Syndromic surveillance by veterinary practitioners: a pilot study in the pig sector

2019 ◽  
Vol 184 (18) ◽  
pp. 556-556
Author(s):  
Carla Correia-Gomes ◽  
Madeleine Kate Henry ◽  
Susanna Williamson ◽  
Richard M Irvine ◽  
George J Gunn ◽  
...  
Keyword(s):  
Pilot Study ◽  
Disease Surveillance ◽  
Syndromic Surveillance ◽  
Animal Health ◽  
Relevant Information ◽  
Health Data ◽  
Vital Role ◽  
Case Definitions ◽  
Pig Farms ◽  
Incident Reports

Traditional indicator-based livestock surveillance has been focused on case definitions, definitive diagnoses and laboratory confirmation. The use of syndromic disease surveillance would increase the population base from which animal health data are captured and facilitate earlier detection of new and re-emerging threats to animal health. Veterinary practitioners could potentially play a vital role in such activities. In a pilot study, specialist private veterinary practitioners (PVP) working in the English pig industry were asked to collect and transfer background data and disease incident reports for pig farms visited during the study period. Baseline data from 110 pig farms were received, along with 68 disease incident reports. Reports took an average of approximately 25 minutes to complete. Feedback from the PVPs indicated that they saw value in syndromic surveillance. Maintenance of anonymity in the outputs would be essential, as would timely access for the PVPs to relevant information on syndromic trends. Further guidance and standardisation would also be required. Syndromic surveillance by PVPs is possible for the pig industry. It has potential to fill current gaps in the collection of animal health data, as long as the engagement and participation of data providers can be obtained and maintained.

scholarly journals Evaluating disease outbreaks with syndromic surveillance using medical student clinical rotation patient encounter logs

2021 ◽  
Vol 121 (2) ◽  
pp. 211-220
Author(s):  
Gabrielle Bruzda ◽  
Fred Rawlins ◽  
Cameron Sumpter ◽  
Harold R. Garner
Keyword(s):  
Medical Students ◽  
Syndromic Surveillance ◽  
Disease Outbreaks ◽  
Health Data ◽  
World Health ◽  
Clinical Rotation ◽  
Patient Encounter ◽  
Case Definitions ◽  
Early Detection Of Disease ◽  
Icd 10

Abstract Context While the data generated by medical students at schools that require electronic patient encounter logs is primarily used to monitor their training progress, it can also be a great source of public health data. Specifically, it can be used for syndromic surveillance, a method used to analyze instantaneous health data for early detection of disease outbreaks. Objective To analyze how the International Classification of Diseases, 10th Revision (ICD-10) codes input by medical students at the Edward Via College of Osteopathic Medicine into the Clinical Rotation Evaluation and Documentation Organizer (CREDO) patient encounter logging system could act as a new syndromic surveillance tool. Methods A CREDO database query was conducted for ICD-10 codes entered between November 1, 2019 and March 13, 2020 using the World Health Organization’s 2011 revised case definitions for Influenza Like Illness (ILI). During that period, medical students had an approximated mean of 3,000 patient encounters per day from over 1,500 clinical sites. A cumulative sum technique was applied to the data to generate alert thresholds. Breast cancer, a disease with a stable incidence during the specified timeframe, was used as a control. Results Total ILI daily ICD-10 counts that exceeded alert thresholds represented unusual levels of disease occurred 11 times from November 20, 2020 through February 28, 2020. This analysis is consistent with the COVID-19 pandemic timeline. The first statistically significant ILI increase occurred nine days prior to the first laboratory confirmed case in the country. Conclusion Syndromic surveillance can be timelier than traditional surveillance methods, which require laboratory testing to confirm disease. As a result of this study, we are installing a real-time alert for ILI into CREDO, so rates can be monitored continuously as an indicator of possible future new infectious disease outbreaks.

