A new bovine tuberculosis model for England and Wales (BoTMEW) to simulate epidemiology, surveillance and control.

BACKGROUND: Bovine tuberculosis (bTB) is a zoonotic disease of cattle caused by Mycobacterium bovis, widespread in England and Wales. It has high incidence towards the South West of England and Wales, with much lower incidence to the East and North. A stochastic simulation model was developed to simulate M. bovis transmission among cattle, transfer by cattle movements and transmission from environmental reservoirs (often wildlife and especially badgers). It distinguishes five surveillance streams, including herd tests, pre-movement testing and slaughter surveillance. The model thereby simulates interventions in bTB surveillance and control, and generates outputs directly comparable to detailed disease records. An anonymized version of the executable model with its input data has been released. The model was fitted to cattle bTB records for 2008-2010 in a cross-sectional comparison, and its projection was compared with records from 2010 to 2016 for validation. RESULTS: The fitted model explained over 99% of the variation among numbers of breakdowns in four defined regions and surveillance streams in 2010. It classified 7800 (95% confidence interval c. 5500 - 14,000) holdings within high incidence regions as exposed to infectious environmental reservoirs, out of over 31,000 cattle holdings identified as potentially exposed to such sources. The model was consistent with previous estimates of low M. bovis transmission rate among cattle, but cattle to cattle transmission was clearly required to generate the number of cattle cases observed. When projected to 2016, the model as fitted to 2010 continued to match the distribution of bTB among counties, although it was notable that the actual distribution of bTB in 2010 was itself a close match for its distribution in 2016. CONCLUSIONS: The close model fit demonstrated that cattle movements could generate breakdowns as observed in low incidence regions, if persistent environmental reservoirs such as wildlife maintained infection levels in the high incidence regions. The model suggests that environmental reservoirs may be a challenge for control, because, although many holdings are exposed to infection from wildlife or the environment, they are a minority of holdings. Large impacts on disease in wildlife will be required to avoid each individual transmission event to cattle.

A visual representation of cattle movement in Ireland during 2016.

The aim of this study was to create a clear visual representation of the live movements of cattle in the Republic of Ireland over the course of the year 2016. The animation created can be viewed online: https://youtu.be/PTCdPMnenBw This animation was created to be a communication tool to enable stakeholders to appreciate the extent of high risk cattle movements (farm to farm, farm to market to farm) in the Republic of Ireland and to highlight the potential role that these movements may play in the spread of infectious diseases of cattle in Ireland from one farm to another.

Examining perceived risk to bovine tuberculosis through factorial survey to inform policymaking for zoonotic diseases control and surveillance.

Prevention and control of infectious diseases in livestock is dependent upon perceived risk and susceptibility, including the prevention of between-herd transmission of bovine tuberculosis through introductions of cattle to susceptible herds. To examine how perceived risk and susceptibility can help to inform policymaking in disease surveillance and control, we used factorial surveys to profile risk perceptions of cattle producers. We found that government indemnity and slaughtering policy did not impact the cattle purchasing behavior of producers who responded to our survey, but rather through other attributes such as the reliability or reputation of the seller. In addition, we identified significant production type and gender differences in purchasing behavior and risk perception. Finally, clustering analysis revealed a group of high-risk respondents characterized as experienced and very dedicated owners of established medium to large size herds. With the increasing availability of business data, assessment of producer's behavior, personalities and attitudes allows policymakers to understand the needs of cattle producers and develop tailored programs that will improve producer cooperation with government agencies.

Quantifying intraherd cattle movement metrics: Implications for disease transmission risk.

There are a paucity of data quantifying on-farm management practices such as the frequency of intraherd cattle movements, use of consolidated or spatially fragmented grazing pastures, and duration of time cattle spend at grass with respect to biosecurity and disease transmission. Such movement dynamics are important when attempting to understand the maintenance of chronic infectious disease, such as bovine tuberculosis (bTB). We captured empirical data on daily cattle movements for a sample of eighteen farms throughout one complete grazing season (n = 18,988 grazing days) and assessed these attributes in relation to herd bTB risk. Dairy herds were stocked at significantly higher densities compared to beef production systems (6.6 animals/ha, 95 % confidence intervals (CI) 6.5-6.7 and 4.1 animals/ha, 95 %CI 4.1 - 4.1 respectively, p < 0.001). Most notably milking cows, were grazed at higher densities than other life stages (e.g. calves, heifers and bullocks) (p < 0.001) and experienced four times the number of movements between pastures. Beef cattle were more likely to be grazed across multiple (rather than single) fields (p < 0.001), with greater time spent on fragmented land away from the main/home farm (p < 0.001). None of the farm or herd attributes analysed (e.g. stocking density, frequency of movement, movement distances or land fragmentation) were associated with herd bovine tuberculosis (bTB) breakdowns during this study. However, there was a weak positive association between bTB breakdowns during the 3 years prior to the study and cattle movement distances (p = 0.05) and time spent on fragmented land (p = 0.08). After a bTB breakdown occurs, restrictions on animals moving out of these herds are implemented to control disease spread, yet we argue that more attention is needed on the role of intraherd grazing patterns in modelling disease transmission risk between herds.

