Measurability of the epidemic reproduction number in data-driven contact networks

Proceedings of the National Academy of Sciences of the United States of America

Volumn 115, Issue 50, 2018, Pages 12680-12685

  Liu, Quan Hui ^a,b   Ajelli, Marco ^b,c   Aleta, Alberto ^d   Merler, Stefano ^c   Moreno, Yamir ^d,e   Vespignani, Alessandro ^b,e  

^a UNIVERSITY OF ELECTRONIC SCIENCE AND TECHNOLOGY OF CHINA   (China)

^b NORTHEASTERN UNIVERSITY   (United States)

^c FONDAZIONE BRUNO KESSLER   (Italy)

^d UNIVERSITY OF ZARAGOZA   (Spain)

^e ISI FOUNDATION   (Italy)

Author keywords

Computational modeling; Generation time; Infectious diseases; Multiplex networks; Reproduction number

Indexed keywords

2009 H1N1 INFLUENZA; ARTICLE; BAYES THEOREM; BEHAVIOR CHANGE; COMMUNITY; DISEASE TRANSMISSION; DUTCHMAN; EPIDEMIC; EPIDEMIOLOGICAL DATA; EVOLUTION; GROWTH RATE; HOUSEHOLD; HUMAN; INCIDENCE; ITALIAN (CITIZEN); ITALY; MATHEMATICAL MODEL; PRIORITY JOURNAL; REPRODUCTION NUMBER; SCHOOL; SEROPREVALENCE; SIMULATION; SOCIAL NETWORK; WORKPLACE; BASIC REPRODUCTION NUMBER; COMPUTER SIMULATION; CONTACT EXAMINATION; EPIDEMIOLOGY; INFLUENZA; NETHERLANDS; STATISTICAL MODEL; STATISTICS AND NUMERICAL DATA; TIME FACTOR; TRANSMISSION;

BASIC REPRODUCTION NUMBER; COMPUTER SIMULATION; CONTACT TRACING; EPIDEMICS; EPIDEMIOLOGIC FACTORS; HUMANS; INFLUENZA, HUMAN; ITALY; MODELS, STATISTICAL; NETHERLANDS; TIME FACTORS;

EID: 85058383380     PISSN: 00278424     EISSN: 10916490     Source Type: Journal    
DOI: 10.1073/pnas.1811115115     Document Type: Article

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