Spatial transmission risk during the 2007-2010 Q fever epidemic in The Netherlands: Analysis of the farm-to-farm and farm-to-resident transmission

• Published in: PloS one Vol. 15; no. 2; p. e0227491
• Main Authors: Koeijer, Aline A de, Hagenaars, Thomas J, Leuken, Jeroen P G van, Swart, Arno N, Boender, Gert Jan
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 04.02.2020; Public Library of Science (PLoS)
• Subjects: Abortion; Animals; Bacteriology; Basic Reproduction Number; Biology and Life Sciences; Dairy farms; Datasets; Disease control; Disease transmission; Epidemics; Epidemiology; Estimation; Farms; Fever; Geography; Goat Diseases - epidemiology; Goats; Goats - microbiology; Health risk assessment; Health risks; Health services; Humans; Infectious diseases; Kernels; Livestock farms; Medicine and Health Sciences; Netherlands; Netherlands - epidemiology; People and places; Population Density; Public health; Q fever; Q Fever - epidemiology; Q Fever - transmission; Risk; Risk Factors; Zoonoses; Netherlands
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0227491

Between 2007 and 2010 a Q fever epidemic in Dutch dairy goat farms caused a large Q fever outbreak in human residents in the southern part of the Netherlands. Here we characterize the transmission of Coxiella burnetii, the aetiological agent of Q fever, between infected and susceptible dairy goat farms by estimating a spatial transmission kernel. In addition, we characterize the zoonotic transmission of C. burnetii by estimating the spatial kernel for transmission from infected farms to neighbouring residents. Whereas the range of between-farm transmission is comparable to the scale of the Netherlands, likely due to long-range between-farm contacts such as animal transport, the transmission risk from farms to humans is more localized, although still extending to 10 km and beyond. Within a range of about 10 km, the transmission risk from an infected goat farm to a single resident is of the same order of magnitude as the farm-to-farm transmission risk per animal in a receiving farm. We illustrate how, based on the estimated kernels, spatial patterns of transmission risks between farms and from farms to residents can be calculated and visualized by means of risk maps, offering further insight relevant to policy making in a one-health context.