title: Similar seasonal peak in clustered and unique extra-pulmonary tuberculosis notifications: winter crowding hypothesis ruled out?
abstract: BACKGROUND
  The incidence of extra-pulmonary tuberculosis (EPTB) in the Netherlands shows a seasonal trend, with a peak in spring and a trough in autumn. Possible causes of this peak are winter crowding and a seasonal decrease in immune competence in spring. A third explanation may be a reporting bias.
  
  
  OBJECTIVE
  To investigate the role of winter crowding by a time-series analysis of notification data. DNA fingerprinting clustering status can differentiate between recent and remote infections. Seasonality in clustered cases would reflect enhanced transmission in winter and/or seasonally lowered immunity, while seasonality in unique cases would only reflect seasonally lowered immunity.
  
  
  METHODS
  We fitted (seasonal) auto-regressive moving average models to culture-positive TB notifications in the Netherlands (1993-2008) to assess seasonality. We then used seasonal trend Loess decompositions to derive the seasonal pattern, and compared the heights of the seasonal peaks.
  
  
  RESULTS
  Clustered and unique EPTB notifications showed a seasonal trend that was absent in clustered and unique PTB notifications. The seasonal peak in clustered EPTB cases was not significantly higher than in unique EPTB cases.
  
  
  CONCLUSIONS
  The similar timing and height of the seasonal peak of clustered and unique EPTB cases suggests that winter crowding is unlikely to cause the seasonal trend in notifications.
authors.affiliation: National Institute for Public Health and the Environment, Epidemiology and Surveillance, Bilthoven, The Netherlands; ResultsinHealth, Leiderdorp, The Netherlands.
authors.forename: R
authors.initials: R
authors.lastname: Top
authors.forename: H
authors.initials: H
authors.lastname: Boshuizen
authors.forename: A
authors.initials: A
authors.lastname: Dekkers
authors.forename: H
authors.initials: H
authors.lastname: Korthals Altes
mesh_terms: D016000:Cluster Analysis; D003441:Crowding; D016172:DNA Fingerprinting; D004269:DNA, Bacterial / Q000032:analysis; D018563:Disease Notification / Q000706:statistics & numerical data*; D006798:Housing; D006801:Humans; D015994:Incidence; D009169:Mycobacterium tuberculosis / Q000235:genetics / Q000276:immunology / Q000302:isolation & purification; D009426:Netherlands / Q000453:epidemiology; D012042:Registries; D012044:Regression Analysis; D012307:Risk Factors; D012621:Seasons; D013997:Time Factors; D014376:Tuberculosis / Q000175:diagnosis / Q000453:epidemiology* / Q000276:immunology / Q000382:microbiology / Q000635:transmission
chemical_list: D004269:DNA, Bacterial