Comparing vector-host and SIR models for dengue transmission

Mathematical Biosciences

Volumn 246, Issue 2, 2013, Pages 252-259

  Pandey, Abhishek ^a   Mubayi, Anuj ^b   Medlock, Jan ^c  

^a CLEMSON UNIVERSITY   (United States)

^b NORTHEASTERN ILLINOIS UNIVERSITY   (United States)

^c OREGON STATE UNIVERSITY   (United States)

Author keywords

Dengue; Markov chain Monte Carlo (MCMC); Mathematical model; Parameter estimation

Indexed keywords

BAYESIAN MARKOV CHAIN MONTE CARLO; DENGUE; DENGUE HEMORRHAGIC FEVER; MARKOV CHAIN MONTE CARLO; MODEL ASSUMPTIONS; MODEL SELECTION; MOSQUITO POPULATIONS; PARAMETER ESTIMATE;

MATHEMATICAL MODELS; PARAMETER ESTIMATION;

DYNAMIC MODELS;

BAYESIAN ANALYSIS; DENGUE FEVER; DISEASE TRANSMISSION; DISEASE VECTOR; HOST; MONTE CARLO ANALYSIS; MOSQUITO; NUMERICAL MODEL; PARAMETERIZATION;

ARTICLE; BASIC REPRODUCTION NUMBER; BAYES THEOREM; CONTROLLED STUDY; CORRELATION COEFFICIENT; DENGUE; HUMAN; INCIDENCE; INTERMETHOD COMPARISON; MARKOV CHAIN MONTE CARLO; MATHEMATICAL MODEL; MATHEMATICAL PARAMETERS; MAXIMUM LIKELIHOOD METHOD; PARTIAL RANK CORRELATION COEFFICIENT; PROBABILITY; SENSITIVITY ANALYSIS; SIR MODEL; THAILAND; UNCERTAINTY; VECTOR HOST MODEL; VIRUS TRANSMISSION;

THAILAND;

AEDES; ANIMALS; BAYES THEOREM; DENGUE VIRUS; HUMANS; INSECT VECTORS; MARKOV CHAINS; MODELS, THEORETICAL; MONTE CARLO METHOD; SEVERE DENGUE; THAILAND;

EID: 84888020012     PISSN: 00255564     EISSN: 18793134     Source Type: Journal    
DOI: 10.1016/j.mbs.2013.10.007     Document Type: Article

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