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Background: Following outbreaks in other parts of the Netherlands, the Dutch border region of South Limburg experienced a large-scale outbreak of human Q fever related to a single dairy goat farm in 2009, with surprisingly few cases reported from neighbouring German counties. Late chronic Q fever, with recent spikes of newly detected cases, is an ongoing public health concern in the Netherlands. We aimed to assess the scope and scale of any undetected cross-border transmission to neighbouring German counties, where individuals unknowingly exposed may carry extra risk of overlooked diagnosis., Methods: (A) Seroprevalence rates in the Dutch area were estimated fitting an exponential gradient to the geographical distribution of notified acute human Q fever cases, using seroprevalence in a sample of farm township inhabitants as baseline. (B) Seroprevalence rates in 122 neighbouring German postcode areas were estimated from a sample of blood donors living in these areas and attending the regional blood donation centre in January/February 2010 (n = 3,460). (C) Using multivariate linear regression, including goat and sheep densities, veterinary Q fever notifications and blood donor sampling densities as covariates, we assessed whether seroprevalence rates across the entire border region were associated with distance from the farm., Results: (A) Seroprevalence in the outbreak farm's township was 16.1%. Overall seroprevalence in the Dutch area was 3.6%. (B) Overall seroprevalence in the German area was 0.9%. Estimated mean seroprevalence rates (per 100,000 population) declined with increasing distance from the outbreak farm (0-19 km = 2,302, 20-39 km = 1,122, 40-59 km = 432 and ≥60 km = 0). Decline was linear in multivariate regression using log-transformed seroprevalence rates (0-19 km = 2.9 [95% confidence interval (CI) = 2.6 to 3.2], 20 to 39 km = 1.9 [95% CI = 1.0 to 2.8], 40-59 km = 0.6 [95% CI = -0.2 to 1.3] and ≥60 km = 0.0 [95% CI = -0.3 to 0.3])., Conclusions: Our findings were suggestive of widespread cross-border transmission, with thousands of undetected infections, arguing for intensified cross-border collaboration and surveillance and screening of individuals susceptible to chronic Q fever in the affected area., (© 2020 The Authors. Transboundary and Emerging Diseases published by Blackwell Verlag GmbH.)

Objective: Q fever epidemic outbreaks have been reported in French Guiana and in The Netherlands. To determine whether the C. burnetii strains involved in these epidemics had a peculiar virulence pattern, we compared the pathogenicity of the Guiana and the German strain (a clone of The Netherlands strain), in silico, in vitro, and in vivo versus the Nine Mile strain., Method: The pan-genomes of the Guiana (Cb175), German (Z3055), and the referent Nine Mile (RSA 493) C. burnetii strains were compared. In vitro, the growth rate and the morphological presentation were compared. In vivo (SCID and Balb/c mice), weight loss, histological lesions, C. burnetii bacterial load in deep organs, and serological response were reported according to each C. burnetii strain studied., Results: The Guiana strain had 77 times more missing genes and 12 times more unique genes than the German strain. The Guiana strain presented as large cell variants (LCVs) and led to the most pronounced fatality rate in SCID mice (100% at 4 weeks). The German strain presented as small cell variants (SCVs), and had an intermediate fatality rate (75% at 4 weeks). Both the Guiana and the German strains led to a significant higher serological response at 2 and 4 weeks post infection (p <0.05)., Conclusion: The Guiana strain was the most virulent strain, followed by the German strain and the referent Nine Mile strain. Unique and missing genes could be implicated but further investigations are necessary to specify their role., (Copyright © 2019 European Society of Clinical Microbiology and Infectious Diseases. Published by Elsevier Ltd. All rights reserved.)

