Steps towards operationalizing One Health approaches.

One Health recognizes the health of humans, agriculture, wildlife, and the environment are interrelated. The concept has been embraced by international health and environmental authorities such as WHO, WOAH, FAO, and UNEP, but One Health approaches have been more practiced by researchers than national or international authorities. To identify priorities for operationalizing One Health beyond research contexts, we conducted 41 semi-structured interviews with professionals across One Health sectors (public health, environment, agriculture, wildlife) and institutional contexts, who focus on national-scale and international applications. We identify important challenges, solutions, and priorities for delivering the One Health agenda through government action. Participants said One Health has made progress with motivating stakeholders to attempt One Health approaches, but achieving implementation needs more guidance (action plans for how to leverage or change current government infrastructure to accommodate cross-sector policy and strategic mission planning) and facilitation (behavioral change, dedicated personnel, new training model).

Modeling the risk of aquatic species invasion spread through boater movements and river connections.

Aquatic invasive species (AIS) are one of the greatest threats to the functioning of aquatic ecosystems worldwide. Once an invasive species has been introduced to a new region, many governments develop management strategies to reduce further spread. Nevertheless, managing AIS in a new region is challenging because of the vast areas that need protection and limited resources. Spatial heterogeneity in invasion risk is driven by environmental suitability and propagule pressure, which can be used to prioritize locations for surveillance and intervention activities. To better understand invasion risk across aquatic landscapes, we developed a simulation model to estimate the likelihood of a waterbody becoming invaded with an AIS. The model included waterbodies connected via a multilayer network that included boater movements and hydrological connections. In a case study of Minnesota, we used zebra mussels (Dreissena polymorpha) and starry stonewort (Nitellopsis obtusa) as model species. We simulated the impacts of management scenarios developed by stakeholders and created a decision-support tool available through an online application provided as part of the AIS Explorer dashboard. Our baseline model revealed that 89% of new zebra mussel invasions and 84% of new starry stonewort invasions occurred through boater movements, establishing it as a primary pathway of spread and offering insights beyond risk estimates generated by traditional environmental suitability models alone. Our results highlight the critical role of interventions applied to boater movements to reduce AIS dispersal.

Modelo del riesgo de la invasión de especies acuáticas dispersadas por movimiento de botes y conexiones entre ríos Resumen Las especies acuáticas invasoras (EAI) son una de las principales amenazas para el funcionamiento de los ecosistemas acuáticos a nivel mundial. Una vez que una especie invasora ha sido introducida a una nueva región, muchos gobiernos desarrollan estrategias de manejo para disminuir la dispersión. Sin embargo, el manejo de las especies acuáticas invasoras en una nueva región se complica debido a las amplias áreas que necesitan protección y los recursos limitados. La heterogeneidad espacial de un riesgo de invasión es causada por la idoneidad ambiental y la presión de propágulo, que puede usarse para priorizar la ubicación de las actividades de vigilancia e intervención. Desarrollamos una simulación para estimar la probabilidad de que un cuerpo de agua sea invadido por EAI para tener un mejor entendimiento del riesgo de invasión en los paisajes acuáticos. El modelo incluyó cuencas conectadas a través de una red multicapa que incluía movimiento de botes y conexiones hidrológicas. Usamos como especies modelo a Dreissena polymorpha y a Nitellopsis obtusa en un estudio de caso en Minnesota. Simulamos el impacto de los escenarios de manejo desarrollado por los actores y creamos una herramienta de decisiones por medio de una aplicación en línea proporcionada como parte del tablero del Explorer de EAI. Nuestro modelo de línea base reveló que el 89% de las invasiones nuevas de D. polymorpha y el 84% de las de N. obtusa ocurrieron debido al movimiento de los botes, lo que lo estableció como una vía primaria de dispersión y nos proporcionó información más allá de las estimaciones de riesgo generadas por los modelos tradicionales de idoneidad ambiental. Nuestros resultados resaltan el papel crítico de las intervenciones aplicadas al movimiento de los botes para reducir la dispersión de especies acuáticas invasoras.

