The performance of approximations of farm contiguity compared to contiguity defined using detailed geographical information in two sample areas in Scotland: implications for foot-and-mouth disease modelling

A discrete-time survival model for porcine epidemic diarrhoea virus

Since the arrival of porcine epidemic diarrhea virus (PEDV) in the United States in 2013, elimination and control programmes have had partial success. The dynamics of its spread are hard to quantify, though previous work has shown that local transmission and the transfer of pigs within production systems are most associated with the spread of PEDV. Our work relies on the history of PEDV infections in a region of the southeastern United States. This infection data is complemented by farm-level features and extensive industry data on the movement of both pigs and vehicles. We implement a discrete-time survival model and evaluate different approaches to modelling the local-transmission and network effects. We find strong evidence in that the local-transmission and pig-movement effects are associated with the spread of PEDV, even while controlling for seasonality, farm-level features and the possible spread of disease by vehicles. Our fully Bayesian model permits full uncertainty quantification of these effects. Our farm-level out-of-sample predictions have a receiver-operating characteristic area under the curve (AUC) of 0.779 and a precision-recall AUC of 0.097. The quantification of these effects in a comprehensive model allows stakeholders to make more informed decisions about disease prevention efforts.

Challenges and opportunities for using national animal datasets to support foot-and-mouth disease control

National level databases of animal numbers, locations and movements provide the essential foundations for disease preparedness, outbreak investigations and control activities. These activities are particularly important for managing and mitigating the risks of high-impact transboundary animal disease outbreaks such as foot-and-mouth disease (FMD), which can significantly affect international trade access and domestic food security. In countries where livestock production systems are heavily subsidized by the government, producers are often required to provide detailed animal movement and demographic data as a condition of business. In the remaining countries, it can be difficult to maintain these types of databases and impossible to estimate the extent of missing or inaccurate information due to the absence of gold standard datasets for comparison. Consequently, competent authorities are often required to make decisions about disease preparedness and control based on available data, which may result in suboptimal outcomes for their livestock industries. It is important to understand the limitations of poor data quality as well as the range of methods that have been developed to compensate in both disease-free and endemic situations. Using FMD as a case example, this review first discusses the different activities that competent authorities use farm-level animal population data for to support (1) preparedness activities in disease-free countries, (2) response activities during an acute outbreak in a disease-free country, and (3) eradication and control activities in an endemic country. We then discuss (4) data requirements needed to support epidemiological investigations, surveillance, and disease spread modelling both in disease-free and endemic countries.

Does Size Matter to Models? Exploring the Effect of Herd Size on Outputs of a Herd-Level Disease Spread Simulator

Disease spread modeling is widely used by veterinary authorities to predict the impact of emergency animal disease outbreaks in livestock and to evaluate the cost-effectiveness of different management interventions. Such models require knowledge of basic disease epidemiology as well as information about the population of animals at risk. Essential demographic information includes the production system, animal numbers, and their spatial locations yet many countries with significant livestock industries do not have publically available and accurate animal population information at the farm level that can be used in these models. The impact of inaccuracies in data on model outputs and the decisions based on these outputs is seldom discussed. In this analysis, we used the Australian Animal Disease model to simulate the spread of foot-and-mouth disease seeded into high-risk herds in six different farming regions in New Zealand. We used three different susceptible animal population datasets: (1) a gold standard dataset comprising known herd sizes, (2) a dataset where herd size was simulated from a beta-pert distribution for each herd production type, and (3) a dataset where herd size was simplified to the median herd size for each herd production type. We analyzed the model outputs to compare (i) the extent of disease spread, (ii) the length of the outbreaks, and (iii) the possible impacts on decisions made for simulated outbreaks in different regions. Model outputs using the different datasets showed statistically significant differences, which could have serious implications for decision making by a competent authority. Outbreak duration, number of infected properties, and vaccine doses used during the outbreak were all significantly smaller for the gold standard dataset when compared with the median herd size dataset. Initial outbreak location and disease control strategy also significantly influenced the duration of the outbreak and number of infected premises. The study findings demonstrate the importance of having accurate national-level population datasets to ensure effective decisions are made before and during disease outbreaks, reducing the damage and cost.