We investigated an outbreak of Q fever in a remote rural town in New South Wales, Australia. Cases identified through active and passive case finding activities, and retrospective laboratory record review were interviewed using a standard questionnaire. Two sets of case-case analyses were completed to generate hypotheses regarding clinical, epidemiological and exposure risk factors associated with infection during the outbreak. Laboratory-confirmed outbreak cases (n=14) were compared with an excluded case group (n=16) and a group of historic Q fever cases from the region (n=106). In comparison with the historic case group, outbreak cases were significantly more likely to be female (43% vs. 18% males, P = 0.04) and identify as Aboriginal (29% vs. 7% non-Aboriginal, P = 0.03). Similarly, very few cases worked in high-risk occupations (21% vs. 84%, P < 0.01). Most outbreak cases (64%) reported no high-risk exposure activities in the month prior to onset. In comparison with the excluded case group, a significantly increased proportion of outbreak cases had contact with dogs (100% vs. 63%, P = 0.02) or sighted kangaroos on their residential property (100% vs. 60%, P = 0.02). High rates of tick exposure (92%) were also reported, although this was not significantly different from the excluded case group. While a source of this outbreak could not be confirmed, our findings suggest infections likely occurred via inhalation of aerosols or dust contaminated by Coxiella burnetii, dispersed through the town from either an unidentified animal facility or from excreta of native wildlife or feral animals. Alternatively transmission may have occurred via companion animals or tick vectors.

Q fever is an almost ubiquitous zoonosis caused by Coxiella burnetii, which is able to infect several animal species, as well as humans. Cattle, sheep and goats are the primary animal reservoirs. In small ruminants, infections are mostly without clinical symptoms, however, abortions and stillbirths can occur, mainly during late pregnancy. Shedding of C. burnetii occurs in feces, milk and, mostly, in placental membranes and birth fluids. During parturition of infected small ruminants, bacteria from birth products become aerosolized. Transmission to humans mainly happens through inhalation of contaminated aerosols. In the last decade, there have been several, sometimes large, human Q fever outbreaks related to sheep and goats. In this review, we describe C. burnetii infections in sheep and goats, including both advantages and disadvantages of available laboratory techniques, as pathology, different serological tests, PCR and culture to detect C. burnetii. Moreover, worldwide prevalences of C. burnetii in small ruminants are described, as well as possibilities for treatment and prevention. Prevention of shedding and subsequent environmental contamination by vaccination of sheep and goats with a phase I vaccine are possible. In addition, compulsory surveillance of C. burnetii in small ruminant farms raises awareness and hygiene measures in farms help to decrease exposure of people to the organism. Finally, this review challenges how to contain an infection of C. burnetii in small ruminants, bearing in mind possible consequences for the human population and probable interference of veterinary strategies, human risk perception and political considerations., (Copyright © 2015 Elsevier B.V. All rights reserved.)

Background: As a major zoonotic pathogen, characterization of the infectivity and pathogenicity of Coxiella burnetii is essential to understand Q-fever epidemiology., Objectives: We want to extend a recently published human dose response model based on experimental challenge of young adult males to include other age groups and both genders. Additionally, we can estimate the spatial distribution of exposure based on observed outbreak data., Methods: Dose response assessment based on human challenge, is extended by including outbreak data, using location of cases as a proxy for exposure. This allows estimation of the influence of age and gender on the probability of developing symptoms of acute respiratory illness., Results: In an outbreak in Switzerland, in 1983, exposure to C. burnetii was shown to depend strongly on distance from the source. The susceptibility of males to develop Q-fever decreases with age, while in females, middle-aged women appear to have the lowest risk., Conclusions: The published dose response model for Q-fever, based on experimental challenge of a small group of human volunteers, has been updated with data from a well studied outbreak. Infectivity estimates remain high, and even low doses (of 10 or fewer organisms) cause a high risk of illness., (Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.)

Coxiella burnetii is a pathogen causing Q fever. The aim of our work was to study Z3055, a strain that is genotypically related to the strain causing the Netherlands outbreak. We compared Z3055 to 5 other completed genomes available in GenBank. We calculated the blast score ratio (BSR) to analyze genetic differences among the strains. The ratio core genome/pangenome was 98% likely other bacteria with closed pangenomes. Differences between Z3055 and the reference NMI consisted only of point mutations and insertion/deletion (INDELs). Non-synonymous mutations significantly increased in genes coding for membrane proteins (16/156 vs 103/1757, bilateral Chi(2) test, p<0.05), ankyrin repeat domains containing proteins (2/9 vs 117/1904, bilateral Chi(2) test, p<0.05), transcription factors (7/53 vs 112/1860, bilateral Chi(2) test, p<0.05) and translation proteins (15/144 vs 109/1655, bilateral Chi(2) test, p<0.05). The evolution of this strain may have been driven by mutations in critical genes., (Copyright © 2014 Elsevier Ltd. All rights reserved.)

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.