Semi-empirical power-law scaling of new infection rate to model epidemic dynamics with inhomogeneous mixing

Mathematical Biosciences

Volumn 203, Issue 2, 2006, Pages 301-318

  Stroud, Phillip D ^a   Sydoriak, Stephen J ^a   Riese, Jane M ^a   Smith, James P ^a   Mniszewski, Susan M ^a   Romero, Phillip R ^a  

^a LOS ALAMOS NATIONAL LABORATORY   (United States)

Author keywords

Epidemic dynamics; Epidemic model; Homogeneous mixing; Power law

Indexed keywords

EPIDEMIC DYNAMICS; EPIDEMIC MODELS; HOMOGENEOUS MIXING; POWER LAW;

MATHEMATICAL MODELS; POPULATION STATISTICS; SOCIAL ASPECTS;

EPIDEMIOLOGY;

EPIDEMIC; HISTOGRAM; IMPLEMENTATION PROCESS; INFECTIOUS DISEASE; INHOMOGENEITY; MODEL; POWER LAW;

ARTICLE; DEMOGRAPHY; DISEASE SIMULATION; DISEASE TRANSMISSION; EPIDEMIC; HISTOGRAM; INFECTION; INFECTION RATE; INFECTION SENSITIVITY; INFLUENZA; POPULATION MODEL; POPULATION STRUCTURE; PREDICTION; SCALE UP; SOCIAL BEHAVIOR; UNITED STATES;

CHICAGO; COMPUTER SIMULATION; DISEASE OUTBREAKS; EPIDEMIOLOGIC METHODS; HUMANS; INCIDENCE; INFLUENZA, HUMAN; LOS ANGELES; MODELS, STATISTICAL; ORTHOMYXOVIRIDAE; POPULATION DYNAMICS; URBAN POPULATION;

CALIFORNIA; CHICAGO; ILLINOIS; LOS ANGELES; NORTH AMERICA; OREGON; PORTLAND [OREGON]; UNITED STATES;

EID: 33749049349     PISSN: 00255564     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.mbs.2006.01.007     Document Type: Article

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