matrices to Serological Data
Fabrizio Iozzi,Francesco Trusiano,Matteo Chinazzi,Francesco C. Billari,Emilio Zagheni,Stefano Merler,Marco Ajelli,Emanuele Del Fava,Piero Manfredi +8 more
TL;DR: The results suggest that simple, carefully designed, synthetic matrices can provide a fruitful complementary approach to questionnaire-based matrices and supports the idea that, depending on the transmissibility level of the infection, either the number of different contacts, or repeated exposure, may be the key factor for transmission.