BackgroundThis was a panel study of the prevalence of C. burnetii infection in does in an endemic dairy goat enterprise in Victoria, Australia. Our first objective was to determine the prevalence of does shedding C. burnetii at the time of parturition and to quantify the concentration of genome equivalents (GE) present in each C. burnetii positive sample. Our second objective was to determine the proportion of positive does that were persistent shedders. Our final objective was to quantify the association between C. burnetii qPCR status at the time of kidding and daily milk volumes produced during the subsequent lactation.ResultsVaginal swabs (n= 490) were collected from does at the time of kidding and analysed using a quantitative polymerase chain reaction (qPCR) assay. Shedding of C. burnetii was detected in 15% (95% CI: 12% to 18%) of the sampled does. Does were classified as qPCR-negative, qPCR-positive low and qPCR-positive high based on the estimated concentration of GE from the qPCR. Persistent shedding at relatively low concentrations was detected in 20% (95% CI: 10% to35%) of shedding does sampled again at their subsequent parturition. After controlling for possible confounders and adjusting for variation in daily milk yields at the individual doe level, daily milk yields for qPCR-positive high does were reduced by 17% (95% CI: 3% to 32%) compared to qPCR-negative does (p= 0.02).ConclusionsShedding concentrations of C. burnetii were highly skewed, with a relatively small group of does shedding relatively high quantities of C. burnetii. Further, high shedding does had reduced milk yields compared to qPCR-negative does. Early detection and culling of high shedding does would result in increased farm profitability and reduce the risk of Q fever transmission.
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Background Q fever is a zoonotic disease that can cause prolonged and debilitating illness in humans. Australia has the highest number of cases reported in the world and animal-human outbreaks would require a coordinated response from both animal and public health authorities. Methods Expert opinion workshops are conducted across several states in Australia. Discussions were audio recorded and transcribed for thematic analysis to elicit sources and routes of transmission that would lead to a large human outbreak, risk factors for outbreaks and variations between states. Results Sources of Q fever for human infection differ between jurisdictions, influenced by disease occurrence and case infection source. Risk factors include aggregation of animals, environmental effects and naïve human contact. Community acquired infection is perceived as a greater outbreak risk than occupationally acquired due to lack of awareness, absence of vaccination and increased exposure of the public. Conclusions Disease occurrence and sources of infection are variable across jurisdictions and a generalised outbreak plan is not the solution. The framework for action must reflect differences identified between jurisdictions. Key messages Expert opinion regarding sources and routes of transmission for a large human Q fever outbreak highlights prevailing differences between jurisdictions, for which a one size fits all outbreak response plan will not be effective.
Background Q fever is a zoonotic disease that can cause prolonged and debilitating illness in humans. Australia has the highest number of cases reported in the world despite the availability of an effective vaccine. Infection is most common among livestock workers, however the demographics affected by Q fever is expanding from occupationally-acquired to include community-acquired cases. The disease has potential to cause large and widespread outbreaks and the number of cases and outbreaks in Australia is increasing. Q fever is a disease with an animal-human interface and outbreaks involving both animals and humans would require a response from both animal health and public health authorities. However, in the absence of a framework for coordination between human and animal health systems, national preparedness for large outbreak detection and control is suboptimal. Q fever is a complex disease to deal with because of limited knowledge on disease transmission and acquisition; an epidemiology that varies with geographical environment; and awareness and responses by human and animal health authorities differ by jurisdiction. To develop an effective outbreak response plan, an understanding of the Australian context under which the plan operates is required. Important components of the plan should include the development of capabilities for both early warning and reaction to Q fever outbreaks. Research is required to understand differences in disease occurrence and the role of system structure between jurisdictions, as well as identifying gaps in knowledge and practice that would delay detection of Q fever outbreaks and provide information that would underpin good policy response. Outbreak preparedness is essential to limit the likelihood of a large and prolonged Q fever outbreak in Australia. In turn, this will reduce the burden of an extremely debilitating disease on the community and maintain Australia’s position as an exporter of premium agricultural produce. Methods Experts in Q fever for human and animal health from each region (Vic, NSW, WA, Brisbane, Townsville, Tas) are identified and invited to participate in Q fever workshop focus groups. Workshops are held with experts from different regions of the country as the risks, sources and routes of transmission are likely to vary according to geographical location and need to be reflected in the national guidelines. Experts are those who have extensive knowledge and experience working with Q fever as well as a sound understanding of the human or animal health systems in which they operate. The list of expert stakeholders for consideration are included in figure 1. Workshops are conducted as focus group interviews and held face-to-face or online via Zoom. Participants from each state are divided into groups of 5-8 people, depending on the number of attendees, with representation from human and animal health in each group. Each group is required to complete a series of exercises, facilitated by a member of the research team. All discussion is audio recorded. Audio recordings are transcribed using a professional transcription service. The transcribed data is reviewed by the researcher in conjunction with the recordings. Thematic analysis is used to identify and analyse for patterns (themes) within the data. This process relies on coding the data. Codes are a word or short phrase that assigns a summative attribute to a portion of transcribed data. Thematic analysis and development of codes is driven by the specific research objectives of describing large Q fever outbreak scenarios, sources and routes of exposures, knowledge gaps and issues with diagnosis and reporting. Thematic analysis using the deductive top-down, data driven approach, is performed on the qualitative data with the software NVIVO 12, according to the methodology described by Braun and Clarke (2006): After data familiarization is performed, initial codes are considered for each region and compiled into a code book (coding frame) for review by the research team. This is followed by an iterative process of independent data coding by two research team members. This process involves sorting and organizing sections of transcribed conversation into meaningful groups under the code book. Intercoder-reliability and degree of agreement between the coders is assessed using NIVO Coding Comparison query to derive percentage agreement and kappa coefficient. Based on emerging patterns and relationships, codes are organized into overarching themes. All themes are assessed in relation to each other. Results Preliminary results indicate opinions regarding important sources of Q fever for human infection differ between jurisdictions. This variability is influenced by the occurrence of human cases and the likely known source for infection of cases in that area. While ruminant livestock are traditionally associated with human cases, risk estimates from these species ranged from low to high, depending upon the predominance of the species in the area, industry awareness and precautionary action taken by businesses. Pigs and horses were consistently ranked as low due to the absence of human cases associated with these animals. Wildlife were considered as high and emerging risks by several groups in NSW and QLD because of urban encroachment, environmental contamination and increasing human contact. Sheep and goat dairies were identified by groups in most states as growing industries that pose an emerging risk. Recurrent overarching risk factors described by the groups include aggregation and movement of animals known to be carriers of Q fever, environmental effects and exposure of naïve human populations. Community acquired Q fever is perceived to be a greater outbreak risk than occupationally acquired Q fever due to the lack of awareness, absence of vaccination and increased exposure of the general public. Conclusions Since disease occurrence and sources of infection are so variable across jurisdictions, there will not be a one size fits all solution for an outbreak response plan that can be uniformly applied across the nations states and territories. Generalised opinion cannot be used to inform policy that will be effective across all jurisdictions. Action toward disease outbreaks is the responsibility of individual states and the framework for action must reflect differences identified between jurisdictions. Information specific to each state regarding Q fever outbreaks has been collected from expert judgement to develop an understanding of the context under which an outbreak response plan has to operate. Further research is being planned to understand the structure of the human and animal health systems for each region and how a response can be coordinated to deal with a large human Q fever outbreak associated with an animal source. Key messages Expert opinion regarding sources and routes of transmission for a large human Q fever outbreak highlights that there are prevailing differences between jurisdictions, for which a one size fits all outbreak response plan will not be effective.
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