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1.  An online survey of horse-owners in Great Britain 
Background
Contingency planning for potential equine infectious disease outbreaks relies on accurate information on horse location and movements to estimate the risk of dissemination of disease(s). An online questionnaire was used to obtain unique information linking owner and horse location to characteristics of horse movements within and outwith Great Britain (GB).
Results
This online survey yielded a strong response, providing more than four times the target number of respondents (1000 target respondents) living in all parts of GB. Key demographic findings of this study indicated that horses which were kept on livery yards and riding schools were likely to be found in urban environments, some distance away from the owner’s home and vaccinated against influenza and herpes virus. Survey respondents were likely to travel greater than 10 miles to attend activities such as eventing or endurance but were also likely to travel and return home within a single day (58.6%, 2063/3522). This may affect the geographical extent and speed of disease spread, if large numbers of people from disparate parts of the country are attending the same event and the disease agent is highly infectious or virulent. The greatest risk for disease introduction and spread may be represented by a small proportion of people who import or travel internationally with their horses. These respondents were likely to have foreign horse passports, which were not necessarily recorded in the National Equine Database (NED), making the location of these horses untraceable.
Conclusions
These results illustrate the difficulties which exist with national GB horse traceability despite the existence of the NED and the horse passport system. This study also demonstrates that an online approach could be adopted to obtain important demographic data on GB horse owners on a more routine and frequent basis to inform decisions or policy pertaining to equine disease control. This represents a reasonable alternative to collection of GB horse location and movement data given that the NED no longer exists and there is no immediate plan to replace it.
doi:10.1186/1746-6148-9-188
PMCID: PMC3850011  PMID: 24074003
Equine movement; Location; Demography; Online questionnaire survey
2.  Summary of current knowledge of the size and spatial distribution of the horse population within Great Britain 
Background
Robust demographic information is important to understanding the risk of introduction and spread of exotic diseases as well as the development of effective disease control strategies, but is often based on datasets collected for other purposes. Thus, it is important to validate, or at least cross-reference these datasets to other sources to assess whether they are being used appropriately. The aim of this study was to use horse location data collected from different contributing industry sectors ("Stakeholder horse data") to calibrate the spatial distribution of horses as indicated by owner locations registered in the National Equine Database (the NED).
Results
A conservative estimate for the accurately geo-located NED horse population within GB is approximately 840,000 horses. This is likely to be an underestimate because of the exclusion of horses due to age or location criteria. In both datasets, horse density was higher in England and Wales than in Scotland. The high density of horses located in urban areas as indicated in the NED is consistent with previous reports indicating that owner location cannot always be viewed as a direct substitute for horse location. Otherwise, at a regional resolution, there are few differences between the datasets. There are inevitable biases in the stakeholder data, and leisure horses that are unaffiliated to major stakeholders are not included in these data. Despite this, the similarity in distributions of these datasets is re-assuring, suggesting that there are few regional biases in the NED.
Conclusions
Our analyses suggest that stakeholder data could be used to monitor possible changes in horse demographics. Given such changes in horse demographics and the advantages of stakeholder data (which include annual updates and accurate horse location), it may be appropriate to use these data for future disease modelling in conjunction with, if not in place of the NED.
doi:10.1186/1746-6148-8-43
PMCID: PMC3351363  PMID: 22475060
Equine; Demography; Spatial distribution; Infectious disease; The National Equine Database
3.  Generating social network data using partially described networks: an example informing avian influenza control in the British poultry industry 
Background
Targeted sampling can capture the characteristics of more vulnerable sectors of a population, but may bias the picture of population level disease risk. When sampling network data, an incomplete description of the population may arise leading to biased estimates of between-host connectivity. Avian influenza (AI) control planning in Great Britain (GB) provides one example where network data for the poultry industry (the Poultry Network Database or PND), targeted large premises and is consequently demographically biased. Exposing the effect of such biases on the geographical distribution of network properties could help target future poultry network data collection exercises. These data will be important for informing the control of potential future disease outbreaks.
