4.6 Article

Human Q fever incidence is associated to spatiotemporal environmental conditions

Journal

ONE HEALTH
Volume 2, Issue -, Pages 77-87

Publisher

ELSEVIER
DOI: 10.1016/j.onehlt.2016.03.004

Keywords

Q fever; Environmental; Risk factors; Atmospheric dispersion model; Prediction; Multivariate; Coxiella burnetii; Concentration; Vegetation; Soil moisture

Funding

  1. National Institute for Public Health and the Environment [S/210106/01/RQ]
  2. ZonMW [205520010]

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Airborne pathogenic transmission from sources to humans is characterised by atmospheric dispersion and influence of environmental conditions on deposition and reaerosolisation. We applied a One Health approach using human, veterinary and environmental data regarding the 2009 epidemic in The Netherlands, and investigated whether observed human Q fever incidence rates were correlated to environmental risk factors. We identified 158 putative sources (dairy goat and sheep farms) and included 2339 human cases. We performed a high-resolution (1 x 1 km) zero-inflated regression analysis to predict incidence rates by Coxiella burnetii concentration (using an atmospheric dispersion model and meteorological data), and environmental factors - including vegetation density, soil moisture, soil erosion sensitivity, and land use data - at a yearly and monthly time-resolution. With respect to the annual data, airborne concentration was the most important predictor variable (positively correlated to incidence rate), followed by vegetation density (negatively). The other variables were also important, but to a less extent. High erosion sensitive soils and the land-use fractions city and forest were positively correlated. Soil moisture and land-use open nature were negatively associated. The geographical prediction map identified the largest Q fever outbreak areas. The hazard map identified highest hazards in a livestock dense area. We conclude that environmental conditions are correlated to human Q fever incidence rate. Similar research with data from other outbreaks would be needed to more firmly establish our findings. This could lead to better estimations of the public health risk of a C. burnetii outbreak, and to more detailed and accurate hazard maps that could be used for spatial planning of livestock operations. (c) 2016 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

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