AIS explorer: Prioritization for watercraft inspections-A decision-support tool for aquatic invasive species management.

Invasions of aquatic invasive species have caused significant economic and ecological damage to global aquatic ecosystems. Once an invasive population has established in a new habitat, eradication can be financially and logistically impossible, motivating management strategies to rely heavily upon prevention measures to reduce the introduction and spread. To be productive, on-the-ground management of aquatic invasive species requires effective decision-making surrounding the allocation of limited resources. Watercraft inspections play an important role in managing aquatic invasive species by preventing the overland transport of invasive species between waterbodies and providing education to boaters. In this study, we developed and tested an interactive web-based decision-support tool, AIS Explorer: Prioritization for Watercraft Inspections, to guide AIS managers in developing efficient watercraft inspection plans. The decision-support tool is informed by a network-based algorithm that maximized the number of inspected watercraft that move from AIS infested to uninfested lakes within and between counties in Minnesota, USA. It was iteratively built with stakeholder feedback, including consultations with county managers, beta-testing of the web-based application, and workshops to educate and train end-users. The co-development and implementation of data-driven decision support tools demonstrate how interdisciplinary methods can be used to connect science and management to support decision-making. The AIS Explorer: Prioritization for Watercraft Inspections application makes optimized research outputs accessible in multiple dynamic forms that maintain pace with discovery of new infestations and local needs. In addition, the decision support tool has supported improved and closer communication between AIS managers and researchers on this topic.

PRAGMATIST: A tool to prioritize foot-and-mouth disease virus antigens held in vaccine banks.

Antigen banks have been established to supply foot-and-mouth disease virus (FMDV) vaccines at short notice to respond to incursions or upsurges in cases of FMDV infection. Multiple vaccine strains are needed to protect against specific FMDV lineages that circulate within six viral serotypes that are unevenly distributed across the world. The optimal selection of distinct antigens held in a bank must carefully balance the desire to cover these risks with the costs of purchasing and maintaining vaccine antigens. PRAGMATIST is a semi-quantitative FMD vaccine strain selection tool combining three strands of evidence: (1) estimates of the risk of incursion from specific areas (source area score); (2) estimates of the relative prevalence of FMD viral lineages in each specific area (lineage distribution score); and (3) effectiveness of each vaccine against specific FMDV lineages based on laboratory vaccine matching tests (vaccine coverage score). The output is a vaccine score, which identifies vaccine strains that best address the threats, and consequently which are the highest priority for inclusion in vaccine antigen banks. In this paper, data used to populate PRAGMATIST are described, including the results from expert elicitations regarding FMD risk and viral lineage circulation, while vaccine coverage data is provided from vaccine matching tests performed at the WRLFMD between 2011 and 2021 (n = 2,150). These data were tailored to working examples for three hypothetical vaccine antigen bank perspectives (Europe, North America, and Australia). The results highlight the variation in the vaccine antigens required for storage in these different regions, dependent on risk. While the tool outputs are largely robust to uncertainty in the input parameters, variation in vaccine coverage score had the most noticeable impact on the estimated risk covered by each vaccine, particularly for vaccines that provide substantial risk coverage across several lineages.

Corrigendum: Evidence in Practice - a Pilot Study Leveraging Companion Animal and Equine Health Data From Primary Care Veterinary Clinics in New Zealand.

[This corrects the article DOI: 10.3389/fvets.2016.00116.].

Creating symptom-based criteria for diagnostic testing: a case study based on a multivariate analysis of data collected during the first wave of the COVID-19 pandemic in New Zealand.

