Improved correlation of human Q fever incidence to modelled C. burnetii concentrations by means of an atmospheric dispersion model

Combining a parsimonious mathematical model with infection data from tailor-made experiments to understand environmental transmission

Although most infections are transmitted through the environment, the processes underlying the environmental stage of transmission are still poorly understood for most systems. Improved understanding of the environmental transmission dynamics is important for effective non-pharmaceutical intervention strategies. To study the mechanisms underlying environmental transmission we formulated a parsimonious modelling framework including hypothesised mechanisms of pathogen dispersion and decay. To calibrate and validate the model, we conducted a series of experiments studying distance-dependent transmission of Campylobacter jejuni in broilers. We obtained informative simultaneous estimates for all three model parameters: the parameter of C. jejuni inactivation, the diffusion coefficient describing pathogen dispersion, and the transmission rate parameter. The time and distance dependence of transmission in the fitted model is quantitatively consistent with marked spatiotemporal patterns in the experimental observations. These results, for C. jejuni in broilers, show that the application of our modelling framework to suitable transmission data can provide mechanistic insight in environmental pathogen transmission.

Performance Evaluation and Validation of Air Samplers To Detect Aerosolized Coxiella burnetii

Coxiella burnetii, the etiological agent of Q fever, is an intracellular zoonotic pathogen transmitted via the respiratory route. Once released from infected animals, C. burnetii can travel long distances through air before infecting another host. As such, the ability to detect the presence of C. burnetii in air is important. In this study, three air samplers, AirPort MD8, BioSampler, and the Coriolis Micro, were assessed against a set of predetermined criteria in the presence of three different aerosolized C. burnetii concentrations. Two liquid collection media, phosphate-buffered saline (PBS) and alkaline polyethylene glycol (Alk PEG), were tested with devices requiring a collection liquid. Samples were tested by quantitative polymerase chain reaction assay (qPCR) targeting the single-copy com1 gene or multicopy insertion element IS1111. All air samplers performed well at detecting airborne C. burnetii across the range of concentrations tested. At high nebulized concentrations, AirPort MD8 showed higher, but variable, recovery probabilities. While the BioSampler and Coriolis Micro recovered C. burnetii at lower concentrations, the replicates were far more repeatable. At low and intermediate nebulized concentrations, results were comparable in the trials between air samplers, although the AirPort MD8 had consistently higher recovery probabilities. In this first study validating air samplers for their ability to detect aerosolized C. burnetii, we found that while all samplers performed well, not all samplers were equal. It is important that these results are further validated under field conditions. These findings will further inform efforts to detect airborne C. burnetii around known point sources of infection. IMPORTANCE Coxiella burnetii causes Q fever in humans and coxiellosis in animals. It is important to know if C. burnetii is present in the air around putative sources as it is transmitted via inhalation. This study assessed air samplers (AirPort MD8, BioSampler, and Coriolis Micro) for their efficacy in detecting C. burnetii. Our results show that all three devices could detect aerosolized bacteria effectively; however, at high concentrations the AirPort performed better than the other two devices, showing higher percent recovery. At intermediate and low concentrations AirPort detected at a level higher than or similar to that of other samplers. Quantification of samples was hindered by the limit of quantitation of the qPCR assay. Compared with the other two devices, the AirPort was easier to handle and clean in the field. Testing air around likely sources (e.g., farms, abattoirs, and livestock saleyards) using validated sampling devices will help better estimate the risk of Q fever to nearby communities.

Regional Relative Risk, a Physics-Based Metric for Characterizing Airborne Infectious Disease Transmission

