Estimating epidemic parameters: Application to H1N1 pandemic data

Mathematical Biosciences

Volumn 270, Issue , 2015, Pages 198-203

  Schwartz, Elissa J ^a   Choi, Boseung ^b   Rempala, Grzegorz A ^c  

^a WASHINGTON STATE UNIVERSITY   (United States)

^b Daegu University   (South Korea)

^c OHIO STATE UNIVERSITY   (United States)

Author keywords

62M 05; 92 08; 92D30; H1N1 influenza; Monte Carlo approximation; Parameter estimation; Stochastic SIR model

Indexed keywords

EPIDEMIOLOGY; STOCHASTIC MODELS; STOCHASTIC SYSTEMS;

62M-05; 92-08; 92D30; H1N1 INFLUENZA; MONTE-CARLO APPROXIMATIONS; SIR MODEL;

PARAMETER ESTIMATION;

EPIDEMIC; ESTIMATION METHOD; INFLUENZA; MONTE CARLO ANALYSIS; NUMERICAL MODEL; STOCHASTICITY;

2009 H1N1 INFLUENZA; ARTICLE; EPIDEMIC; HUMAN; MAXIMUM LIKELIHOOD METHOD; MONTE CARLO METHOD; REGRESSION ANALYSIS; SIR MODEL; STOCHASTIC MODEL; UNITED STATES; UNIVERSITY STUDENT; INFLUENZA A VIRUS (H1N1); INFLUENZA, HUMAN; PANDEMIC; PATHOGENICITY; STATISTICS AND NUMERICAL DATA; THEORETICAL MODEL;

HUMANS; INFLUENZA A VIRUS, H1N1 SUBTYPE; INFLUENZA, HUMAN; MODELS, THEORETICAL; PANDEMICS;

EID: 84949532708     PISSN: 00255564     EISSN: 18793134     Source Type: Journal    
DOI: 10.1016/j.mbs.2015.03.007     Document Type: Article

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