BACKGROUND: Diagnostic testing using PCR is a fundamental component of COVID-19 pandemic control. Criteria for determining who should be tested by PCR vary between countries, and ultimately depend on resource constraints and public health objectives. Decisions are often based on sets of symptoms in individuals presenting to health services, as well as demographic variables, such as age, and travel history. The objective of this study was to determine the sensitivity and specificity of sets of symptoms used for triaging individuals for confirmatory testing, with the aim of optimising public health decision making under different scenarios. METHODS: Data from the first wave of COVID-19 in New Zealand were analysed; comprising 1153 PCR-confirmed and 4750 symptomatic PCR negative individuals. Data were analysed using Multiple Correspondence Analysis (MCA), automated search algorithms, Bayesian Latent Class Analysis, Decision Tree Analysis and Random Forest (RF) machine learning. RESULTS: Clinical criteria used to guide who should be tested by PCR were based on a set of mostly respiratory symptoms: a new or worsening cough, sore throat, shortness of breath, coryza, anosmia, with or without fever. This set has relatively high sensitivity (> 90%) but low specificity (< 10%), using PCR as a quasi-gold standard. In contrast, a group of mostly non-respiratory symptoms, including weakness, muscle pain, joint pain, headache, anosmia and ageusia, explained more variance in the MCA and were associated with higher specificity, at the cost of reduced sensitivity. Using RF models, the incorporation of 15 common symptoms, age, sex and prioritised ethnicity provided algorithms that were both sensitive and specific (> 85% for both) for predicting PCR outcomes. CONCLUSIONS:  If predominantly respiratory symptoms are used for test-triaging,  a large proportion of the individuals being tested may not have COVID-19. This could overwhelm testing capacity and hinder attempts to trace and eliminate infection. Specificity can be increased using alternative rules based on sets of symptoms informed by multivariate analysis and automated search algorithms, albeit at the cost of sensitivity. Both sensitivity and specificity can be improved through machine learning algorithms, incorporating symptom and demographic data, and hence may provide an alternative approach to test-triaging that can be optimised according to prevailing conditions.

COVID-19 in New Zealand and the impact of the national response: a descriptive epidemiological study.

BACKGROUND: In early 2020, during the COVID-19 pandemic, New Zealand implemented graduated, risk-informed national COVID-19 suppression measures aimed at disease elimination. We investigated their impacts on the epidemiology of the first wave of COVID-19 in the country and response performance measures. METHODS: We did a descriptive epidemiological study of all laboratory-confirmed and probable cases of COVID-19 and all patients tested for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in New Zealand from Feb 2 to May 13, 2020, after which time community transmission ceased. We extracted data from the national notifiable diseases database and the national SARS-CoV-2 test results repository. Demographic features and disease outcomes, transmission patterns (source of infection, outbreaks, household transmission), time-to-event intervals, and testing coverage were described over five phases of the response, capturing different levels of non-pharmaceutical interventions. Risk factors for severe outcomes (hospitalisation or death) were examined with multivariable logistic regression and time-to-event intervals were analysed by fitting parametric distributions using maximum likelihood estimation. FINDINGS: 1503 cases were detected over the study period, including 95 (6·3%) hospital admissions and 22 (1·5%) COVID-19 deaths. The estimated case infection rate per million people per day peaked at 8·5 (95% CI 7·6-9·4) during the 10-day period of rapid response escalation, declining to 3·2 (2·8-3·7) in the start of lockdown and progressively thereafter. 1034 (69%) cases were imported or import related, tending to be younger adults, of European ethnicity, and of higher socioeconomic status. 702 (47%) cases were linked to 34 outbreaks. Severe outcomes were associated with locally acquired infection (crude odds ratio [OR] 2·32 [95% CI 1·40-3·82] compared with imported), older age (adjusted OR ranging from 2·72 [1·40-5·30] for 50-64 year olds to 8·25 [2·59-26·31] for people aged ≥80 years compared with 20-34 year olds), aged residential care residency (adjusted OR 3·86 [1·59-9·35]), and Pacific peoples (adjusted OR 2·76 [1·14-6·68]) and Asian (2·15 [1·10-4·20]) ethnicities relative to European or other. Times from illness onset to notification and isolation progressively decreased and testing increased over the study period, with few disparities and increasing coverage of females, Maori, Pacific peoples, and lower socioeconomic groups. INTERPRETATION: New Zealand's response resulted in low relative burden of disease, low levels of population disease disparities, and the initial achievement of COVID-19 elimination. FUNDING: Ministry of Business Innovation and Employment Strategic Scientific Investment Fund, and Ministry of Health, New Zealand.

