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

<b>Background</b><p></p> 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.<p></p> 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.<p></p> <b>Results</b><p></p> 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.<p></p> <b>Conclusions</b><p></p> 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

The challenges of data in future pandemics

This work was supported by Engineering and Physical Sciences Research Council (EPSRC) grant no. EP/R014604/1. M.C. was funded by the Engineering and Physical Sciences Research Council (EPSRC) grant no. EP/V054236/1. G.M. is supported by the Scottish Government’s Rural and Environment Science and Analytical Services Division (RESAS). J.P-G’s work is supported by funding from the UK Health Security Agency and the UK Department of Health and Social Care. L.P. is funded by the Wellcome Trust, UK and the Royal Society, UK (grant no. 202562/Z/16/Z). L.P. is supported by the UK Research and Innovation (UKRI) through the JUNIPER modelling consortium (grant no. MR/V038613/1). L.P. is also supported by The Alan Turing Institute for Data Science and Artificial Intelligence, UK. R.R was supported by the Natural Environment Research Council (NERC) grant no. NE/T004193/1 and NE/T010355/1, the Engineering and Physical Sciences Research Council (EPSRC) grant no. EP/V054236/1 and the Science and Technology Facilities Council (STFC) grant no. ST/V006126/1.The use of data has been essential throughout the unfolding COVID-19 pandemic. We have needed it to populate our models, inform our understanding, and shape our responses to the disease. However, data has not always been easy to find and access, it has varied in quality and coverage, been difficult to reuse or repurpose. This paper reviews these and other challenges and recommends steps to develop a data ecosystem better able to deal with future pandemics by better supporting preparedness, prevention, detection and response.Publisher PDFPeer reviewe

Antibody responses to recombinant protein fragments of the major outer membrane protein and polymorphic outer membrane protein POMP90 in Chlamydophila abortus-infected pregnant sheep

Chlamydophila abortus is one of the major causes of infectious abortion in pregnant sheep (enzootic abortion of ewes or EAE) worldwide. Organisms shed in infected placentas and uterine discharges at lambing time are the main sources of environmental contamination, responsible for transmission to susceptible animals and possible human contacts. In the present study, a recently developed test, based on a recombinant fragment of the polymorphic outer membrane protein POMP90 (rOMP90-4 indirect enzyme-linked immunosorbent assay [iELISA]) and one based on the variable segment 2 (VS2) region of the major outer membrane protein (MOMP) (MOMP VS2 iELISA) were compared using sera from C. abortus-infected ewes at different stages throughout pregnancy. The rOMP90 iELISA detected antibody much earlier in pregnancy than the MOMP iELISA, which, like the complement fixation test, detected antibody only at the time of abortion or lambing. No anti-MOMP antibody response could be detected in three of seven experimentally infected ewes. Furthermore, the rOMP90 iELISA detected antibody in an animal that seroconverted during the course of the study, which the MOMP iELISA failed to detect. Overall, the results show that the rOMP90-4 iELISA is considerably more sensitive than the MOMP VS2 iELISA for identifying animals infected with C. abortus. Earlier detection of infection will allow appropriate control measures to be taken to reduce environmental contamination, thus limiting the spread of infection, financial losses, and the possible risks of zoonotic transmission to humans

Patterns of mortality in domesticated ruminants in Ethiopia

BACKGROUND: Premature death of livestock is a problem in all ruminant production systems. While the number of premature ruminant deaths in a country is a reasonable indicator for the nation's health, few data sources exist in a country like Ethiopia that can be used to generate valid estimates. The present study aimed to establish if three different data sets, each with imperfect information on ruminant mortality, including abortions, could be combined into improved estimates of nationwide mortality in Ethiopia. METHODS: We combined information from a recent survey of ruminant mortality with information from the Living Standards Measurement Study and the Disease Outbreak and Vaccination Reporting dataset. Generalized linear mixed and hurdle models were used for data analysis, with results summarized using predicted outcomes. RESULTS: Analyses indicated that most herds experienced zero mortality and reproductive losses, with rare occasions of larger losses. Diseases causing deaths varied greatly both geographically and over time. There was little agreement between the different datasets. While the models aid the understanding of patterns of mortality and reproductive losses, the degree of variation observed limited the predictive scope. CONCLUSIONS: The models revealed some insight into why mortality rates are variable over time and are therefore less useful in measuring production or health status, and it is suggested that alternative measures of productivity, such as number of offspring raised to 1 year old per dam, would be more stable over time and likely more indicative

Combining Slaughterhouse Surveillance Data with Cattle Tracing Scheme and Environmental Data to Quantify Environmental Risk Factors for Liver Fluke in Cattle.

