Identifying temporal variation in reported births, deaths and movements of cattle in Britain

BACKGROUND: The accuracy of predicting disease occurrence using epidemic models relies on an understanding of the system or population under investigation. At the time of the Foot and Mouth disease (FMD) outbreak of 2001, there were limited reports in the literature as to the cattle population structure in Britain. In this paper we examine the temporal patterns of cattle births, deaths, imports and movements occurring within Britain, reported to the Department for the Environment, Food and Rural Affairs (DEFRA) through the British Cattle Movement service (BCMS) during the period 1(st )January 2002 to 28(th )February 2005. RESULTS: In Britain, the number of reported cattle births exhibit strong seasonality characterised by a large spring peak followed by a smaller autumn peak. Other event types also exhibit strong seasonal trends; both the reported number of cattle slaughtered and "on-farm" cattle deaths increase during the final part of the year. After allowing for seasonal components by smoothing the data, we illustrate that there is very little remaining non-seasonal trend in the number of cattle births, "on-farm" deaths, slaughterhouse deaths, on- and off-movements. However after allowing for seasonal fluctuations the number of cattle imports has been decreasing since 2002. Reporting of movements, births and deaths was more frequent on certain days of the week. For instance, greater numbers of cattle were slaughtered on Tuesdays, Wednesdays and Thursdays. Evidence for digit preference was found in the reporting of births and "on-farm" deaths with particular bias towards over reporting on the 1(st), 10(th )and 20(th )of each month. CONCLUSION: This study provides insight into the population and movement dynamics of the British cattle population. Although the population is in constant flux, seasonal and long term trends can be identified in the number of reported births, deaths and movements of cattle. Incorporating this temporal variation in epidemic disease modelling may result in more accurate model predictions and may usefully inform future surveillance strategies

GP coding behaviour for non-specific clinical presentations: a pilot study

Background: Clinical coding is an integral part of primary care. Disease incidence studies based on primary care electronic health records (EHRs) rely on the accuracy of these codes. Current code validation methods are not appropriate for non-specific conditions and provide limited information about GPs' decision-making behaviour around coding. Qualitative methods could offer insight into decision-making behaviour around coding of patients with non-specific conditions. Aim: To investigate the decision-making behaviour of GPs when applying Read codes to non-specific clinical presentations, using Lyme disease as a case example. Design & setting: A pilot study was undertaken, involving masked semi-structured interviews of eight GPs in the North West of England. Method: Semi-structured interviews were carried out based on 11 clinical cases representative of Lyme disease presentations. Discrete answers were described descriptively. Interview transcripts were analysed using a thematic approach. Results: Themes underpinning GPs’ coding behaviour included: GP personal and professional experience; clinical evidence; diagnostic uncertainty; professional integrity and defensive practice; and patient-sourced health information and beliefs. GPs placed Lyme disease on their differential diagnosis list for five cases; in only two cases would GPs select a Lyme disease related Read code. Conclusion: GPs were reluctant to code with specific diagnostic Read codes when they were presented with patients with vague or unfamiliar symptomology. This masked questionnaire methodology offers a new approach to validate incidence figures, based on Read codes of non-specific conditions. The reluctance to code poses many problems for primary care EH

Can policy be risk-based? The cultural theory of risk and the case of livestock disease containment

This article explores the nature of calls for risk-based policy present in expert discourse from a cultural theory perspective. Semi-structured interviews with professionals engaged in the research and management of livestock disease control provide the data for a reading proposing that the real basis of policy relating to socio-technical hazards is deeply political and cannot be purified through ‘escape routes’ to objectivity. Scientists and risk managers are shown calling, on the one hand, for risk-based policy approaches while on the other acknowledging a range of policy drivers outside the scope of conventional quantitative risk analysis including group interests, eventualities such as outbreaks, historical antecedents, emergent scientific advances and other contingencies. Calls for risk-based policy are presented, following cultural theory, as ideals connected to a reductionist epistemology and serving particular professional interests over others rather than as realistic proposals for a paradigm shift

A survey of UK healthcare workers' attitudes on volunteering to help with the Ebola outbreak in West Africa

Objective To understand the barriers and enablers for UK healthcare workers who are considering going to work in the current Ebola outbreak in West Africa, but have not yet volunteered. Design After focus group discussions, and a pilot questionnaire, an anonymous survey was conducted using SurveyMonkey to determine whether people had considered going to West Africa, what factors might make them more or less likely to volunteer, and whether any of these were modifiable factors. Participants The survey was publicised among doctors, nurses, laboratory staff and allied health professionals. 3109 people answered the survey, of whom 472 (15%) were considering going to work in the epidemic but had not yet volunteered. 1791 (57.6%) had not considered going, 704 (22.6%) had considered going but decided not to, 53 (1.7%) had volunteered to go and 14 (0.45%) had already been and worked in the epidemic. Results For those considering going to West Africa, the most important factor preventing them from volunteering was a lack of information to help them decide; fear of getting Ebola and partners’ concerns came next. Uncertainty about their potential role, current work commitments and inability to get agreement from their employer were also important barriers, whereas clarity over training would be an important enabler. In contrast, for those who were not considering going, or who had decided against going, family considerations and partner concerns were the most important factors. Conclusions More UK healthcare workers would volunteer to help tackle Ebola in West Africa if there was better information available, including clarity about roles, cover arrangements, and training. This could be achieved with a well-publicised high quality portal of reliable information