Identifying emerging trends in antimicrobial resistance using Salmonella surveillance data in poultry in Spain.

Despite of controls and preventive measures implemented along the food chain, infection with non-typhoidal Salmonella (NTS) remains one of the major causes of foodborne disease worldwide. Poultry is considered one of the major sources of NTS. This has led to the implementation of monitoring and control programmes in many countries (including Spain) to ensure that in poultry flocks infection is kept to a minimum and to allow the identification and monitoring of circulating NTS strains and their antimicrobial resistance (AMR) phenotypes. Here, we investigated the information from the monitoring programme for AMR in Salmonella from poultry in Spain in 2011-2017 to assess the diversity in phenotypic resistance and to evaluate the programme's ability to detect multi-resistance patterns and emerging strains in the animal reservoir. Data on serotype and AMR to nine antimicrobials obtained from 3,047 NTS isolates from laying hens (n = 1,060), broiler (n = 765) and turkey (n = 1,222) recovered during controls performed by the official veterinary services and food business operators were analysed using univariate and multivariate methods in order to describe host and serotype-specific profiles. Diversity and prevalence of phenotypic resistance to all but one of the antimicrobials (colistin) were higher in NTS from broiler and turkey compared with laying hen isolates. Certain combinations of serotype and AMR pattern (resistotype) were particularly linked with certain hosts (e.g. susceptible Enteritidis with laying hens, multi-drug resistant (MDR) Derby in turkey, MDR Kentucky in turkey and broiler). The widespread presence of certain serotype-resistotype combinations in certain hosts/years suggested the possible expansion of MDR strains in the animal reservoir. This study demonstrates the usefulness of the analysis of data from monitoring programmes at the isolate level to detect emerging threats and suggests aspects that should be subjected to further research to identify the forces driving the expansion/dominance of certain strains in the food chain.

Genomic Analysis of Fluoroquinolone- and Tetracycline-Resistant Campylobacter jejuni Sequence Type 6964 in Humans and Poultry, New Zealand, 2014-2016.

In 2014, antimicrobial drug-resistant Campylobacter jejuni sequence type 6964 emerged contemporaneously in poultry from 3 supply companies in the North Island of New Zealand and as a major cause of campylobacteriosis in humans in New Zealand. This lineage, not previously identified in New Zealand, was resistant to tetracycline and fluoroquinolones. Genomic analysis revealed divergence into 2 major clades; both clades were associated with human infection, 1 with poultry companies A and B and the other with company C. Accessory genome evolution was associated with a plasmid, phage insertions, and natural transformation. We hypothesize that the tetO gene and a phage were inserted into the chromosome after conjugation, leaving a remnant plasmid that was lost from isolates from company C. The emergence and rapid spread of a resistant clone of C. jejuni in New Zealand, coupled with evolutionary change in the accessory genome, demonstrate the need for ongoing Campylobacter surveillance among poultry and humans.

Use of molecular and genomic data for disease surveillance in aquaculture: Towards improved evidence for decision making.