Liver fluke infection causes serious disease (fasciolosis) in cattle and sheep in many regions of the world, resulting in production losses and additional economic consequences due to condemnation of the liver at slaughter. Liver fluke depends on mud snails as an intermediate host and infect livestock when ingested through grazing. Therefore, environmental factors play important roles in infection risk and climate change is likely to modify this. Here, we demonstrate how slaughterhouse data can be integrated with other data, including animal movement and climate variables to identify environmental risk factors for liver fluke in cattle in Scotland. We fitted a generalized linear mixed model to the data, with exposure-weighted random and fixed effects, an approach which takes into account the amount of time cattle spent at different locations, exposed to different levels of risk. This enabled us to identify an increased risk of liver fluke with increased animal age, rainfall, and temperature and for farms located further to the West, in excess of the risk associated with a warmer, wetter climate. This model explained 45% of the variability in liver fluke between farms, suggesting that the unexplained 55% was due to factors not included in the model, such as differences in on-farm management and presence of wet habitats. This approach demonstrates the value of statistically integrating routinely recorded slaughterhouse data with other pre-existing data, creating a powerful approach to quantify disease risks in production animals. Furthermore, this approach can be used to better quantify the impact of projected climate change on liver fluke risk for future studies

Temporal and spatial patterns of bovine Escherichia coli O157 prevalence and comparison of temporal changes in the patterns of phage types associated with bovine shedding and human E. coli O157 cases in Scotland between 1998-2000 and 2002-2004

Background: Escherichia coli O157 is an important cause of acute diarrhoea, haemorrhagic colitis and, especially in children, haemolytic uraemic syndrome (HUS). Incidence rates for human E. coli O157 infection in Scotland are higher than most other United Kingdom, European and North American countries. Cattle are considered the main reservoir for E. coli O157. Significant associations between livestock related exposures and human infection have been identified in a number of studies. Results: Animal Studies: There were no statistically significant differences (P = 0.831) in the mean farm-level prevalence between the two studies (SEERAD: 0.218 (95% CI: 0.141-0.32); IPRAVE: 0.205 (95% CI: 0.135-0.296)). However, the mean pat-level prevalence decreased from 0.089 (95% CI: 0.075-0.105) to 0.040 (95% CI: 0.028-0.053) between the SEERAD and IPRAVE studies respectively (P < 0.001). Highly significant (P < 0.001) reductions in mean pat-level prevalence were also observed in the spring, in the North East and Central Scotland, and in the shedding of phage type (PT) 21/28. Human Cases: Contrasting the same time periods, there was a decline in the overall comparative annual reported incidence of human cases as well as in all the major PT groups except 'Other' PTs. For both cattle and humans, the predominant phage type between 1998 and 2004 was PT21/28 comprising over 50% of the positive cattle isolates and reported human cases respectively. The proportion of PT32, however, was represented by few (<5%) of reported human cases despite comprising over 10% of cattle isolates. Across the two studies there were differences in the proportion of PTs 21/28, 32 and 'Other' PTs in both cattle isolates and reported human cases; however, only differences in the cattle isolates were statistically significant (P = 0.002). Conclusion: There was no significant decrease in the mean farm-level prevalence of E. coli O157 between 1998 and 2004 in Scotland, despite significant declines in mean pat-level prevalence. Although there were declines in the number of human cases between the two study periods, there is no statistically significant evidence that the overall rate (per 100,000 population) of human E. coli O157 infections in Scotland over the last 10 years has altered. Comparable patterns in the distribution of PTs 21/28 and 32 between cattle and humans support a hypothesized link between the bovine reservoir and human infections. This emphasizes the need to apply and improve methods to reduce bovine shedding of E. coli O157 in Scotland where rates appear higher in both cattle and human populations, than in other countrie