Implications of Cattle Trade for the Spread and Control of Infectious Diseases in Slovenia.

The objectives of this study were to gain insight into the structure of the cattle trade network in Slovenia and to evaluate the potential for infectious disease spread through movements. The study considered cattle movements between different types of premises that occurred between August 1, 2011 and July 31, 2016 with the exclusion of the movements to the end nodes (e.g., slaughterhouses). In the first part, we performed a static network analysis on monthly and yearly snapshots of the network. These time scales reflect our interest in slowly spreading pathogens; namely Mycobacterium avium subsp. paratuberculosis (MAP), which causes paratuberculosis, a worldwide economically important disease. The results showed consistency in the network measures over time; nevertheless, it was evident that year to year contacts between premises were changing. The importance of individual premises for the network connectedness was highly heterogeneous and the most influential premises in the network were collection centers, mountain pastures, and pastures. Compared to random node removal, targeted removal informed by ranking based on local network measures from previous years was substantially more effective in network disassociation. Inclusion of the latest movement data improved the results. In the second part, we simulated disease spread using a Susceptible-Infectious (SI) model on the temporal network. The SI model was based on the empirically estimated true prevalence of paratuberculosis in Slovenia and four scenarios for probabilities of transmission. Different probabilities were realized by the generation of new networks with the corresponding proportion of contacts which were randomly selected from the original network. These diluted networks served as substrates for simulation of MAP spread. The probability of transmission had a significant influence on the velocity of disease spread through the network. The peaks in daily incidence rates of infected herds were observed at the end of the grazing period. Our results suggest that network analysis may provide support in the optimization of paratuberculosis surveillance and intervention in Slovenia. The approach of simulating disease spread on a diluted network may also be used to model other transmission pathways between herds.

Economic aspects of foot and mouth disease in Bolivia.

The paper presents results from two economic analyses of foot and mouth disease (FMD) in Bolivia. Both recommended a programme to eradicate the disease, but one reported a negative economic return while the later study found a positive and robust return. To investigate the reasons for these differences the paper presents information on cattle movement and how this relates to the epidemiological situation of FMD in Bolivia. This analysis identifies two important trade routes: southern and central cattle trade routes and two FMD endemic areas: the humid tropical areas of the Departments of the Beni and Santa Cruz, and the semi-arid subtropical area to the south east of the country known as the Bolivian Chaco. The farm-level incentives to control FMD in the endemic areas, where cattle are kept in extensive systems, are negative and the main losses caused by the disease occur four to six years after an outbreak. Given this situation it is suggested that resources being used to eradicate the disease in Bolivia should be concentrated in these endemic areas where convincing cattle owners of the need to control FMD is particularly difficult. It is also suggested that the eradication programme should coordinate its activities with neighbouring countries.

Modeling cost-effectiveness of risk-based bovine tuberculosis surveillance in Minnesota.

In the United States, slaughter surveillance combined with other measures has effectively maintained a very low prevalence of bovine tuberculosis (bTB). However, bTB continues to be sporadically detected, causing substantial economic burden to the government and cattle producers. To detect the infection earlier and reduce sudden economic losses, additional risk-based surveillance of live animals might be more cost-effective than slaughter surveillance alone to detect and prevent bTB infection. The objective of this study was to evaluate alternative risk-based surveillance strategies targeting high-risk herds to complement slaughter surveillance in a region with very low bTB prevalence. We developed an integrated within- and between-herd bTB transmission model with simulated premises-level cattle movements among beef and dairy herds in Minnesota for 10 years. We constructed ten risk-based surveillance strategies for beef herds and dairy herds, and predicted the epidemiological outcomes and costs for each strategy in combination with slaughter surveillance. Our models showed that slaughter surveillance alone resulted in low risk of between-herd transmission with typically small outbreak sizes, and also cost less compared to alternative risk-based surveillance measures. However, risk-based surveillance strategies could reduce the time to detect infection and the time to reach disease freedom by up to 9 months. At a higher initial prevalence, alternative risk-based surveillance could reduce the number of infected herds and shorten the time to disease freedom by almost 3 years (34-35 months). Our findings suggest that risk-based surveillance could detect infection more quickly and allow affected regions to reach disease freedom faster. If the bTB status of the affected regions changes after an outbreak happens, the reduced time to disease freedom could reduce the economic impact on the affected region.

