title: A model for the early identification of sources of airborne pathogens in an outdoor environment.
abstract: BACKGROUND
  Source identification in areas with outbreaks of airborne pathogens is often time-consuming and expensive. We developed a model to identify the most likely location of sources of airborne pathogens.
  
  
  METHODS
  As a case study, we retrospectively analyzed three Q fever outbreaks in the Netherlands in 2009, each with suspected exposure from a single large dairy goat farm. Model input consisted only of case residential addresses, day of first clinical symptoms, and human population density data. We defined a spatial grid and fitted an exponentially declining function to the incidence-distance data of each grid point. For any grid point with a fit significant at the 95% confidence level, we calculated a measure of risk. For validation, we used results from abortion notifications, voluntary (2008) and mandatory (2009) bulk tank milk sampling at large (i.e. >50 goats and/or sheep) dairy farms, and non-systematic vaginal swab sampling at large and small dairy and non-dairy goat/sheep farms. In addition, we performed a two-source simulation study.
  
  
  RESULTS
  Hotspots--areas most likely to contain the actual source--were identified at early outbreak stages, based on the earliest 2-10% of the case notifications. Distances between the hotspots and suspected goat farms varied from 300-1500 m. In regional likelihood rankings including all large dairy farms, the suspected goat farms consistently ranked first. The two-source simulation study showed that detection of sources is most clear if the distance between the sources is either relatively small or relatively large.
  
  
  CONCLUSIONS
  Our model identifies the most likely location of sources in an airborne pathogen outbreak area, even at early stages. It can help to reduce the number of potential sources to be investigated by microbial testing and to allow rapid implementation of interventions to limit the number of human infections and to reduce the risk of source-to-source transmission.
authors: Institute for Risk Assessment Sciences (IRAS), Utrecht University, Utrecht, The Netherlands ; Centre for Infectious Disease Control (CIb), National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands.
authors: Jeroen P G
authors: JP
authors: van Leuken
authors: Arie H
authors: AH
authors: Havelaar
authors: Wim
authors: W
authors: van der Hoek
authors: Georgia A F
authors: GA
authors: Ladbury
authors: Volker H
authors: VH
authors: Hackert
authors: Arno N
authors: AN
authors: Swart
mesh_terms: D000822:Animal Husbandry; D000818:Animals; D003198:Computer Simulation; D016997:Coxiella burnetii / Q000302:isolation & purification* / Q000472:pathogenicity; D004196:Disease Outbreaks; D005260:Female; D015511:Goat Diseases / Q000175:diagnosis / Q000453:epidemiology* / Q000635:transmission; D006041:Goats; D006801:Humans; D015233:Models, Statistical; D009426:Netherlands / Q000453:epidemiology; D011156:Population Density; D011247:Pregnancy; D011778:Q Fever / Q000175:diagnosis / Q000453:epidemiology / Q000635:transmission / Q000662:veterinary*; D012756:Sheep; D012757:Sheep Diseases / Q000175:diagnosis / Q000453:epidemiology* / Q000635:transmission