scholarly journals Standardising Syndromic Classification in Animal Health Data

2015 ◽  
Vol 7 (1) ◽  
Author(s):  
Fernanda C. Dórea ◽  
Céline Dupuy ◽  
Flavie Vial ◽  
Crawford Revie ◽  
Ann Lindberg
Keyword(s):  
Syndromic Surveillance ◽  
Animal Health ◽  
Data Use ◽  
Health Data ◽  
Disease Classification ◽  
Summary Statistics ◽  
Data Recording ◽  
Animal Disease ◽  
Contingency Plans ◽  
Different Sources

Data sharing remains a barrier to joint surveillance and the establishment of contingency plans among countries and institutions. Summary statistics are hard to interpret and compare, and nomenclatures for animal disease classification are seldom used. SSynCAHD (Syndromic Classification in Animal Health Data) proposes to harmonise, through the development on an ontology, syndromic surveillance data use rather than data recording. This will be achieved by standardising classification into syndromes, based on records from different sources of animal health data which are (and will continue to be) recorded using an institution own vocabulary.

Monitoring, Evaluation, Disease Surveillance, and Quality Improvement

2017 ◽  
Author(s):  
Joia S. Mukherjee
Keyword(s):  
Quality Improvement ◽  
Medical Records ◽  
Disease Surveillance ◽  
Program Planning ◽  
Health Data ◽  
Quality Data ◽  
Electronic Systems ◽  
Health Delivery ◽  
Use Of Data ◽  
Improve Health

Quality data are necessary to make good decisions in health delivery for both individuals and populations. Data can be used to improve care and achieve equity. However, systems for health data management were historically weak in most impoverished countries. Health data are not uncommonly compiled in stacks of poorly organized paper records. Efforts to streamline and improve health information discussed in this chapter include patient-held booklets, demographic health surveys, and the use of common indicators. This chapter also focuses on the evolution of medical records, including electronic systems. The use of data for monitoring, evaluation, and quality improvement is explained. Finally, this chapter reviews the use of frameworks—such as logic models and log frames—for program planning, evaluation, and improvement.

California National Animal Health Monitoring System for Meat Turkey Flocks: 1988-89 Pilot Study: Management Practices, Flock Health, and Production

1996 ◽  
Vol 40 (2) ◽  
pp. 278 ◽  
Author(s):  
Kathryn H. Christiansen ◽  
David W. Hird ◽  
Kurt P. Snipes ◽  
Cyrus Danaye-Elmi ◽  
Charles W. Palmer ◽  
...  
Keyword(s):  
Pilot Study ◽  
Monitoring System ◽  
Health Monitoring ◽  
Management Practices ◽  
Animal Health ◽  
Health Monitoring System ◽  
Study Management

scholarly journals Utilization of WhatsApp for sharing livestock related information: An Experimental Study

2017 ◽  
Vol 13 (01) ◽  
Author(s):  
Devesh Thakur ◽  
Mahesh Chander
Keyword(s):  
Experimental Study ◽  
Animal Health ◽  
Relevant Information ◽  
Himachal Pradesh ◽  
Animal Breeding ◽  
Multiple Forms ◽  
Related Information ◽  
Dairy Processing ◽  
Extension Agencies

The paper is based on the use of WhatsApp in sharing of livestock related information among the farmers. A WhatsApp group of randomly selected 96 farmers from eight different districts of the Himachal Pradesh, India was created under the study. In a period of six months, information was shared in multiple forms among the farmers. A total of 62 queries during six months to seek information and advice on various livestock related problems were posted by the farmers. Maximum number of queries pertained to animal health followed by animal breeding, feeding, government programmes and dairy processing .The livestock extension agencies have the opportunity to explore and develop relevant information which can be disseminated through WhatsApp to the farmers.

scholarly journals Sleep Tracking and Exercise in Patients With Type 2 Diabetes Mellitus (Step-D): Pilot Study to Determine Correlations Between Fitbit Data and Patient-Reported Outcomes (Preprint)

