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Statistical Methods for model selection and parameter estimation
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#91703
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Controlling Infectious Diseases »
Controlling Infectious Diseases
Controlling Infectious DiseasesâMapping the issues around endemic diseasesâsuch as malaria, measles, influenza, HIV, Dengue and West Nile Virusâwith the aims of identifying improved control strategies and of providing insights into to the work of mathematical biologists, epidemiologists and public health officials in this field.âF1CEB7
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Research Questions »
Research Questions
Research QuestionsâWhat are the research priorities for the field?âFFB597
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Open mathematical/computational problems? »
Open mathematical/computational problems?
Open mathematical/computational problems?ââFFB597
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Statistical Methods for model selection and parameter estimation
Statistical Methods for model selection and parameter estimationââFFB597
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Nonparametric approaches »
Nonparametric approaches
Nonparametric approachesâUse information or summary statistics on disease incidence or dynamics to estimate metrics such as R0, without using a fully specified disease modelâFFB597
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Parametric approaches »
Parametric approaches
Parametric approachesâGiven an explicit (full) model of disease, estimate all parameters (or some parameters, e.g. beta/R0 only assuming others known from independent sources) by fitting to disease dynamicsâFFB597
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References »
References
ReferencesââFFB597
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Unobservable events »
Unobservable events
Unobservable eventsâData are based on observable events. Some key events in disease transmission are unobservable. Inference for unobservable events based on observed data (usually subsequent events of the event of interest) often subject to bias, and/or, non-identifiability issues.âFFB597
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Entrée par:
Daihai He
NodeID:
#91703
Node type:
Issue
Date d'entrée (GMT):
2/9/2011 8:29:00 PM
Date de la derniĂšre modification (Heure GMT):
3/12/2011 8:13:00 PM
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