A Fully Integrated Real-Time Detection, Diagnosis, and Control of Community Diarrheal Disease Clusters and Outbreaks (the INTEGRATE Project):Protocol for an Enhanced Surveillance System

BACKGROUND:Diarrheal disease, which affects 1 in 4 people in the United Kingdom annually, is the most common cause of outbreaks in community and health care settings. Traditional surveillance methods tend to detect point-source outbreaks of diarrhea and vomiting; they are less effective at identifying low-level and intermittent food supply contamination. Furthermore, it can take up to 9 weeks for infections to be confirmed, reducing slow-burn outbreak recognition, potentially impacting hundreds or thousands of people over wide geographical areas. There is a need to address fundamental problems in traditional diarrheal disease surveillance because of underreporting and subsequent unconfirmed infection by patients and general practitioners (GPs); varying submission practices and selective testing of samples in laboratories; limitations in traditional microbiological diagnostics, meaning that the timeliness of sample testing and etiology of most cases remains unknown; and poorly integrated human and animal surveillance systems, meaning that identification of zoonoses is delayed or missed. OBJECTIVE:This study aims to detect anomalous patterns in the incidence of gastrointestinal disease in the (human) community; to target sampling; to test traditional diagnostic methods against rapid, modern, and sensitive molecular and genomic microbiology methods that identify and characterize responsible pathogens rapidly and more completely; and to determine the cost-effectiveness of rapid, modern, sensitive molecular and genomic microbiology methods. METHODS:Syndromic surveillance will be used to aid identification of anomalous patterns in microbiological events based on temporal associations, demographic similarities among patients and animals, and changes in trends in acute gastroenteritis cases using a point process statistical model. Stool samples will be obtained from patients' consulting GPs, to improve the timeliness of cluster detection and characterize the pathogens responsible, allowing health protection professionals to investigate and control outbreaks quickly, limiting their size and impact. The cost-effectiveness of the proposed system will be examined using formal cost-utility analysis to inform decisions on national implementation. RESULTS:The project commenced on April 1, 2013. Favorable approval was obtained from the Research Ethics Committee on June 15, 2015, and the first patient was recruited on October 13, 2015, with 1407 patients recruited and samples processed using traditional laboratory techniques as of March 2017. CONCLUSIONS:The overall aim of this study is to create a new One Health paradigm for detecting and investigating diarrhea and vomiting in the community in near-real time, shifting from passive human surveillance and management of laboratory-confirmed infection toward an integrated, interdisciplinary enhanced surveillance system including management of people with symptoms. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID):DERR1-10.2196/13941

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<p><b>Copyright information:</b></p><p>Taken from "Identifying temporal variation in reported births, deaths and movements of cattle in Britain"</p><p>BMC Veterinary Research 2006;2():11-11.</p><p>Published online 30 Mar 2006</p><p>PMCID:PMC1440854.</p><p>Copyright © 2006 Robinson and Christley; licensee BioMed Central Ltd.</p>unconnected symbols) (c) Residuals after accounting for the 3-point moving average (d) 53-point moving average (raw weekly data shown as unconnected symbols)

Identifying temporal variation in reported births, deaths and movements of cattle in Britain-4

<p><b>Copyright information:</b></p><p>Taken from "Identifying temporal variation in reported births, deaths and movements of cattle in Britain"</p><p>BMC Veterinary Research 2006;2():11-11.</p><p>Published online 30 Mar 2006</p><p>PMCID:PMC1440854.</p><p>Copyright © 2006 Robinson and Christley; licensee BioMed Central Ltd.</p>esiduals after accounting for the 3-point moving average (d) 13-point moving average (raw monthly data shown as unconnected symbols)

Identifying temporal variation in reported births, deaths and movements of cattle in Britain-7

<p><b>Copyright information:</b></p><p>Taken from "Identifying temporal variation in reported births, deaths and movements of cattle in Britain"</p><p>BMC Veterinary Research 2006;2():11-11.</p><p>Published online 30 Mar 2006</p><p>PMCID:PMC1440854.</p><p>Copyright © 2006 Robinson and Christley; licensee BioMed Central Ltd.</p>incorporate the standard errors around the parameter estimate with error bars indicating the 95% confidence interval

Identifying temporal variation in reported births, deaths and movements of cattle in Britain-1

<p><b>Copyright information:</b></p><p>Taken from "Identifying temporal variation in reported births, deaths and movements of cattle in Britain"</p><p>BMC Veterinary Research 2006;2():11-11.</p><p>Published online 30 Mar 2006</p><p>PMCID:PMC1440854.</p><p>Copyright © 2006 Robinson and Christley; licensee BioMed Central Ltd.</p>unconnected symbols) (c) Residuals after accounting for the 3-point moving average (d) 53-point moving average (raw weekly data shown as unconnected symbols)