title: Estimating the burden of mucormycosis infections in France (2005-2007) through a capture-recapture method on laboratory and administrative data.
abstract: BACKGROUND
  Mucormycoses are rare but severe fungal infections whose incidence is increasing, particularly in immunosuppressed and diabetic patients. Following a retrospective study on the characteristics and outcomes of cases who were identified through two sources of information, we carried out a capture-recapture method to estimate the actual burden of the disease in France, 2005-2007.
  
  
  METHODS
  An administrative dataset from the national hospital discharge system and a laboratory dataset from the National Reference Centre for Mycoses and Antifungals were combined to identify patients from 2005 to 2007. We applied capture-recapture equations to estimate the number of cases missed by both sources and to assess the advantages of each dataset, especially in terms of sensitivity.
  
  
  RESULTS
  There were 94 mucormycosis cases included in the study: 30 and 31 in each respective source and 33 common to both. Capture-recapture showed that 28 cases were missed (expected total: 122 cases, CI95: 102-142). Each dataset had a sensitivity value below 53%. The merged set yielded a 77% sensitivity (66%-92%).
  
  
  CONCLUSIONS
  This study highlights the importance of combining available sources when analysing rare infectious diseases. The proportion of 23% missed cases might seem acceptable given the scarcity of the disease, for which further knowledge is needed. However this proportion could decrease in the future, through the sensitization of clinicians, pathologists and mycologists together with the improving quality of discharge datasets.
authors.affiliation: Département des maladies infectieuses, institut de veille sanitaire, Saint-Maurice, France. d.bitar@invs.sante.fr
authors.forename: D
authors.initials: D
authors.lastname: Bitar
authors.forename: G
authors.initials: G
authors.lastname: Morizot
authors.forename: D
authors.initials: D
authors.lastname: Van Cauteren
authors.forename: E
authors.initials: E
authors.lastname: Dannaoui
authors.forename: F
authors.initials: F
authors.lastname: Lanternier
authors.forename: O
authors.initials: O
authors.lastname: Lortholary
authors.forename: F
authors.initials: F
authors.lastname: Dromer
mesh_terms: D017281:Cost of Illness; D003627:Data Interpretation, Statistical; D016208:Databases, Factual / Q000706:statistics & numerical data*; D015340:Epidemiologic Research Design; D005260:Female; D005602:France / Q000453:epidemiology; D006298:Health Services Administration / Q000706:statistics & numerical data*; D006801:Humans; D007755:Laboratories, Hospital / Q000706:statistics & numerical data*; D008297:Male; D050316:Medical Order Entry Systems / Q000706:statistics & numerical data; D009091:Mucormycosis / Q000175:diagnosis* / Q000453:epidemiology*; D011237:Predictive Value of Tests; D011379:Prognosis; D012189:Retrospective Studies; D013223:Statistics as Topic / Q000379:methods*