Smooth incidence maps give valuable insight into Q fever outbreaks in The Netherlands

  • Wim van der Hoek | wim.van.der.hoek@rivm.nl Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, Netherlands.
  • Jan van de Kassteele Department of Statistics, Mathematical Modelling and Data Logistics, National Institute for Public Health and the Environment, Bilthoven, Netherlands.
  • Ben Bom Department of Statistics, Mathematical Modelling and Data Logistics, National Institute for Public Health and the Environment, Bilthoven, Netherlands.
  • Arnout de Bruin Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, Netherlands.
  • Frederika Dijkstra Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, Netherlands.
  • Barbara Schimmer Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, Netherlands.
  • Piet Vellema Department of Small Ruminant Health, Animal Health Service, Deventer, Netherlands.
  • Ronald ter Schegget Municipal Health Service “Brabant Zuidoost”, Eindhoven, Netherlands.
  • Peter M. Schneeberger Department of Medical Microbiology and Infection Control, Jeroen Bosch Hospital, ’s Hertogenbosch, Netherlands.

Abstract

From 2007 through 2009, The Netherlands faced large outbreaks of human Q fever. Control measures focused primarily on dairy goat farms because these were implicated as the main source of infection for the surrounding population. However, in other countries, outbreaks have mainly been associated with non-dairy sheep and The Netherlands has many more sheep than goats. Therefore, a public discussion arose about the possible role of non-dairy (meat) sheep in the outbreaks. To inform decision makers about the relative importance of different infection sources, we developed accurate and high-resolution incidence maps for detection of Q fever hot spots. In the high incidence area in the south of the country, full postal codes of notified Q fever patients with onset of illness in 2009, were georeferenced. Q fever cases (n = 1,740) were treated as a spatial point process. A 500 x 500 m grid was imposed over the area of interest. The number of cases and the population number were counted in each cell. The number of cases was modelled as an inhomogeneous Poisson process where the underlying incidence was estimated by 2-dimensional P-spline smoothing. Modelling of numbers of Q fever cases based on residential addresses and population size produced smooth incidence maps that clearly showed Q fever hotspots around infected dairy goat farms. No such increased incidence was noted around infected meat sheep farms. We conclude that smooth incidence maps of human notifications give valuable information about the Q fever epidemic and are a promising method to provide decision support for the control of other infectious diseases with an environmental source.

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Published
2012-11-01
Section
Original Articles
Keywords:
Q fever, smooth incidence maps, dairy goats, The Netherlands.
Statistics
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How to Cite
van der Hoek, W., van de Kassteele, J., Bom, B., de Bruin, A., Dijkstra, F., Schimmer, B., Vellema, P., ter Schegget, R., & Schneeberger, P. M. (2012). Smooth incidence maps give valuable insight into Q fever outbreaks in The Netherlands. Geospatial Health, 7(1), 127-134. https://doi.org/10.4081/gh.2012.111