Diagnostic tools for the identification and confirmation of animal diseases have been evolving rapidly over the last decade, with diseases of aquatic animals being no exception. Hence, case definitions used in surveillance may now include molecular and genomic components and ultimately be based on the entire genome of a pathogen. While the opportunities brought on by this change in our ability to define and differentiate organisms are manifold, there are also challenges. These include the need to consider typing tool characteristics during sampling design, but also the re-thinking of diagnostic protocols and standards for the meaningful interpretation of the increasingly complex data presented to surveillance managers. These issues are illustrated for aquaculture using the example of multi-country surveillance of antimicrobial resistance of Aeromonas spp. strains isolated from rainbow trouts (Oncorhynchus mykiss) in Europe. In order to fully exploit the opportunities of molecular and genomic information, a multi-disciplinary approach is needed to develop harmonised diagnostic procedures and modified surveillance designs for aquaculture as well as for terrestrial animal production. This will require adjustments in the relevant standards applicable to assess food safety and trade risks.

SurF: an innovative framework in biosecurity and animal health surveillance evaluation.

Surveillance for biosecurity hazards is being conducted by the New Zealand Competent Authority, the Ministry for Primary Industries (MPI) to support New Zealand's biosecurity system. Surveillance evaluation should be an integral part of the surveillance life cycle, as it provides a means to identify and correct problems and to sustain and enhance the existing strengths of a surveillance system. The surveillance evaluation Framework (SurF) presented here was developed to provide a generic framework within which the MPI biosecurity surveillance portfolio, and all of its components, can be consistently assessed. SurF is an innovative, cross-sectoral effort that aims to provide a common umbrella for surveillance evaluation in the animal, plant, environment and aquatic sectors. It supports the conduct of the following four distinct components of an evaluation project: (i) motivation for the evaluation, (ii) scope of the evaluation, (iii) evaluation design and implementation and (iv) reporting and communication of evaluation outputs. Case studies, prepared by MPI subject matter experts, are included in the framework to guide users in their assessment. Three case studies were used in the development of SurF in order to assure practical utility and to confirm usability of SurF across all included sectors. It is anticipated that the structured approach and information provided by SurF will not only be of benefit to MPI but also to other New Zealand stakeholders. Although SurF was developed for internal use by MPI, it could be applied to any surveillance system in New Zealand or elsewhere.

epidemix-An interactive multi-model application for teaching and visualizing infectious disease transmission.

Mathematical models of disease transmission are used to improve our understanding of patterns of infection and to identify factors influencing them. During recent public and animal health crises, such as pandemic influenza, Ebola, Zika, foot-and-mouth disease, models have made important contributions in addressing policy questions, especially through the assessment of the trajectory and scale of outbreaks, and the evaluation of control interventions. However, their mathematical formulation means that they may appear as a "black box" to those without the appropriate mathematical background. This may lead to a negative perception of their utility for guiding policy, and generate expectations, which are not in line with what these models can deliver. It is therefore important for policymakers, as well as public health and animal health professionals and researchers who collaborate with modelers and use results generated by these models for policy development or research purpose, to understand the key concepts and assumptions underlying these models. The software application epidemix (http://shinyapps.rvc.ac.uk) presented here aims to make mathematical models of disease transmission accessible to a wider audience of users. By developing a visual interface for a suite of eight models, users can develop an understanding of the impact of various modelling assumptions - especially mixing patterns - on the trajectory of an epidemic and the impact of control interventions, without having to directly deal with the complexity of mathematical equations and programming languages. Models are compartmental or individual-based, deterministic or stochastic, and assume homogeneous or heterogeneous-mixing patterns (with the probability of transmission depending on the underlying structure of contact networks, or the spatial distribution of hosts). This application is intended to be used by scientists teaching mathematical modelling short courses to non-specialists - including policy makers, public and animal health professionals and students - and wishing to develop hands-on practicals illustrating key concepts of disease dynamics and control.

Shiga Toxin-Producing Escherichia coli O157 Shedding Dynamics in an Australian Beef Herd.