Airborne infectious disease transmission events occur over a wide range of spatial scales and can be an important means of disease transmission. Physics- and biology-based models can assist in predicting airborne transmission events, overall disease incidence, and disease control strategy efficacy. We describe a new theory that extends current approaches for the case in which an individual is infected by a single airborne particle, including the scenario in which numerous infectious particles are present in the air but only one causes infection. A single infectious particle can contain more than one pathogenic microorganism and be physically larger than the pathogen itself. This approach allows robust relative risk estimates even when there is wide variation in (i) individual exposures and (ii) the individual response to that exposure (the pathogen dose-response function can take any mathematical form and vary by individual). Based on this theory, we propose the regional relative risk-a new metric, distinct from the traditional relative risk metric, that compares the risk between two regions. In theory, these regions can range from individual rooms to large geographic areas. In this paper, we apply the regional relative risk metric to outdoor disease transmission events over spatial scales ranging from 50 m to 20 km, demonstrating that in many common cases minimal input information is required to use the metric. Also, we demonstrate that the model predictions are consistent with data from prior outbreaks. Future efforts could apply and validate this theory for other spatial scales, such as transmission within indoor environments. This work provides context for (i) the initial stages of an airborne disease outbreak and (ii) larger-scale disease spread, including unexpected low-probability disease "sparks" that potentially affect remote populations, a key practical issue in controlling airborne disease outbreaks. IMPORTANCE Airborne infectious disease transmission events occur over a wide range of spatial scales and can be important to disease outbreaks. We describe a new physics- and biology-based theory for the important case in which individuals are infected by a single airborne particle (even though numerous infectious particles can be emitted into the air and inhaled). Based on this theory, we propose a new epidemiological metric, regional relative risk, that compares the risk between two geographic regions (in theory, regions can range from individual rooms to large areas). Our modeling of transmission events predicts that for many scenarios of interest, minimal information is required to use this metric for locations 50 m to 20 km downwind. This prediction is consistent with data from prior disease outbreaks. Future efforts could apply and validate this theory for other spatial scales, such as indoor environments. Our results may be applicable to many airborne diseases a priori, as these results depend on the physics of airborne particulate dispersion.

Atmospheric dispersion and transmission of Legionella from wastewater treatment plants: A 6-year case-control study

Legionnaires Disease incidence has risen in the Netherlands in recent years. For the majority of the cases, the source of infection is never identified. Two Dutch wastewater treatment plants (WWTPs) have previously been identified as source of outbreaks of Legionnaires Disease (LD) among local residents. The objective of this study is to examine if LD patients in the Netherlands are more exposed to aerosols originating from WWTPs than controls.

METHODS

An atmospheric dispersion model was used to generate nationwide exposure maps of aerosols from 776 WWTPs in the Netherlands. Municipal sewage treatment plants and industrial WWTPs were both included. Exposure of LD cases and controls at the residential address was compared, in a matched case-control design using a conditional logistic regression. Cases were notified LD cases with onset of disease in the period 2013-2018 in the Netherlands (n = 1604).

RESULTS

Aerosols dispersed over a large part of the Netherlands, but modelled concentrations are estimated to be elevated in close proximity to WWTPs. A statistically significant association was found between LD and the calculated annual average aerosol concentrations originating from WWTPs (odds-ratio: 1.32 (1.06-1.63)). This association remained significant when the two outbreak-related WWTPs were removed from the analysis (odds-ratio: 1.28 (1.03-1.58)).

CONCLUSION

LD cases were more exposed to aerosols from WWTPs than controls. This indicates that exposure to aerosols dispersed from WWTPs caused Legionnaires Disease in residents living near WWTPs in the period 2013-2018. In order to investigate which characteristics of WWTPs are associated with an increased LD risk, the WWTP database should be updated and more data is needed on the presence and survival of aerosolized Legionella bacteria to improve the Legionella dispersion modelling. Furthermore, it is recommended to further investigate how aerosol dispersion of WWTPs can effectively be reduced in order to reduce the potential health risk.

Multi-Scale Airborne Infectious Disease Transmission

Airborne disease transmission is central to many scientific disciplines including agriculture, veterinary biosafety, medicine, and public health. Legal and regulatory standards are in place to prevent agricultural, nosocomial, and community airborne disease transmission. However, the overall importance of the airborne pathway is underappreciated, e.g.,, US National Library of Medicine's Medical Subjects Headings (MESH) thesaurus lacks an airborne disease transmission indexing term. This has practical consequences as airborne precautions to control epidemic disease spread may not be taken when airborne transmission is important, but unrecognized. Publishing clearer practical methodological guidelines for surveillance studies and disease outbreak evaluations could help address this situation.To inform future work, this paper highlights selected, well-established airborne transmission events - largely cases replicated in multiple, independently conducted scientific studies. Methodologies include field experiments, modeling, epidemiology studies, disease outbreak investigations and mitigation studies. Collectively, this literature demonstrates that airborne viruses, bacteria, and fungal pathogens have the capability to cause disease in plants, animals, and humans over multiple distances - from near range (< 5 m) to continental (> 500 km) in scale. The plausibility and implications of undetected airborne disease transmission are discussed, including the notable underreporting of disease burden for several airborne transmitted diseases.

