Escherichia coli O157 infection on Scottish cattle farms: dynamics and control

Spatio-temporal modelling of verotoxigenic Escherichia coli O157 in cattle in Sweden: exploring options for control

A spatial data-driven stochastic model was developed to explore the spread of verotoxigenic Escherichia coli O157 (VTEC O157) by livestock movements and local transmission among neighbouring holdings in the complete Swedish cattle population. Livestock data were incorporated to model the time-varying contact network between holdings and population demographics. Furthermore, meteorological data with the average temperature at the geographical location of each holding was used to incorporate season. The model was fitted against observed data and extensive numerical experiments were conducted to investigate the model’s response to control strategies aimed at reducing shedding and susceptibility, as well as interventions informed by network measures. The results showed that including local spread and season improved agreement with prevalence studies. Also, control strategies aimed at reducing the average shedding rate were more efficient in reducing the VTEC O157 prevalence than strategies based on network measures. The methodology presented in this study could provide a basis for developing disease surveillance on regional and national scales, where observed data are combined with readily available high-resolution data in simulations to get an overview of potential disease spread in unobserved regions.

Factors Involved in the Persistence of a Shiga Toxin-Producing Escherichia coli O157:H7 Strain in Bovine Feces and Gastro-Intestinal Content

Healthy cattle are the primary reservoir for O157:H7 Shiga toxin-producing E. coli responsible for human food-borne infections. Because farm environment acts as a source of cattle contamination, it is important to better understand the factors controlling the persistence of E. coli O157:H7 outside the bovine gut. The E. coli O157:H7 strain MC2, identified as a persistent strain in French farms, possessed the characteristics required to cause human infections and genetic markers associated with clinical O157:H7 isolates. Therefore, the capacity of E. coli MC2 to survive during its transit through the bovine gastro-intestinal tract (GIT) and to respond to stresses potentially encountered in extra-intestinal environments was analyzed. E. coli MC2 survived in rumen fluids, grew in the content of posterior digestive compartments and survived in bovine feces at 15°C predicting a successful transit of the bacteria along the bovine GIT and its persistence outside the bovine intestine. E. coli MC2 possessed the genetic information encoding 14 adherence systems including adhesins with properties related to colonization of the bovine intestine (F9 fimbriae, EhaA and EspP autotransporters, HCP pilus, FdeC adhesin) reflecting the capacity of the bacteria to colonize different segments of the bovine GIT. E. coli MC2 was also a strong biofilm producer when incubated in fecal samples at low temperature and had a greater ability to form biofilms than the bovine commensal E. coli strain BG1. Furthermore, in contrast to BG1, E. coli MC2 responded to temperature stresses by inducing the genes cspA and htrA during its survival in bovine feces at 15°C. E. coli MC2 also activated genes that are part of the GhoT/GhoS, HicA/HicB and EcnB/EcnA toxin/antitoxin systems involved in the response of E. coli to nutrient starvation and chemical stresses. In summary, the large number of colonization factors known to bind to intestinal epithelium and to biotic or abiotic surfaces, the capacity to produce biofilms and to activate stress fitness genes in bovine feces could explain the persistence of E. coli MC2 in the farm environment.

Complex responses to movement-based disease control: when livestock trading helps

Livestock disease controls are often linked to movements between farms, for example, via quarantine and pre- or post-movement testing. Designing effective controls, therefore, benefits from accurate assessment of herd-to-herd transmission. Household models of human infections make use of R_*, the number of groups infected by an initial infected group, which is a metapopulation level analogue of the basic reproduction number R₀ that provides a better characterization of disease spread in a metapopulation. However, existing approaches to calculate R_* do not account for individual movements between locations which means we lack suitable tools for livestock systems. We address this gap using next-generation matrix approaches to capture movements explicitly and introduce novel tools to calculate R_* in any populations coupled by individual movements. We show that depletion of infectives in the source group, which hastens its recovery, is a phenomenon with important implications for design and efficacy of movement-based controls. Underpinning our results is the observation that R_* peaks at intermediate livestock movement rates. Consequently, under movement-based controls, infection could be controlled at high movement rates but persist at intermediate rates. Thus, once control schemes are present in a livestock system, a reduction in movements can counterintuitively lead to increased disease prevalence. We illustrate our results using four important livestock diseases (bovine viral diarrhoea, bovine herpes virus, Johne's disease and Escherichia coli O157) that each persist across different movement rate ranges with the consequence that a change in livestock movements could help control one disease, but exacerbate another.

Transmission of Escherichia coli O157:H7 in cattle is influenced by the level of environmental contamination

A pen infection-transmission experiment was conducted to elucidate the role of pathogen strain and environmental contamination in transmission of Escherichia coli O157:H7 (ECO157) in cattle. Five steers were inoculated with a three-strain mixture of ECO157 and joined with five susceptible steers in each of two experimental replicates. Faecal and environmental samples were monitored for ECO157 presence over 30 days. One ECO157 strain did not spread. Transmission rates for the other two strains were estimated using a generalized linear model developed based on a modified ‘Susceptible–Infectious–Susceptible’ mathematical model. Transmission rates estimated for the two strains (0·11 and 0·14) were similar. However, the rates significantly (P = 0·0006) increased 1·5 times for every 1-unit increase in the level of environmental contamination measured as log₁₀ c.f.u. Depending on the level of environmental contamination, the estimated basic reproduction numbers varied from <1 to 8. The findings indicate the importance of on-farm measures to reduce environmental contamination for ECO157 control in cattle that should be validated under field conditions.

