Inference for nonlinear epidemiological models using genealogies and time series

PLoS Computational Biology

Volumn 7, Issue 8, 2011, Pages

  Rasmussen, David A ^a   Ratmann, Oliver ^a,b   Koelle, Katia ^a,c  

^a DUKE UNIVERSITY   (United States)

^b IMPERIAL COLLEGE LONDON   (United Kingdom)

^c NATIONAL INSTITUTES OF HEALTH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DIGITAL STORAGE; DYNAMICS; HISTORY; POPULATION STATISTICS; STOCHASTIC MODELS; STOCHASTIC SYSTEMS; TIME SERIES; VIRUSES;

'CURRENT; COMPLEX DYNAMICS; DEMOGRAPHIC MODELLING; ECOLOGICAL AND EVOLUTIONARY DYNAMICS; EPIDEMIOLOGICAL MODELING; RNA VIRUS; SEQUENCE DATA; SIMPLE++; TIME-SERIES DATA; TIMES SERIES;

POPULATION DYNAMICS;

ACCURACY; ALGORITHM; ARTICLE; BAYES THEOREM; COMPUTER SIMULATION; CONTROLLED STUDY; DISEASE TRANSMISSION; EPIDEMIC; EPIDEMIOLOGICAL DATA; GENEALOGY; INFECTION RATE; MATHEMATICAL COMPUTING; NONLINEAR SYSTEM; POPULATION DYNAMICS; STOCHASTIC MODEL; TIME SERIES ANALYSIS; BIOLOGICAL MODEL; BIOLOGY; EPIDEMIOLOGY; METHODOLOGY; MONTE CARLO METHOD; PHYLOGENY; PREVALENCE; STATISTICS;

RNA VIRUSES;

ALGORITHMS; BAYES THEOREM; COMPUTATIONAL BIOLOGY; DISEASE TRANSMISSION, INFECTIOUS; EPIDEMICS; EPIDEMIOLOGIC METHODS; MODELS, BIOLOGICAL; MONTE CARLO METHOD; NONLINEAR DYNAMICS; PHYLOGENY; POPULATION DYNAMICS; PREVALENCE; STOCHASTIC PROCESSES;

EID: 80052336720     PISSN: 1553734X     EISSN: 15537358     Source Type: Journal    
DOI: 10.1371/journal.pcbi.1002136     Document Type: Article

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