Relationship between Coxiella burnetii (Q fever) antibody serology and time spent outdoors

BACKGROUND/AIM

From 2007 through 2010, the Netherlands experienced the largest recorded Q fever outbreak to date. People living closer to Coxiella burnetii infected goat farms were at increased risk for acute Q fever. Time spent outdoors near infected farms may have contributed to exposure to C. burnetii. The aim of this study was to retrospectively evaluate whether hours/week spent outdoors, in the vicinity of previously C. burnetii infected goat farms, was associated with presence of antibodies against C. burnetii in residents of a rural area in the Netherlands.

METHODS

Between 2014-2015, we collected C. burnetii antibody serology and self-reported data about habitual hours/week spent outdoors near the home from 2494 adults. From a subgroup we collected 941 GPS tracks, enabling analyses of active mobility in the outbreak region. Participants were categorised as exposed if they spent time within specified distances (500m, 1000m, 2000m, or 4000m) of C. burnetii infected goat farms. We evaluated whether time spent near these farms was associated with positive C. burnetii serology using spline analyses and logistic regression.

RESULTS

People that spent more hours/week outdoors near infected farms had a significantly increased risk for positive C. burnetii serology (time spent within 2000m of a C. burnetii abortion-wave positive farm, OR 3.6 (1.2-10.6)), compared to people spending less hours/week outdoors.

CONCLUSIONS

Outdoor exposure contributed to the risk of becoming C. burnetii serology positive. These associations were stronger if people spent more time near C. burnetii infected farms. Outdoor exposure should, if feasible, be included in outbreak investigations.

Current perspectives on the transmission of Q fever: Highlighting the need for a systematic molecular approach for a neglected disease in Africa

Q fever is a bacterial worldwide zoonosis (except New Zealand) caused by the Gram-negative obligate intracellular bacterium Coxiella burnetii (C. burnetii). The bacterium has a large host range including arthropods, wildlife and companion animals and is frequently identified in human and livestock populations. In humans, the disease can occur as either a clinically acute or chronic aetiology, affecting mainly the lungs and liver in the acute disease, and heart valves when chronic. In livestock, Q fever is mainly asymptomatic; however, the infection can cause abortion, and the organism is shed in large quantities, where it can infect other livestock and humans. The presence of Q fever in Africa has been known for over 60 years, however while our knowledge of the transmission routes and risk of disease have been well established in many parts of the world, there is a significant paucity of knowledge across the African continent, where it remains a neglected zoonosis. Our limited knowledge of the disease across the African sub-continent have relied largely upon observational (sero) prevalence studies with limited focus on the molecular epidemiology of the disease. This review highlights the need for systematic studies to understand the routes of C. burnetii infection, and understand the disease burden and risk factors for clinical Q fever in both humans and livestock. With such knowledge gaps filled, the African continent could stand a better chance of eradicating Q fever through formulation and implementation of effective public health interventions.

A systematic knowledge synthesis on the spatial dimensions of Q fever epidemics

From 2007 through 2010, the Netherlands experienced the largest Q fever epidemic ever reported. This study integrates the outcomes of a multidisciplinary research programme on spatial airborne transmission of Coxiella burnetii and reflects these outcomes in relation to other scientific Q fever studies worldwide. We have identified lessons learned and remaining knowledge gaps. This synthesis was structured according to the four steps of quantitative microbial risk assessment (QMRA): (a) Rapid source identification was improved by newly developed techniques using mathematical disease modelling; (b) source characterization efforts improved knowledge but did not provide accurate C. burnetii emission patterns; (c) ambient air sampling, dispersion and spatial modelling promoted exposure assessment; and (d) risk characterization was enabled by applying refined dose–response analyses. The results may support proper and timely risk assessment and risk management during future outbreaks, provided that accurate and structured data are available and exchanged readily between responsible actors.