Cattle movement patterns in Australia: an analysis of the NLIS database 2008-2012.

OBJECTIVE: To identify patterns of cattle movement that could influence disease spread in the Australian cattle population. METHODS: Records from the National Livestock Identification System database for the period January 2008 to December 2012 were accessed and analysed. Postcodes were used to allocate each individual property to one of 12 livestock production regions. National movement patterns and the characteristics of each livestock production region were quantified in terms of the number of consignments and animals moved, and seasonality of movements. RESULTS: The majority of cattle movements remained within a single livestock production region, while those that did not, usually remained within the same state or territory. Producers were the most common source of cattle, and abattoirs and other producers the most common destinations, with approximately 40% of animals moving via a saleyard. The northern regions generally moved larger consignments than the southern regions and were less connected to other regions. The eastern and south-eastern regions were very well connected by cattle movements. Seasonal patterns were seen for some regions, particularly the northern regions where weather patterns strongly influence the ability of producers to muster and transport stock. CONCLUSIONS: The movement patterns observed provide quantitative support for previous information based on surveys and expert opinion, and capture more of the variability in Australian cattle production. This information may assist with management of animal disease risks, in particular exotic diseases, and in planning surveillance programs.

Controlling infectious disease through the targeted manipulation of contact network structure.

Individuals in human and animal populations are linked through dynamic contact networks with characteristic structural features that drive the epidemiology of directly transmissible infectious diseases. Using animal movement data from the British cattle industry as an example, this analysis explores whether disease dynamics can be altered by placing targeted restrictions on contact formation to reconfigure network topology. This was accomplished using a simple network generation algorithm that combined configuration wiring with stochastic block modelling techniques to preserve the weighted in- and out-degree of individual nodes (farms) as well as key demographic characteristics of the individual network connections (movement date, livestock market, and animal production type). We then tested a control strategy based on introducing additional constraints into the network generation algorithm to prevent farms with a high in-degree from selling cattle to farms with a high out-degree as these particular network connections are predicted to have a disproportionately strong role in spreading disease. Results from simple dynamic disease simulation models predicted significantly lower endemic disease prevalences on the trade restricted networks compared to the baseline generated networks. As expected, the relative magnitude of the predicted changes in endemic prevalence was greater for diseases with short infectious periods and low transmission probabilities. Overall, our study findings demonstrate that there is significant potential for controlling multiple infectious diseases simultaneously by manipulating networks to have more epidemiologically favourable topological configurations. Further research is needed to determine whether the economic and social benefits of controlling disease can justify the costs of restricting contact formation.

From network analysis to risk analysis--An approach to risk-based surveillance for bovine tuberculosis in Minnesota, US.

Bovine tuberculosis (bTB) was first detected in 2005 in cattle in northwestern Minnesota (MN) through slaughter surveillance. By the end of 2008, 12 cattle herds were infected with bTB, and the main cause for infection was determined to be the movement of infected animals between herds. Bovine tuberculosis was contained in a smaller area in northwestern Minnesota classified as modified accredited (MA), corresponding to a prevalence inferior to 0.1% in cattle. From January 2008 to 2011, all cattle movements within the bTB MA were recorded electronically. The primary objectives of this study were to characterize cattle movements within this region and identify cattle herds with higher risk of bTB introduction based on network parameters and known risk factors from the published literature. During the period that data was collected, 57,460 cattle were moved in 3762 movements corresponding to permits issued to 682 premises, mostly representing private farms, sale yards, slaughter facilities and county or state fairs. Although sale yards represented less than 2% of the premises (nodes), 60% of the movements were to or from a sale yard. The network showed an overall density of 0.4%, a clustering coefficient of 14.6% and a betweenness centralization index of 12.7%, reflecting the low connectivity of this cattle network. The degree distribution showed that 20% of nodes performed 90% of the movements. Farms were ranked based on the total risk score and divided into high, medium, and low risk groups based on the score and its variability. The higher risk group included 14% (n=50) of the farms, corresponding to 80% of the cumulative risk for the farms in the bTB area. This analysis provides a baseline description about the contact structure of cattle movements in an area previously infected with bTB and develops a framework for a targeted surveillance approach for bTB to support future surveillance decisions.