Vaccinia Virus in Blood Samples of Humans, Domestic and Wild Mammals in Brazil

Outbreaks of Vaccinia virus (VACV) affecting cattle and humans have been reported in Brazil in the last 15 years, but the origin of outbreaks remains unknown. Although VACV DNA have been already detected in mice (Mus musculus), opossums (Didelphis albiventris) and dogs during VACV zoonotic outbreaks, no transmission to cattle or humans from any of these were reported during Brazilian outbreaks. In this work, we assessed the PCR positivity to VACV in blood samples of cows and other domestic mammals, wild rodents and other wild mammals, and humans from areas with or without VACV infection reports. Our results show the detection of VACV DNA in blood samples of cows, horse and opossums, raising important questions about VACV spread.

Analysis of bovine viral diarrhoea virus: Biobank and sequence database to support eradication in Scotland

Samples from bovine viral diarrhoea virus (BVDV)-positive cattle were gathered by Scottish diagnostic laboratories and used to produce a Biobank of samples with associated location and identification data in support of the Scottish BVDV eradication scheme. The samples were subject to direct amplification and sequencing of the 5'-untranslated region (5'-UTR) to define the viral types and subtypes present. From 2693 samples collected prior to 2016, approximately 2300 sequences were obtained, representing 8 BVDV type 1 subtypes. No BVDV type 2 samples were detected. The samples came from all regions of the UK but 66 per cent were from Scotland. Analysis of the sequences showed great diversity in the 5'-UTR, with 1206 different sequences. Many samples carried virus with identical 5'-UTR sequences; often from single locations, but there were also examples of the same sequence being obtained from samples at several different locations. This work provides a resource that can be used to analyse the movement of BVDV strains both within Scotland and between Scotland and other nations, particularly in the latter stages of the Scottish eradication programme, and so inform the advice available to both livestock keepers and policymakers.

E. coli O157 on Scottish cattle farms: evidence of local spread and persistence using repeat cross-sectional data

Background

Escherichia coli (E. coli) O157 is a virulent zoonotic strain of enterohaemorrhagic E. coli. In Scotland (1998-2008) the annual reported rate of human infection is 4.4 per 100,000 population which is consistently higher than other regions of the UK and abroad. Cattle are the primary reservoir. Thus understanding infection dynamics in cattle is paramount to reducing human infections.

A large database was created for farms sampled in two cross-sectional surveys carried out in Scotland (1998 - 2004). A statistical model was generated to identify risk factors for the presence of E. coli O157 on farms. Specific hypotheses were tested regarding the presence of E. coli O157 on local farms and the farms previous status. Pulsed-field gel electrophoresis (PFGE) profiles were further examined to ascertain whether local spread or persistence of strains could be inferred.

Results

The presence of an E. coli O157 positive local farm (average distance: 5.96km) in the Highlands, North East and South West, farm size and the number of cattle moved onto the farm 8 weeks prior to sampling were significant risk factors for the presence of E. coli O157 on farms. Previous status of a farm was not a significant predictor of current status (p = 0.398). Farms within the same sampling cluster were significantly more likely to be the same PFGE type (p < 0.001), implicating spread of strains between local farms. Isolates with identical PFGE types were observed to persist across the two surveys, including 3 that were identified on the same farm, suggesting an environmental reservoir. PFGE types that were persistent were more likely to have been observed in human clinical infections in Scotland (p < 0.001) from the same time frame.

Conclusions

The results of this study demonstrate the spread of E. coli O157 between local farms and highlight the potential link between persistent cattle strains and human clinical infections in Scotland. This novel insight into the epidemiology of Scottish E. coli O157 paves the way for future research into the mechanisms of transmission which should help with the design of control measures to reduce E. coli O157 from livestock-related sources.