Airborne geographical dispersal of Q fever from livestock holdings to human communities: a systematic review and critical appraisal of evidence

BACKGROUND

Q fever is a zoonotic disease caused by Coxiella burnetii. This bacterium survives harsh conditions and attaches to dust, suggesting environmental dispersal is a risk factor for outbreaks. Spatial epidemiology studies collating evidence on Q fever geographical contamination gradients are needed, as human cases without occupational exposure are increasing worldwide.

METHODS

We used a systematic literature search to assess the role of distance from ruminant holdings as a risk factor for human Q fever outbreaks. We also collated evidence for other putative drivers of C. burnetii geographical dispersal.

RESULTS

In all documented outbreaks, infective sheep or goats, not cattle, was the likely source. Evidence suggests a prominent role of airborne dispersal; Coxiella burnetii travels up to 18 km on gale force winds. In rural areas, highest infection risk occurs within 5 km of sources. Urban outbreaks generally occur over smaller distances, though evidence on attack rate gradients is limited. Wind speed / direction, spreading of animal products, and stocking density may all contribute to C. burnetii environmental gradients.

CONCLUSIONS

Q fever environmental gradients depend on urbanization level, ruminant species, stocking density and wind speed. While more research is needed, evidence suggests that residential exclusion zones around holdings may be inadequate to contain this zoonotic disease, and should be species-specific.

Spatial Prediction of Coxiella burnetii Outbreak Exposure via Notified Case Counts in a Dose-Response Model

We develop a novel approach to study an outbreak of Q fever in 2009 in the Netherlands by combining a human dose-response model with geostatistics prediction to relate probability of infection and associated probability of illness to an effective dose of Coxiella burnetii. The spatial distribution of the 220 notified cases in the at-risk population are translated into a smooth spatial field of dose. Based on these symptomatic cases, the dose-response model predicts a median of 611 asymptomatic infections (95% range: 410, 1,084) for the 220 reported symptomatic cases in the at-risk population; 2.78 (95% range: 1.86, 4.93) asymptomatic infections for each reported case. The low attack rates observed during the outbreak range from (Equation is included in full-text article.)to (Equation is included in full-text article.). 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 allowing for a novel approach to study outbreaks. Unobserved infections and the spatially varying effective dose can be predicted using the flexible framework without assuming any underlying spatial structure of the outbreak process. Such predictions are important for targeting interventions during an outbreak, estimating future disease burden, and determining acceptable risk levels.

Farming, Q fever and public health: agricultural practices and beyond

Since the Neolithic period, humans have domesticated herbivores to have food readily at hand. The cohabitation with animals brought various advantages that drastically changed the human lifestyle but simultaneously led to the emergence of new epidemics. The majority of human pathogens known so far are zoonotic diseases and the development of both agricultural practices and human activities have provided new dynamics for transmission. This article provides a general overview of some factors that influence the epidemic potential of a zoonotic disease, Q fever. As an example of a disease where the interaction between the environment, animal (domestic or wildlife) and human populations determines the likelihood of the epidemic potential, the management of infection due to the Q fever agent, Coxiella burnetii, provides an interesting model for the application of the holistic One Health approach.

Coxiella burnetii Circulation in a Naturally Infected Flock of Sheep: Individual Follow-Up of Antibodies in Serum and Milk

The control of Q fever, a zoonotic disease caused by the Coxiella burnetii bacterium, remains a scientific challenge. Domestic ruminants are considered the main reservoir, shedding C. burnetii essentially through parturition products during abortion or birth. Sheep are particularly frequently associated with human outbreaks, but there are insufficient field data to fully understand disease dynamics and to instigate efficient control measures. A longitudinal follow-up study of a naturally infected sheep flock was performed (i) to investigate relationships between seropositivity and bacterial shedding in the vaginal mucus, (ii) to describe the kinetics of antibodies, including responses to vaccination, (iii) to monitor maternal antibodies in ewe lambs, and (iv) to compare serological results for milk and serum samples. For 8 months, we collected blood samples every 3 weeks from 11 aborting and 26 nonaborting dairy ewes, 20 nonaborting suckler ewes, and 9 ewe lambs. Individual milk samples were also obtained from lactating females. All serum and milk samples were tested by enzyme-linked immunosorbent assay (ELISA), whereas vaginal swabs were tested by quantitative PCR. We found that some dairy females did not seroconvert despite shedding C. burnetii in their vaginal mucus. Overall, antibody levels in adult females were found to remain stable over time, with exceptions during the mating and lambing periods. Maternal antibodies decreased during the first month after birth. Interestingly, antibody levels in milk were correlated with those in serum. This study provides valuable field data that will help improve Q fever surveillance and within-flock management measures.IMPORTANCE Field data are necessary to improve the surveillance, diagnosis, and sanitary management of Q fever in livestock. Here, we provide extensive serological data obtained from serum and milk samples from infected and vaccinated ewes belonging to a naturally infected flock of sheep. We show that antibody levels are stable over time and seropositivity and vaginal shedding are not clearly correlated, whereas antibody levels in milk are strongly correlated with those in serum. Accordingly, we find that antibody levels in bulk tank milk are consistent with the variations observed in the serum of dairy females over time. We report the existence of maternal antibody transmission to ewe lambs and we show that the presence of maternal antibodies at birth does not prevent the development of a serological response to vaccination at the age of 4 months. Finally, we report that adult ewes generally seroconvert after vaccination, including during pregnancy.

