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Abstract:
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We explore a Netherlands outbreak of Q fever in 2009 by combining a human dose-response model with geostatistics to predict local probability of infection, associated probability of illness, and local effective exposures to Coxiella burnetii. We begin with the spatial distribution of 220 notified cases in the at-risk population. Next, we use the dose-response relationship (established via historical experiments) to convert the observed risk map into an estimated smooth spatial field of local dose. Based on the observed symptomatic cases, the dose-response model predicts a median of 611 asymptomatic infections (95% range 410 to 1,084), i.e., 2.78 (95% range 1.86 to 4.93) asymptomatic infections for each reported case. The estimated peak levels of exposure extend to the north-east from the point source with an increasing proportion of asymptomatic infections further from the source. Our work combines established methodology from model-based geostatistics and dose-response modeling providing a novel approach to study outbreaks. Such predictions (and associated uncertainties) are important for targeting interventions during an outbreak, estimating future disease burden, and planning
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