Real‐time epidemiology
Identifieur interne : 000A32 ( Istex/Curation ); précédent : 000A31; suivant : 000A33Real‐time epidemiology
Auteurs : Christl Donnelly ; Azra GhaniSource :
- Significance [ 1740-9705 ] ; 2004-12.
English descriptors
- Teeft :
- Accurate characterisation, Average number, Azra ghani, Case incidence, Case study, Christl donnelly, Complex transmission models, Control measures, Cyan, Data collection, Disease control, Disease persistence, Epidemiological, Epidemiological data, Epidemiological modelling, Epidemiology, Hong kong, Hong kong authorities, Hong kong epidemic, Hospitalisation, Infection incidence, Infectious disease, Infectious disease epidemiology, Infectious diseases, Information technology, Model structure, Modelling, Other countries, Outbreak, Pantone, Parameter, Parameter estimates, Parameter estimation, Policy makers, Process cyan process, Sars, Sars case, Sars cases, Sars epidemic, Sars epidemics, Secondary cases, Sensitivity analysis, Stochastic, Stochastic models, Stockholm challenge award, Such models, Transmission dynamics, Transmission models.
Abstract
Fitting transmission models to outbreak data allows key epidemiological parameters to be estimated and the impact of control measures to be evaluated. Christl Donnelly and Azra Ghani describe the use of such models in the 2003 SARS epidemic in Hong Kong.
Url:
DOI: 10.1111/j.1740-9713.2004.00066.x
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Christl Donnelly<affiliation><mods:affiliation>Imperial College London, Faculty of Medicine</mods:affiliation><wicri:noCountry code="subField">Medicine</wicri:noCountry></affiliation><affiliation><mods:affiliation>Imperial College London, Faculty of Medicine</mods:affiliation><wicri:noCountry code="subField">Medicine</wicri:noCountry></affiliation>Le document en format XML
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