Molecular epidemiology of Coxiella burnetii in French livestock reveals the existence of three main genotype clusters and suggests species-specific associations as well as regional stability

Q fever is a worldwide zoonosis caused by the bacterium Coxiella burnetii. In domestic ruminants, Q fever main clinical manifestations are abortions. Although the clinical signs may differ between ruminant species, C. burnetii's genetic diversity remains understudied in enzootic areas. Here, we focused on France, where Q fever is enzootic, with the aims to (a) identify potential associations between C. burnetii genotypes and ruminant host species; (b) assess the distribution of C. burnetii genotypes both within French farms and across France's major livestock-farming regions; and (c) suggest a subset of markers for future genotypic studies. We used DNA samples collected between 2006 and 2015 from 301 females (160 cows, 76 ewes, 65 goats) aborted of Q fever within 7 different farming regions. C. burnetii diversity was determined using a multiple-locus variable-number of tandem repeat analysis (MLVA) considering 17 markers. Using a phylogenetic approach, we identified 3 main genotypic clusters divided into 12 sub-clusters. These clusters were significantly associated with ruminant species: almost all the cattle genotypes were found in a "cattle-specific" cluster whereas small ruminants genotypes essentially grouped into the two other clusters. The clusters also proved stable over space and time, some genotypes being more specifically observed in certain farming regions. We also observed some within-farm diversity but this diversity was restricted to a same genotypic cluster. Finally, we identified 6 MLVA markers that maximized the representativeness of the diversity described. Overall, we highlighted that molecular epidemiology is a relevant approach to assess C. burnetii's genetic diversity and to reveal the existence of species-specific associations and regional stability. These results will be valuable in the field to trace genotype circulation among ruminants and from ruminants to humans. Ultimately, the potential links between genotypes and virulence traits need to be investigated to adapt control measures in livestock farms.

Human Q fever incidence is associated to spatiotemporal environmental conditions

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 × 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.

Use of a Dose-Response Model to Study Temporal Trends in Spatial Exposure to Coxiella burnetii: Analysis of a Multiyear Outbreak of Q Fever

The Netherlands underwent a large Q fever outbreak between 2007 and 2009. In this paper, we study spatial and temporal Coxiella burnetii exposure trends during this large outbreak as well as validate outcomes against other published studies and provide evidence to support hypotheses on the causes of the outbreak. To achieve this, we develop a framework using a dose-response model to translate acute Q fever case incidence into exposure estimates. More specifically, we incorporate a geostatistical model that accounts for spatial and temporal correlation of exposure estimates from a human Q fever dose-response model to quantify exposure trends during the outbreak. The 2051 cases, with the corresponding age, gender and residential addresses, reside in the region with the highest attack rates during the outbreak in the Netherlands between 2006 and 2009. We conclude that the multiyear outbreak in the Netherlands is caused by sustained release of infectious bacteria from the same sources, which suggests that earlier implementation of interventions may have prevented many of the cases. The model predicts the risk of infection and acute symptomatic Q fever from multiple exposure sources during a multiple-year outbreak providing a robust, evidence-based methodology to support decision-making and intervention design.