2017 ◽  
Author(s):  
James Weatherall ◽  
Yurek Paprocki ◽  
Theresa M Meyer ◽  
Ian Kudel ◽  
Edward A Witt
Keyword(s):  
Physical Activity ◽  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Pilot Study ◽  
Patient Reported Outcomes ◽  
Sleep Problems ◽  
Health Data ◽  
Patient Reported

BACKGROUND Few studies assessing the correlation between patient-reported outcomes and patient-generated health data from wearable devices exist. OBJECTIVE The aim of this study was to determine the direction and magnitude of associations between patient-generated health data (from the Fitbit Charge HR) and patient-reported outcomes for sleep patterns and physical activity in patients with type 2 diabetes mellitus (T2DM). METHODS This was a pilot study conducted with adults diagnosed with T2DM (n=86). All participants wore a Fitbit Charge HR for 14 consecutive days and completed internet-based surveys at 3 time points: day 1, day 7, and day 14. Patient-generated health data included minutes asleep and number of steps taken. Questionnaires assessed the number of days of exercise and nights of sleep problems per week. Means and SDs were calculated for all data, and Pearson correlations were used to examine associations between patient-reported outcomes and patient-generated health data. All respondents provided informed consent before participating. RESULTS The participants were predominantly middle-aged (mean 54.3, SD 13.3 years), white (80/86, 93%), and female (50/86, 58%). Use of oral T2DM medication correlated with the number of mean steps taken (r=.35, P=.001), whereas being unaware of the glycated hemoglobin level correlated with the number of minutes asleep (r=−.24, P=.04). On the basis of the Fitbit data, participants walked an average of 4955 steps and slept 6.7 hours per day. They self-reported an average of 2.0 days of exercise and 2.3 nights of sleep problems per week. The association between the number of days exercised and steps walked was strong (r=.60, P<.001), whereas the association between the number of troubled sleep nights and minutes asleep was weaker (r=.28, P=.02). CONCLUSIONS Fitbit and patient-reported data were positively associated for physical activity as well as sleep, with the former more strongly correlated than the latter. As extensive patient monitoring can guide clinical decisions regarding T2DM therapy, passive, objective data collection through wearables could potentially enhance patient care, resulting in better patient-reported outcomes.

scholarly journals The latest FAD – Faecal antibody detection in cattle. Protocol and results from three UK beef farms naturally infected with gastrointestinal nematodes

Parasitology ◽  
2018 ◽  
Vol 146 (1) ◽  
pp. 89-96 ◽  
Author(s):  
A. S. Cooke ◽  
K. A. Watt ◽  
E. R. Morgan ◽  
J. A. J. Dungait
Keyword(s):  
Animal Health ◽  
Nematode Species ◽  
Gastrointestinal Nematodes ◽  
Vital Role ◽  
Antibody Detection ◽  
Enzyme Linked Immunosorbent Assay ◽  
Serum Samples ◽  
Fecal Samples ◽  
Gastrointestinal Health ◽  
Immunological Protection

AbstractAntibodies at gastrointestinal mucosal membranes play a vital role in immunological protection against a range of pathogens, including helminths. Gastrointestinal health is central to efficient livestock production, and such infections cause significant losses. Fecal samples were taken from 114 cattle, across three beef farms, with matched blood samples taken from 22 of those animals. To achieve fecal antibody detection, a novel fecal supernatant was extracted. Fecal supernatant and serum samples were then analysed, using adapted enzyme-linked immunosorbent assay protocols, for levels of total immunoglobulin (Ig)A, IgG, IgM, andTeladorsagia circumcincta-specific IgA, IgG, IgM and IgE (in the absence of reagents for cattle-specific nematode species). Fecal nematode egg counts were conducted on all fecal samples. Assays performed successfully and showed that IgA was the predominant antibody in fecal samples, whereas IgG was predominant in serum. Total IgA in feces and serum correlated within individuals (0.581,P= 0.005), but other Ig types did not. Results support the hypothesis that the tested protocols are an effective method for the non-invasive assessment of cattle immunology. The method could be used as part of animal health assessments, although further work is required to interpret the relationship between results and levels of infection and immunity.

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