Shiga toxin-producing Escherichia coli (STEC) O157 is an important foodborne pathogen that can be transmitted to humans both directly and indirectly from the feces of beef cattle, its primary reservoir. Numerous studies have investigated the shedding dynamics of E. coli O157 by beef cattle; however, the spatiotemporal trends of shedding are still not well understood. Molecular tools can increase the resolution through the use of strain typing to explore transmission dynamics within and between herds and identify strain-specific characteristics that may influence pathogenicity and spread. Previously, the shedding dynamics and molecular diversity, through the use of multilocus variable number of tandem repeat analysis (MLVA) of STEC O157, were separately investigated in an Australian beef herd over a 9-month study period. Variation in shedding was observed over time, and 33 MLVA types were identified. The study presented here combines the two datasets previously published with an aim to clarify the relationship between epidemiological variables and strain types. Three major genetic clusters (GCs) were identified that were significantly associated with the location of the cattle in different paddocks. No significant association between GCs and individual cow was observed. Results from this molecular epidemiological study provide evidence for herd-level clonal replacement over time that may have been triggered by movement to a new paddock. In conclusion, this study has provided further insight into STEC O157 shedding dynamics and pathogen transmission. Knowledge gaps remain regarding the relationship of strain types and the shedding dynamics of STEC O157 by beef cattle that could be further clarified through the use of whole-genome sequencing.

A review of methods used for studying the molecular epidemiology of Brachyspira hyodysenteriae.

Brachyspira (B.) spp. are intestinal spirochaetes isolated from pigs, other mammals, birds and humans. In pigs, seven Brachyspira spp. have been described, i.e. B. hyodysenteriae, B. pilosicoli, B. intermedia, B. murdochii, B. innocens, B. suanatina and B. hampsonii. Brachyspira hyodysenteriae is especially relevant in pigs as it causes swine dysentery and hence considerable economic losses to the pig industry. Furthermore, reduced susceptibility of B. hyodysenteriae to antimicrobials is of increasing concern. The epidemiology of B. hyodysenteriae infections is only partially understood, but different methods for detection, identification and typing have supported recent improvements in knowledge and understanding. In the last years, molecular methods have been increasingly used. Molecular epidemiology links molecular biology with epidemiology, offering unique opportunities to advance the study of diseases. This review is based on papers published in the field of epidemiology and molecular epidemiology of B. hyodysenteriae in pigs. Electronic databases were screened for potentially relevant papers using title and abstract and finally, Barcellos et al. papers were systemically selected and assessed. The review summarises briefly the current knowledge on B. hyodysenteriae epidemiology and elaborates on molecular typing techniques available. Results of the studies are compared and gaps in the knowledge are addressed. Finally, potential areas for future research are proposed.

A Review of Quantitative Tools Used to Assess the Epidemiology of Porcine Reproductive and Respiratory Syndrome in U.S. Swine Farms Using Dr. Morrison's Swine Health Monitoring Program Data.

Porcine reproductive and respiratory syndrome (PRRS) causes far-reaching financial losses to infected countries and regions, including the U.S. The Dr. Morrison's Swine Health Monitoring Program (MSHMP) is a voluntary initiative in which producers and veterinarians share sow farm PRRS status weekly to contribute to the understanding, in quantitative terms, of PRRS epidemiological dynamics and, ultimately, to support its control in the U.S. Here, we offer a review of a variety of analytic tools that were applied to MSHMP data to assess disease dynamics in quantitative terms to support the decision-making process for veterinarians and producers. Use of those methods has helped the U.S. swine industry to quantify the cyclical patterns of PRRS, to describe the impact that emerging pathogens has had on that pattern, to identify the nature and extent at which environmental factors (e.g., precipitation or land cover) influence PRRS risk, to identify PRRS virus emerging strains, and to assess the influence that voluntary reporting has on disease control. Results from the numerous studies reviewed here provide important insights into PRRS epidemiology that help to create the foundations for a near real-time prediction of disease risk, and, ultimately, will contribute to support the prevention and control of, arguably, one of the most devastating diseases affecting the North American swine industry. The review also demonstrates how different approaches to analyze and visualize the data may help to add value to the routine collection of surveillance data and support infectious animal disease control.