Design and descriptive epidemiology of the Infectious Diseases of East African Livestock (IDEAL) project, a longitudinal calf cohort study in western Kenya

Background

There is a widely recognised lack of baseline epidemiological data on the dynamics and impacts of infectious cattle diseases in east Africa. The Infectious Diseases of East African Livestock (IDEAL) project is an epidemiological study of cattle health in western Kenya with the aim of providing baseline epidemiological data, investigating the impact of different infections on key responses such as growth, mortality and morbidity, the additive and/or multiplicative effects of co-infections, and the influence of management and genetic factors.

A longitudinal cohort study of newborn calves was conducted in western Kenya between 2007-2009. Calves were randomly selected from all those reported in a 2 stage clustered sampling strategy. Calves were recruited between 3 and 7 days old. A team of veterinarians and animal health assistants carried out 5-weekly, clinical and postmortem visits. Blood and tissue samples were collected in association with all visits and screened using a range of laboratory based diagnostic methods for over 100 different pathogens or infectious exposures.

Results

The study followed the 548 calves over the first 51 weeks of life or until death and when they were reported clinically ill. The cohort experienced a high all cause mortality rate of 16% with at least 13% of these due to infectious diseases. Only 307 (6%) of routine visits were classified as clinical episodes, with a further 216 reported by farmers. 54% of calves reached one year without a reported clinical episode. Mortality was mainly to east coast fever, haemonchosis, and heartwater. Over 50 pathogens were detected in this population with exposure to a further 6 viruses and bacteria.

Conclusion

The IDEAL study has demonstrated that it is possible to mount population based longitudinal animal studies. The results quantify for the first time in an animal population the high diversity of pathogens a population may have to deal with and the levels of co-infections with key pathogens such as Theileria parva. This study highlights the need to develop new systems based approaches to study pathogens in their natural settings to understand the impacts of co-infections on clinical outcomes and to develop new evidence based interventions that are relevant.

Herd-level risk factors associated with fecal shedding of Shiga toxin-encoding bacteria on dairy farms in Minnesota, USA

This study aimed to identify herd-level risk factors associated with fecal shedding of Shiga toxin-encoding bacteria (STB) on dairy cattle farms in Minnesota, USA. After adjustment for farm size, risk factors included: use of total mixed ration (TMR) for lactating dairy cows [odds ratio (OR) = 3.0; 95% confidence interval (CI): 1.8 to 5.1], no use of monensin for weaned calves (OR = 4.8, 95% CI: 2.5, 9.3), and no use of decoquinate for preweaned calves (OR = 2.2, 95% CI: 1.4, 3.6). Fecal shedding of STB was more common in small herds (< 100 cows, OR = 3.6, 95% CI: 2.1, 6.2) than in large herds (≥ 100 cows). Herd management factors related to cattle feeding practices were associated with fecal shedding of STB.

A comparison of modelling approaches to assess the transmission of pathogens between Scottish fish farms: the role of hydrodynamics and site biomass

Scotland is the largest Atlantic salmon (Salmo salar) producer in the EU with an output of over 150,000 t, contributing over £500 million annually towards the economy. Production continues to increase, predominantly due to the increase in output per farm and reduction in losses due to infectious diseases. Farms are grouped within disease management areas whose boundaries are defined by where the closest pair of farms is separated by more than twice the tidal excursion distance (TE) Tidal excursion is defined as 7.2 km in mainland Scotland, or 3.6 km in the Shetland Islands). The majority of salmon farms are located within relatively sheltered inshore areas where non-tidal advective current speed is minimal. However there is an aspiration for offshore production where it might be possible to increase stocking levels and where current speeds will be greater so TE models could break down. Separation distances whereby farms would avoid infection risk were obtained using an analytical, discrete-time Susceptible-Exposed-Infectious-Recovered (SEIR) model coupled with a hydrodynamic transport expression representing transmission of pathogenic agents between fish farms. The model incorporated transmission, expression and recovery parameters as well as pathogen shedding and decay. The simplified hydrodynamic model incorporated residual advection, tidal advection and turbulent diffusion elements. The obtained separation distances were compared to a computationally intensive, numerical model and were demonstrated to be comparable, although the analytical model underestimated the variation within the transmission distances. Applying characteristics for a robust pathogen, infectious pancreatic necrosis virus type (IPNV-type), and less robust pathogens such as infectious salmon anaemia virus type (ISAV-type) and Aeromonas salmonicida type (AS-type) pathogens, it was possible to obtain separation distances whereby farms avoided infection. Simulation outputs indicated that separation distances should increase to avoid disease as farm size and current speed increase. The more conserved IPNV-type pathogen required separation distances of hundreds of kilometres, AS-type required tens of kilometres, whilst the distances for ISAV-type were within the scale of the current DMAs, that were developed for ISAV control. However, should production be moved to areas of faster moving currents and increased farm production the current disease management area principles might need readdressing.

How to make predictions about future infectious disease risks

Formal, quantitative approaches are now widely used to make predictions about the likelihood of an infectious disease outbreak, how the disease will spread, and how to control it. Several well-established methodologies are available, including risk factor analysis, risk modelling and dynamic modelling. Even so, predictive modelling is very much the ‘art of the possible’, which tends to drive research effort towards some areas and away from others which may be at least as important. Building on the undoubted success of quantitative modelling of the epidemiology and control of human and animal diseases such as AIDS, influenza, foot-and-mouth disease and BSE, attention needs to be paid to developing a more holistic framework that captures the role of the underlying drivers of disease risks, from demography and behaviour to land use and climate change. At the same time, there is still considerable room for improvement in how quantitative analyses and their outputs are communicated to policy makers and other stakeholders. A starting point would be generally accepted guidelines for ‘good practice’ for the development and the use of predictive models.