Scenario planning: the future of the cattle and sheep industries in Scotland and their resiliency to disease

In this paper, we present a description of foresighting activities undertaken by EPIC, Scotland’s Centre of Expertise on Animal Disease Outbreaks, to investigate the future uncertainty of animal health security in the Scottish sheep and cattle sectors. Using scenario planning methodologies, we explored four plausible but provocative long-term futures which identify dynamics underpinning the resilience of these agricultural sectors to animal disease. These scenarios highlight a number of important drivers that influence disease resilience: industry demographics, the role of government support and regulation and the capacity for technological innovation to support the industry to meet local and global market demand. Participants in the scenario planning exercises proposed creative, robust strategies that policy makers could consider implementing now to enhance disease control and industry resilience in multiple, uncertain futures. Using these participant-led strategies as a starting point, we offer ten key questions for policy makers and stakeholders to provoke further discussion about improving resiliency and disease preparedness. We conclude with a brief discussion of the value of scenario planning, not only for the development of futures which will inform disease contingency plans and improve industry resilience, but as a mechanism for dialogue and information sharing between stakeholders and government

Successful immunization against a parasitic nematode by vaccination with recombinant proteins

AbstractInfection of humans and livestock with parasitic nematodes can have devastating effects on health and production, affecting food security in both developed and developing regions. Despite decades of research, the development of recombinant sub-unit vaccines against these pathogens has been largely unsuccessful. We have developed a strategy to identify protective antigens from Teladorsagia circumcincta, the major pathogen causing parasitic gastroenteritis in small ruminants in temperate regions, by studying IgA responses directed at proteins specific to post-infective larvae. Antigens were also selected on the basis of their potential immunomodulatory role at the host/parasite interface. Recombinant versions of eight molecules identified by immunoproteomics, homology with vaccine candidates in other nematodes and/or with potential immunoregulatory activities, were therefore administered to sheep in a single vaccine formulation. The vaccine was administered three times with Quil A adjuvant and the animals subsequently subjected to a repeated challenge infection designed to mimic field conditions. Levels of protection in the vaccinates were compared to those obtained in sheep administered with Quil A alone. The trial was performed on two occasions. In both trials, vaccinates had significantly lower mean fecal worm egg counts (FWECs) over the sampling period, with a mean reduction in egg output of 70% (Trial 1) and 58% (Trial 2). During the period of peak worm egg shedding, vaccinates shed 92% and 73% fewer eggs than did controls in Trials 1 and 2, respectively. At post mortem, vaccinates had 75% (Trial 1) and 56% (Trial 2) lower adult nematode burdens than the controls. These levels of protection are the highest observed in any system using a nematode recombinant sub-unit vaccine in the definitive ruminant host and indicate that control of parasitic helminths via vaccination with recombinant subunit vaccine cocktails is indeed an alternative option in the face of multi-drug resistance

FAIR Data Pipeline: provenance-driven data management for traceable scientific workflows

Modern epidemiological analyses to understand and combat the spread of disease depend critically on access to, and use of, data. Rapidly evolving data, such as data streams changing during a disease outbreak, are particularly challenging. Data management is further complicated by data being imprecisely identified when used. Public trust in policy decisions resulting from such analyses is easily damaged and is often low, with cynicism arising where claims of "following the science" are made without accompanying evidence. Tracing the provenance of such decisions back through open software to primary data would clarify this evidence, enhancing the transparency of the decision-making process. Here, we demonstrate a Findable, Accessible, Interoperable and Reusable (FAIR) data pipeline developed during the COVID-19 pandemic that allows easy annotation of data as they are consumed by analyses, while tracing the provenance of scientific outputs back through the analytical source code to data sources. Such a tool provides a mechanism for the public, and fellow scientists, to better assess the trust that should be placed in scientific evidence, while allowing scientists to support policy-makers in openly justifying their decisions. We believe that tools such as this should be promoted for use across all areas of policy-facing research