Brucella suis Seroprevalence and Associated Risk Factors in Dogs in Eastern Australia, 2016 to 2019

Brucella suis is a zoonotic disease of feral pigs that also affects pig hunting dogs, pig hunters, veterinarians and veterinary staff. In recent years the incidence of B. suis in the eastern Australian states of New South Wales (NSW) and Queensland (QLD) has increased. A cross-sectional study was conducted to document the seroprevalence, geographical extent and risk factors for B. suis in dogs at-risk of contracting the disease. Eligible dogs were those that were known to hunt or consume feral pig meat. Dogs were enrolled through private veterinary clinics and/or directly by District Veterinarians in six regions of NSW and QLD. Blood was collected by venepuncture and tested for B. suis antibodies using the Rose Bengal Test (RBT) followed by a Complement Fixation Test (CFT) if they returned a positive RBT. Owners were invited to complete a questionnaire on the dogs' signalment, husbandry including hunting practices and locations, and any clinical signs referable to brucellosis. Of the 317 dogs included in the prevalence survey, 21 were seropositive returning a survey-adjusted true seroprevalence of 9.3 (95% CI 0.45 to 18) B. suis positive dogs per 100 dogs at-risk. True seroprevalence ranged from 0 to 24 B. suis positive dogs per 100 across eastern Australia, with the highest prevalence in central west NSW and southern QLD. Adjusted for other factors, dogs that shared a household with other seropositive dogs and those that traveled away from their home regions to hunt were more likely to be seropositive. Clinical signs at presentation were not predictive of serostatus, with seropositive and seronegative dogs equally likely to present with signs consistent with brucellosis. The results obtained from this study show that B. suis exposure is relatively common in dogs that have contact with feral pigs, with one in 10 testing seropositive. Further studies are needed to understand the progression and risk of transmission from seropositive dogs

Development and Application of a Framework for Emerging Infectious Disease Intelligence in Lower Resource Settings

Frontline mobile phone-based reporting has the potential to contribute to emerging infectious disease (EID) intelligence as shown by the Infectious Disease Surveillance and Analysis System (IDSAS). This article proposes an EID intelligence framework that can be informed by published literature from the fields of surveillance, epidemic intelligence, and military intelligence. The underlying premise is the need for a framework which reflects the notion that a change in health of animal populations could indicate an impending EID event of human health significance, and functions separately from the Centers for Disease Control and Prevention (CDC) Guidelines for Evaluating Public Health Surveillance Systems

Mobile Phone-based Infectious Disease Surveillance System, Sri Lanka

Because many infectious diseases are emerging in animals in low-income and middle-income countries, surveillance of animal health in these areas may be needed for forecasting disease risks to humans. We present an overview of a mobile phone–based frontline surveillance system developed and implemented in Sri Lanka. Field veterinarians reported animal health information by using mobile phones. Submissions increased steadily over 9 months, with ≈4,000 interactions between fi eld veterinarians and reports on the animal population received by the system. Development of human resources and increased communication between local stakeholders (groups and persons whose actions are affected by emerging infectious diseases and animal health) were instrumental for successful implementation. The primary lesson learned was that mobile phone–based surveillance of animal populations is acceptable and feasible in lower-resource settings. However, any system implementation plan must consider the time needed to garner support for novel surveillance methods among users and stakeholders

A Hidden Markov Model for Analysis of Frontline Veterinary Data for Emerging Zoonotic Disease Surveillance

Surveillance systems tracking health patterns in animals have potential for early warning of infectious disease in humans, yet there are many challenges that remain before this can be realized. Specifically, there remains the challenge of detecting early warning signals for diseases that are not known or are not part of routine surveillance for named diseases. This paper reports on the development of a hidden Markov model for analysis of frontline veterinary sentinel surveillance data from Sri Lanka. Field veterinarians collected data on syndromes and diagnoses using mobile phones. A model for submission patterns accounts for both sentinel-related and disease-related variability. Models for commonly reported cattle diagnoses were estimated separately. Region-specific weekly average prevalence was estimated for each diagnoses and partitioned into normal and abnormal periods. Visualization of state probabilities was used to indicate areas and times of unusual disease prevalence. The analysis suggests that hidden Markov modelling is a useful approach for surveillance datasets from novel populations and/or having little historical baselines