Results
The PND was used to compute between-farm association frequencies, assuming that farms sharing the same slaughterhouse or catching company, or through integration, are potentially epidemiologically linked. The fitted statistical models were extrapolated to the Great Britain Poultry Register (GBPR); this dataset is more representative of the poultry industry but lacks network information. This comparison showed how systematic biases in the demographic characterisation of a network, resulting from targeted sampling procedures, can bias the derived picture of between-host connectivity within the network.
Conclusions
With particular reference to the predictive modeling of AI in GB, we find significantly different connectivity patterns across GB when network estimates incorporate the more demographically representative information provided by the GBPR; this has not been accounted for by previous epidemiological analyses. We recommend ranking geographical regions, based on relative confidence in extrapolated estimates, for prioritising further data collection. Evaluating whether and how the between-farm association frequencies impact on the risk of between-farm transmission will be the focus of future work.
doi:10.1186/1746-6148-7-66
PMCID: PMC3275467  PMID: 22027039
4.  The potential spread of highly pathogenic avian influenza virus via dynamic contacts between poultry premises in Great Britain 
Background
Highly pathogenic avian influenza (HPAI) viruses have had devastating effects on poultry industries worldwide, and there is concern about the potential for HPAI outbreaks in the poultry industry in Great Britain (GB). Critical to the potential for HPAI to spread between poultry premises are the connections made between farms by movements related to human activity. Movement records of catching teams and slaughterhouse vehicles were obtained from a large catching company, and these data were used in a simulation model of HPAI spread between farms serviced by the catching company, and surrounding (geographic) areas. The spread of HPAI through real-time movements was modelled, with the addition of spread via company personnel and local transmission.
Results
The model predicted that although large outbreaks are rare, they may occur, with long distances between infected premises. Final outbreak size was most sensitive to the probability of spread via slaughterhouse-linked movements whereas the probability of onward spread beyond an index premises was most sensitive to the frequency of company personnel movements.
Conclusions
Results obtained from this study show that, whilst there is the possibility that HPAI virus will jump from one cluster of farms to another, movements made by catching teams connected fewer poultry premises in an outbreak situation than slaughterhouses and company personnel. The potential connection of a large number of infected farms, however, highlights the importance of retaining up-to-date data on poultry premises so that control measures can be effectively prioritised in an outbreak situation.
doi:10.1186/1746-6148-7-59
PMCID: PMC3224601  PMID: 21995783
5.  Contact structures in the poultry industry in Great Britain: Exploring transmission routes for a potential avian influenza virus epidemic 
Background
The commercial poultry industry in United Kingdom (UK) is worth an estimated £3.4 billion at retail value, producing over 174 million birds for consumption per year. An epidemic of any poultry disease with high mortality or which is zoonotic, such as avian influenza virus (AIV), would result in the culling of significant numbers of birds, as seen in the Netherlands in 2003 and Italy in 2000. Such an epidemic would cost the UK government millions of pounds in compensation costs, with further economic losses through reduction of international and UK consumption of British poultry. In order to better inform policy advisers and makers on the potential for a large epidemic in GB, we investigate the role that interactions amongst premises within the British commercial poultry industry could play in promoting an AIV epidemic, given an introduction of the virus in a specific part of poultry industry in Great Britain (GB).
Results
Poultry premises using multiple slaughterhouses lead to a large number of premises being potentially connected, with the resultant potential for large and sometimes widespread epidemics. Catching companies can also potentially link a large proportion of the poultry population. Critical to this is the maximum distance traveled by catching companies between premises and whether or not between-species transmission could occur within individual premises. Premises closely linked by proximity may result in connections being formed between different species and or sectors within the industry.
Conclusion
Even quite well-contained epidemics have the potential for geographically widespread dissemination, potentially resulting in severe logistical problems for epidemic control, and with economic impact on a large part of the country. Premises sending birds to multiple slaughterhouses or housing multiple species may act as a bridge between otherwise separate sectors of the industry, resulting in the potential for large epidemics. Investment into further data collection and analyses on the importance of industry structure as a determinant for spread of AIV would enable us to use the results from this study to contribute to policy on disease control.
doi:10.1186/1746-6148-4-27
PMCID: PMC2526082  PMID: 18651959

Results 1-5 (5)