Spread of Coxiella burnetii between dairy cattle herds in an enzootic region: modelling contributions of airborne transmission and trade

Q fever, a worldwide zoonotic disease caused by Coxiella burnetii, is a looming concern for livestock and public health. Epidemiological features of inter-herd transmission of C. burnetii in cattle herds by wind and trade of cows are poorly understood. We present a novel dynamic spatial model describing the inter-herd regional spread of C. burnetii in dairy cattle herds, quantifying the ability of airborne transmission and animal trade in C. burnetii propagation in an enzootic region. Among all the new herd infections, 92% were attributed to airborne transmission and the rest to cattle trade. Infections acquired following airborne transmission were shown to cause relatively small and ephemeral intra-herd outbreaks. On the contrary, disease-free herds purchasing an infectious cow experienced significantly higher intra-herd prevalence. The results also indicated that, for short duration, both transmission routes were independent from each other without any synergistic effect. The model outputs applied to the Finistère department in western France showed satisfactory sensitivity (0.71) and specificity (0.80) in predicting herd infection statuses at the end of one year in a neighbourhood of 3 km around expected incident herds, when compared with data. The model developed here thus provides important insights into the spread of C. burnetii between dairy cattle herds and paves the way for implementation and assessment of control strategies.

Climate change effects on airborne pathogenic bioaerosol concentrations: a scenario analysis

The most recent IPCC report presented further scientific evidence for global climate change in the twenty-first century. Important secondary effects of climate change include those on water resource availability, agricultural yields, urban healthy living, biodiversity, ecosystems, food security, and public health. The aim of this explorative study was to determine the range of expected airborne pathogen concentrations during a single outbreak or release in a future climate compared to a historical climatic period (1981-2010). We used five climate scenarios for the periods 2016-2045 and 2036-2065 defined by the Royal Netherlands Meteorological Institute and two conversion tools to create hourly future meteorological data sets. We modelled season-averaged airborne pathogen concentrations by means of an atmospheric dispersion model and compared these data to historical (1981-2010) modelled concentrations. Our results showed that modelled concentrations were modified several percentage points on average as a result of climate change. On average, concentrations were reduced in four out of five scenarios. Wind speed and global radiation were of critical importance, which determine horizontal and vertical dilution. Modelled concentrations decreased on average, but large positive and negative hourly averaged effects were calculated (from -67 to +639 %). This explorative study shows that further research should include pathogen inactivation and more detailed probability functions on precipitation, snow, and large-scale circulation.

Detection of Coxiella burnetii in Ambient Air after a Large Q Fever Outbreak

One of the largest Q fever outbreaks ever occurred in the Netherlands from 2007-2010, with 25 fatalities among 4,026 notified cases. Airborne dispersion of Coxiella burnetii was suspected but not studied extensively at the time. We investigated temporal and spatial variation of Coxiella burnetii in ambient air at residential locations in the most affected area in the Netherlands (the South-East), in the year immediately following the outbreak. One-week average ambient particulate matter < 10 μm samples were collected at eight locations from March till September 2011. Presence of Coxiella burnetii DNA was determined by quantitative polymerase chain reaction. Associations with various spatial and temporal characteristics were analyzed by mixed logistic regression. Coxiella burnetii DNA was detected in 56 out of 202 samples (28%). Airborne Coxiella burnetii presence showed a clear seasonal pattern coinciding with goat kidding. The spatial variation was significantly associated with number of goats on the nearest goat farm weighted by the distance to the farm (OR per IQR: 1.89, CI: 1.31-2.76). We conclude that in the year after a large Q fever outbreak, temporal variation of airborne Coxiella burnetii is suggestive to be associated with goat kidding, and spatial variation with distance to and size of goat farms. Aerosol measurements show to have potential for source identification and attribution of an airborne pathogen, which may also be applicable in early stages of an outbreak.

