title: Dynamically modeling SARS and other newly emerging respiratory illnesses: past, present, and future.
abstract: The emergence and rapid global spread of the severe acute respiratory syndrome (SARS) coronavirus in 2002-2003 prompted efforts by modelers to characterize SARS epidemiology and inform control policies. We overview and discuss models for emerging infectious diseases (EIDs), provide a critical survey of SARS modeling literature, and discuss promising future directions for research. We reconcile discrepancies between published estimates of the basic reproductive number R0 for SARS (a crucial epidemiologic parameter), discuss insights regarding SARS control measures that have emerged uniquely from a modeling approach, and argue that high priorities for future modeling of SARS and similar respiratory EIDs should include informing quarantine policy and better understanding the impact of population heterogeneity on transmission patterns.
authors.affiliation: Department of Mathematics and Statistics, University of Guelph, Guelph, Ontario, Canada. cbauch@uoguelph.ca
authors.forename: Chris T
authors.initials: CT
authors.lastname: Bauch
authors.forename: James O
authors.initials: JO
authors.lastname: Lloyd-Smith
authors.forename: Megan P
authors.initials: MP
authors.lastname: Coffee
authors.forename: Alison P
authors.initials: AP
authors.lastname: Galvani
mesh_terms: D021821:Communicable Diseases, Emerging / Q000453:epidemiology* / Q000635:transmission; D004196:Disease Outbreaks; D005544:Forecasting; D006801:Humans; D008954:Models, Biological; D045169:Severe Acute Respiratory Syndrome / Q000453:epidemiology* / Q000635:transmission