Animal health surveillance for early detection of emerging infectious disease risks

Bibliography: p. 206-234A couple of pages are in colour.Includes copy of ethics approval. Original copy with original Partial Copyright Licence

A focused ethnographic study of Sri Lankan government field veterinarians' decision making about diagnostic laboratory submissions and perceptions of surveillance.

The global public health community is facing the challenge of emerging infectious diseases. Historically, the majority of these diseases have arisen from animal populations at lower latitudes where many nations experience marked resource constraints. In order to minimize the impact of future events, surveillance of animal populations will need to enable prompt event detection and response. Many surveillance systems targeting animals rely on veterinarians to submit cases to a diagnostic laboratory or input clinical case data. Therefore understanding veterinarians' decision-making process that guides laboratory case submission and their perceptions of infectious disease surveillance is foundational to interpreting disease patterns reported by laboratories and engaging veterinarians in surveillance initiatives. A focused ethnographic study was conducted with twelve field veterinary surgeons that participated in a mobile phone-based surveillance pilot project in Sri Lanka. Each participant agreed to an individual in-depth interview that was recorded and later transcribed to enable thematic analysis of the interview content. Results found that field veterinarians in Sri Lanka infrequently submit cases to laboratories--so infrequently that common case selection principles could not be described. Field veterinarians in Sri Lanka have a diagnostic process that operates independently of laboratories. Participants indicated a willingness to take part in surveillance initiatives, though they highlighted a need for incentives that satisfy a range of motivations that vary among field veterinarians. This study has implications for the future of animal health surveillance, including interpretation of disease patterns reported, system design and implementation, and engagement of data providers

A focused ethnographic study of Alberta cattle veterinarians' decision making about diagnostic laboratory submissions and perceptions of surveillance programs.

The animal and public health communities need to address the challenge posed by zoonotic emerging infectious diseases. To minimize the impacts of future events, animal disease surveillance will need to enable prompt event detection and response. Diagnostic laboratory-based surveillance systems targeting domestic animals depend in large part on private veterinarians to submit samples from cases to a laboratory. In contexts where pre-diagnostic laboratory surveillance systems have been implemented, this group of veterinarians is often asked to input data. This scenario holds true in Alberta where private cattle veterinarians have been asked to participate in the Alberta Veterinary Surveillance Network-Veterinary Practice Surveillance, a platform to which pre-diagnostic disease and non-disease case data are submitted. Consequently, understanding the factors that influence these veterinarians to submit cases to a laboratory and the complex of factors that affect their participation in surveillance programs is foundational to interpreting disease patterns reported by laboratories and engaging veterinarians in surveillance. A focused ethnographic study was conducted with ten cattle veterinarians in Alberta. Individual in-depth interviews with participants were recorded and transcribed to enable thematic analysis. Laboratory submissions were biased toward outbreaks of unknown cause, cases with unusual mortality rates, and issues with potential herd-level implications. Decreasing cattle value and government support for laboratory testing have contributed to fewer submissions over time. Participants were willing participants in surveillance, though government support and collaboration were necessary. Changes in the beef industry and veterinary profession, as well as cattle producers themselves, present both challenges and opportunities in surveillance

Research aims linked to the themes and categories that emerged during data analysis.

<p>Research aims linked to the themes and categories that emerged during data analysis.</p

Leading open-ended questions and follow-up probes used during in-depth interviews.

<p>Leading open-ended questions and follow-up probes used during in-depth interviews.</p

Open-ended questions and follow-up probes used during in-depth interviews.

<p>Open-ended questions and follow-up probes used during in-depth interviews.</p