Atmospheric dispersion modelling of bioaerosols that are pathogenic to humans and livestock - A review to inform risk assessment studies

In this review we discuss studies that applied atmospheric dispersion models (ADM) to bioaerosols that are pathogenic to humans and livestock in the context of risk assessment studies. Traditionally, ADMs have been developed to describe the atmospheric transport of chemical pollutants, radioactive matter, dust, and particulate matter. However, they have also enabled researchers to simulate bioaerosol dispersion. To inform risk assessment, the aims of this review were fourfold, namely (1) to describe the most important physical processes related to ADMs and pathogen transport, (2) to discuss studies that focused on the application of ADMs to pathogenic bioaerosols, (3) to discuss emission and inactivation rate parameterisations, and (4) to discuss methods for conversion of concentrations to infection probabilities (concerning quantitative microbial risk assessment). The studies included human, livestock, and industrial sources. Important factors for dispersion included wind speed, atmospheric stability, topographic effects, and deposition. Inactivation was mainly governed by humidity, temperature, and ultraviolet radiation. A majority of the reviewed studies, however, lacked quantitative analyses and application of full quantitative microbial risk assessments (QMRA). Qualitative conclusions based on geographical dispersion maps and threshold doses were encountered frequently. Thus, to improve risk assessment for future outbreaks and releases, we recommended determining well-quantified emission and inactivation rates and applying dosimetry and dose-response models to estimate infection probabilities in the population at risk.

Integrating interdisciplinary methodologies for One Health: goat farm re-implicated as the probable source of an urban Q fever outbreak, the Netherlands, 2009

BACKGROUND

In spring 2008, a goat farm experiencing Q fever abortions ("Farm A") was identified as the probable source of a human Q fever outbreak in a Dutch town. In 2009, a larger outbreak with 347 cases occurred in the town, despite no clinical Q fever being reported from any local farm.

METHODS

Our study aimed to identify the source of the 2009 outbreak by applying a combination of interdisciplinary methods, using data from several sources and sectors, to investigate seventeen farms in the area: namely, descriptive epidemiology of notified cases; collation of veterinary data regarding the seventeen farms; spatial attack rate and relative risk analyses; and GIS mapping of farms and smooth incidence of cases. We conducted further spatio-temporal analyses that integrated temporal data regarding date of onset with spatial data from an atmospheric dispersion model with the most highly suspected source at the centre.

RESULTS

Our analyses indicated that Farm A was again the most likely source of infection, with persons living within 1 km of the farm at a 46 times larger risk of being a case compared to those living within 5-10 km. The spatio-temporal analyses demonstrated that about 60 - 65 % of the cases could be explained by aerosol transmission from Farm A assuming emission from week 9; these explained cases lived significantly closer to the farm than the unexplained cases (p = 0.004). A visit to Farm A revealed that there had been no particular changes in management during the spring/summer of 2009, nor any animal health problems around the time of parturition or at any other time during the year.

CONCLUSIONS

We conclude that the probable source of the 2009 outbreak was the same farm implicated in 2008, despite animal health indicators being absent. Veterinary and public health professionals should consider farms with past as well as current history of Q fever as potential sources of human outbreaks.

Circulation of Coxiella burnetii in a Naturally Infected Flock of Dairy Sheep: Shedding Dynamics, Environmental Contamination, and Genotype Diversity

Q fever is a worldwide zoonosis caused by Coxiella burnetii. Domestic ruminants are considered to be the main reservoir. Sheep, in particular, may frequently cause outbreaks in humans. Because within-flock circulation data are essential to implementing optimal management strategies, we performed a follow-up study of a naturally infected flock of dairy sheep. We aimed to (i) describe C. burnetii shedding dynamics by sampling vaginal mucus, feces, and milk, (ii) assess circulating strain diversity, and (iii) quantify barn environmental contamination. For 8 months, we sampled vaginal mucus and feces every 3 weeks from aborting and nonaborting ewes (n=11 and n=26, respectively); for lactating females, milk was obtained as well. We also sampled vaginal mucus from nine ewe lambs. Dust and air samples were collected every 3 and 6 weeks, respectively. All samples were screened using real-time PCR, and strongly positive samples were further analyzed using quantitative PCR. Vaginal and fecal samples with sufficient bacterial burdens were then genotyped by multiple-locus variable-number tandem-repeat analysis (MLVA) using 17 markers. C. burnetii burdens were higher in vaginal mucus and feces than in milk, and they peaked in the first 3 weeks postabortion or postpartum. Primiparous females and aborting females tended to shed C. burnetii longer and have higher bacterial burdens than nonaborting and multiparous females. Six genotype clusters were identified; they were independent of abortion status, and within-individual genotype diversity was observed. C. burnetii was also detected in air and dust samples. Further studies should determine whether the within-flock circulation dynamics observed here are generalizable.