title: Modeling the risk of an emerging pathogen entering the Canadian blood supply.
abstract: BACKGROUND
  As part of its risk management process, Canadian Blood Services (CBS) constructed mathematical models of how newly emerging pathogens might affect blood transfusion recipients.
  
  
  METHODS
  CBS convened an expert panel including medical, health economics, analytical, risk management, and insurance professionals to examine multiple data sources. The model for emerging pathogen risk included separate modules to calculate the frequency and severity of infections from transfusion-transmitted agents that could cause either acute transient or chronic persistent infection. Important model input variables were annual number of components transfused, the presumed incidence and prevalence of a new agent, the time interval of recipient risk, recipient age and sex, projected recipient survival, rate of secondary infection, pathogen-induced morbidity, and the associated medical costs of such morbidity.
  
  
  RESULTS
  In the 5-year time frame considered in the model, it was estimated that approximately 3500 recipient infections (two-SD range of 0 to 11,370 infections) could occur from an emerging pathogen that establishes a chronic infection in donors, with 60% of these due to red blood cell transfusion. The medical costs associated with recipient outcomes due to a catastrophic emerging pathogen could be lowered by 20% if an effective pathogen reduction method for either platelets or plasma were in place.
  
  
  CONCLUSIONS
  This modeling exercise offers a framework for other blood services to construct similar models. It also provides a useful way to model the implementation of new blood safety interventions (e.g., pathogen reduction) on emerging pathogen risk.
authors.affiliation: Department of Pathology & Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada.
authors.forename: Steven
authors.initials: S
authors.lastname: Kleinman
authors.forename: Claire
authors.initials: C
authors.lastname: Cameron
authors.forename: Brian
authors.initials: B
authors.lastname: Custer
authors.forename: Michael
authors.initials: M
authors.lastname: Busch
authors.forename: Louis
authors.initials: L
authors.lastname: Katz
authors.forename: Boris
authors.initials: B
authors.lastname: Kralj
authors.forename: Ian
authors.initials: I
authors.lastname: Matheson
authors.forename: Ken
authors.initials: K
authors.lastname: Murphy
authors.forename: Jutta
authors.initials: J
authors.lastname: Preiksaitis
authors.forename: Dana
authors.initials: D
authors.lastname: Devine
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001771:Blood Banks / Q000592:standards / Q000706:statistics & numerical data / Q000600:supply & distribution; D001782:Blood Donors / Q000706:statistics & numerical data* / Q000600:supply & distribution; D058731:Blood Safety / Q000592:standards / Q000706:statistics & numerical data*; D001803:Blood Transfusion / Q000592:standards / Q000706:statistics & numerical data; D017848:Blood-Borne Pathogens / Q000302:isolation & purification; D002170:Canada; D002648:Child; D002675:Child, Preschool; D005260:Female; D006801:Humans; D015994:Incidence; D007223:Infant; D007231:Infant, Newborn; D007239:Infections / Q000097:blood / Q000453:epidemiology / Q000209:etiology* / Q000635:transmission; D008297:Male; D008875:Middle Aged; D008962:Models, Theoretical; D018570:Risk Assessment / Q000379:methods; D012307:Risk Factors; D065227:Transfusion Reaction; D055815:Young Adult