Human dose response models for Q fever: estimation of Coxiella burnetii exposure and disease burden

Abstract

The largest Q fever outbreak in the world occurred in the Netherlands between 2007 and 2009 with 4,500 reported acute symptomatic Q fever cases. Interventions were required to stop the release of aerosolized Coxiella burnetii from infected goat farms and the outbreak developed into a major public health concern. Scientific research was needed to support interventions necessary to control the outbreak and prevent future outbreaks. Specifically, this included quantifying the spatial distribution of aerosolized bacteria and quantifying the disease burden of Q fever. We show that C. burnetii is highly infectious for young adult males, with a dose of 0.71 infectious units capable of infecting 50% of exposed young adult males. Once infected, individuals can develop post infectious fatigue syndrome, a long term debilitating complication with little treatment and, we show, the greatest contributor to Q fever disease burden. Though the infection dose-response relation may not be age or gender dependent, the conditional illness dose-response relationship does depend on age and gender. Given exposure to the same dose, males have a higher probability of illness than females and individuals between 40 and 59 years of age have the highest probability of developing symptomatic acute Q fever. With these models it is also possible to predict the number of asymptomatic infections: at low exposure levels there are 11 asymptomatic infections for each notified symptomatic acute Q fever case. We study the spatial distribution of exposure during Q fever outbreaks, using the dose-response relationships to predict the number of unobserved, asymptomatic infections based on notification data. To achieve this, a geostatistical model is used to structure the dose in a dose-response model. Models show that outbreaks with high attack rates may result from low exposure levels. To study large, multi-year outbreaks, temporal trends in exposure were included in the models. Analyzing the large Netherlands outbreak shows that the spreading pattern of bacteria from infected farms did not change during the outbreak but that the exposure did increase annually. These works provide evidence to support timely interventions targeting exposure sources to reduce the number of human cases and the large disease burden associated with it.