Serotypes and Antimicrobial Resistance in Salmonella enterica Recovered from Clinical Samples from Cattle and Swine in Minnesota, 2006 to 2015.

Salmonellosis remains one of the leading causes of foodborne disease worldwide despite preventive efforts at various stages of the food production chain. The emergence of multi-drug resistant (MDR) non-typhoidal Salmonella enterica represents an additional challenge for public health authorities. Food animals are considered a major reservoir and potential source of foodborne salmonellosis; thus, monitoring of Salmonella strains in livestock may help to detect emergence of new serotypes/MDR phenotypes and to gain a better understanding of Salmonella epidemiology. For this reason, we analyzed trends over a nine-year period in serotypes, and antimicrobial resistance, of Salmonella isolates recovered at the Minnesota Veterinary Diagnostic Laboratory (MVDL) from swine (n = 2,537) and cattle (n = 1,028) samples. Prevalence of predominant serotypes changed over time; in swine, S. Typhimurium and S. Derby decreased and S. Agona and S. 4,5,12:i:- increased throughout the study period. In cattle, S. Dublin, S. Montevideo and S. Cerro increased and S. Muenster became less frequent. Median minimum inhibitory concentration (MIC) values and proportion of antibiotic resistant isolates were higher for those recovered from swine compared with cattle, and were particularly high for certain antibiotic-serotype combinations. The proportion of resistant swine isolates was also higher than observed in the NARMS data, probably due to the different cohort of animals represented in each dataset. Results provide insight into the dynamics of antimicrobial resistant Salmonella in livestock in Minnesota, and can help to monitor emerging trends in antimicrobial resistance.

Evidence in Practice - A Pilot Study Leveraging Companion Animal and Equine Health Data from Primary Care Veterinary Clinics in New Zealand.

Veterinary practitioners have extensive knowledge of animal health from their day-to-day observations of clinical patients. There have been several recent initiatives to capture these data from electronic medical records for use in national surveillance systems and clinical research. In response, an approach to surveillance has been evolving that leverages existing computerized veterinary practice management systems to capture animal health data recorded by veterinarians. Work in the United Kingdom within the VetCompass program utilizes routinely recorded clinical data with the addition of further standardized fields. The current study describes a prototype system that was developed based on this approach. In a 4-week pilot study in New Zealand, clinical data on presentation reasons and diagnoses from a total of 344 patient consults were extracted from two veterinary clinics into a dedicated database and analyzed at the population level. New Zealand companion animal and equine veterinary practitioners were engaged to test the feasibility of this national practice-based health information and data system. Strategies to ensure continued engagement and submission of quality data by participating veterinarians were identified, as were important considerations for transitioning the pilot program to a sustainable large-scale and multi-species surveillance system that has the capacity to securely manage big data. The results further emphasized the need for a high degree of usability and smart interface design to make such a system work effectively in practice. The geospatial integration of data from multiple clinical practices into a common operating picture can be used to establish the baseline incidence of disease in New Zealand companion animal and equine populations, detect unusual trends that may indicate an emerging disease threat or welfare issue, improve the management of endemic and exotic infectious diseases, and support research activities. This pilot project is an important step toward developing a national surveillance system for companion animals and equines that moves beyond emerging infectious disease detection to provide important animal health information that can be used by a wide range of stakeholder groups, including participating veterinary practices.

Timely Reporting and Interactive Visualization of Animal Health and Slaughterhouse Surveillance Data in Switzerland.

The reporting of outputs from health surveillance systems should be done in a near real-time and interactive manner in order to provide decision makers with powerful means to identify, assess, and manage health hazards as early and efficiently as possible. While this is currently rarely the case in veterinary public health surveillance, reporting tools do exist for the visual exploration and interactive interrogation of health data. In this work, we used tools freely available from the Google Maps and Charts library to develop a web application reporting health-related data derived from slaughterhouse surveillance and from a newly established web-based equine surveillance system in Switzerland. Both sets of tools allowed entry-level usage without or with minimal programing skills while being flexible enough to cater for more complex scenarios for users with greater programing skills. In particular, interfaces linking statistical softwares and Google tools provide additional analytical functionality (such as algorithms for the detection of unusually high case occurrences) for inclusion in the reporting process. We show that such powerful approaches could improve timely dissemination and communication of technical information to decision makers and other stakeholders and could foster the early-warning capacity of animal health surveillance systems.

