Inferring source attribution from a multi-year multi-source dataset of Salmonella in Minnesota

Salmonella enterica is a global health concern because of its widespread association with foodborne illness. Bayesian models have been developed to attribute the burden of human salmonellosis to specific sources with the ultimate objective of prioritizing intervention strategies. Important considerations of source attribution models include the evaluation of the quality of input data, assessment of whether attribution results logically reflect the data trends and identification of patterns within the data that might explain the detailed contribution of different sources to the disease burden. Here, more than 12,000 non-typhoidal Salmonella isolates from human, bovine, porcine, chicken and turkey sources that originated in Minnesota were analysed. A modified Bayesian source attribution model (available in a dedicated R package), accounting for non-sampled sources of infection, attributed 4,672 human cases to sources assessed here. Most (60%) cases were attributed to chicken, although there was a spike in cases attributed to a non-sampled source in the second half of the study period. Molecular epidemiological analysis methods were used to supplement risk modelling, and a visual attribution application was developed to facilitate data exploration and comprehension of the large multiyear data set assessed here. A large amount of within-source diversity and low similarity between sources was observed, and visual exploration of data provided clues into variations driving the attribution modelling results. Results from this pillared approach provided first attribution estimates for Salmonella in Minnesota and offer an understanding of current data gaps as well as key pathogen population features, such as serotype frequency, similarity and diversity across the sources. Results here will be used to inform policy and management strategies ultimately intended to prevent and control Salmonella infection in the state

Marked Campylobacteriosis Decline after Interventions Aimed at Poultry, New Zealand

A population-level food safety response successfully reduced disease incidence

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 ( = 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

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

Integrating Survey and Molecular Approaches to Better Understand Wildlife Disease Ecology

Infectious wildlife diseases have enormous global impacts, leading to human pandemics, global biodiversity declines and socio-economic hardship. Understanding how infection persists and is transmitted in wildlife is critical for managing diseases, but our understanding is limited. Our study aim was to better understand how infectious disease persists in wildlife populations by integrating genetics, ecology and epidemiology approaches. Specifically, we aimed to determine whether environmental or host factors were stronger drivers of Salmonella persistence or transmission within a remote and isolated wild pig (Sus scrofa) population. We determined the Salmonella infection status of wild pigs. Salmonella isolates were genotyped and a range of data was collected on putative risk factors for Salmonella transmission. We a priori identified several plausible biological hypotheses for Salmonella prevalence (cross sectional study design) versus transmission (molecular case series study design) and fit the data to these models. There were 543 wild pig Salmonella observations, sampled at 93 unique locations. Salmonella prevalence was 41% (95% confidence interval [CI]: 37-45%). The median Salmonella DICE coefficient (or Salmonella genetic similarity) was 52% (interquartile range [IQR]: 42-62%). Using the traditional cross sectional prevalence study design, the only supported model was based on the hypothesis that abundance of available ecological resources determines Salmonella prevalence in wild pigs. In the molecular study design, spatial proximity and herd membership as well as some individual risk factors (sex, condition score and relative density) determined transmission between pigs. Traditional cross sectional surveys and molecular epidemiological approaches are complementary and together can enhance understanding of disease ecology: abundance of ecological resources critical for wildlife influences Salmonella prevalence, whereas Salmonella transmission is driven by local spatial, social, density and individual factors, rather than resources. This enhanced understanding has implications for the control of diseases in wildlife populations. Attempts to manage wildlife disease using simplistic density approaches do not acknowledge the complexity of disease ecology

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 programming skills while being flexible enough to cater for more complex scenarios for users with greater programming 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

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

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

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

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

volumes: illustrations; 22-28 c