Preliminary molecular epidemiological investigation of hepatitis E virus sequences from Québec, Canada.

Our study objective was to describe the Canadian Hepatitis E virus (HEV) sequences currently cataloged in GenBank from three populations: commercially raised pigs, retail pork, and locally acquired Hepatitis E cases, and to interpret the molecular evidence they provide. We searched the GenBank for any/all Canadian HEV sequences from these populations, and identified highly similar matches using the Basic Local Alignment Search Tool (BLAST) algorithm, studying sequences of the partial ORF2 gene. We validated the findings made using Multiple Sequence Comparison by Log-Expectation (MUSCLE) and Clustal 2 programs for multiple sequence alignments, as inputs to estimate dendrograms using both neighbour-joining and Unweighted Pair Group Method with Arithmetic Mean (UPGMA) methods. The GenBank search yielded 47 sequences collected from pigs: 32 sequences from two to four month old commercial pigs in Québec, one from three to four month old pigs at a research station in Ontario, one from two month old pigs in a commercial Saskatchewan herd, and 13 collected from finisher pigs in a national survey. Additionally, 14 sequences were collected from a national survey of Canadian retail pork livers, and seven sequences from two Canadian pediatric patients with locally acquired Hepatitis E, both from the province of Québec. All sequences belonged to genotype 3. Eight of the 14 sequences from retail pork livers had human-derived sequences in their top ten BLAST matches; six did not. Those eight sequences having close human BLAST matches clustered within a dendrogram, as did those with no close human BLAST matches. Human sequences with close matches to the eight retail sequences included both of the Québec Hepatitis E cases, as well as sequences from Japanese Hepatitis E cases, and Japanese blood donors. Seven of the eight HEV sequences from retail liver with close human BLAST matches originated in Québec. Kulldorff's spatial scan statistic showed a significant (P<0.05) spatial cluster of these sequences, but not of the overall dataset of 12 HEV sequences collected from Québec retail livers. All seven retail liver sequences with close human matches were processed in-store. We conclude that some Canadian sequences of HEV collected from pigs/pork are more closely related to human sequences than others, and hypothesize that detection of some HEV sequences recovered from Canadian retail pork livers may be associated with exposure to human shedding. More research needs to be conducted at the processing level to help understand the molecular epidemiology of HEV in Canadian retail pork.

Building a foundation for 'One Health': an education strategy for enhancing and sustaining national and regional capacity in endemic and emerging zoonotic disease management.

The rapid global spread of diseases such as SARS, H5N1, and H1N1 influenza has emphasized the pressing need for trans-disciplinary collaboration and cross-border action, and has also exposed a serious deficit of capacity and coordination in dealing effectively with emerging disease threats. The need for capacity development is particularly acute in the developing world, which is the least well-equipped to respond adequately. Such capacity development can be achieved through education and the implementation of applied 'One Health' activities. This chapter describes the establishment of a 'One Health' capacity development program in South Asia, consisting of two phases. The first phase provides Masters level training for public health doctors and veterinarians, with a focus on epidemiology, and disease control. The second phase reinforces the postgraduate training by establishing a sustainable framework for the implementation of collaborative 'One Health' activities such as the development of multidisciplinary professional networks, implementation of applied zoonotic disease investigation projects, and support for continuing professional development. The objectives are to provide individual skills required to strengthen capacity; to develop an appreciation of the cross-cutting issues which affect human and animal health, set within an institutional context; and to facilitate the development of regional professional networks which will be instrumental in implementing 'One Health' activities.