General Principles

Within this section we will post information and links to material about the need, challenges and sources of population data.   For example: Dr. Dan O'Neill, who developed VetCompass in the UK ( http://www.rvc.ac.uk/vetcompass ), has written this review article: http://www.cgejournal.org/content/1/1/2   From the article:   "An ability to identify at a population level how many dogs, within breeds or across all breeds develop certain diseases, either over a fixed time period (e.g. each year) or as a proportion of the total population is very important. This helps establish whether some animals and breeds are particularly susceptible to a disease or whether conditions are becoming more or less common."   The aims of any given study and the methods influence the findings and what can be extrapolated from them. This is true for formal research studies and, e.g., breed club surveys. Sometimes conflicting results are due to the different approaches or inaccurate data. However, usually, there is some useful information, if we are careful in how we interpret findings.   As we develop this section on DogWellNet we hope to assist stakeholders in assembling the best picture of health and disease in specific breeds, and dogs in general. Through this we will also identify gaps - areas where our understanding is lacking - and this will help inform new studies and research.         

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Barbara Thiel graciously provided DWN's community with a book review - a great read for breed managers and breeders.   "Managing Breeds for a Secure Future: Strategies for Breeders and Breed Associations"
by D. Phillip Sponenberg, Jeannette Beranger and Alison Martin Originally published in 2007, Second Edition 2017

Dr Dan O’Neill
MVB BSc(hons) GPCert(SAP) GPCert(FelP) GPCert(Derm) GPCert(B&PS) MSc(VetEpi) PhD MRCVS

• VetCompass: Unweaving the rainbow of canine health (PPT)
• VetCompass: Unweaving the rainbow of canine health (PDF)

 

Jerold S Bell DVM (jerold.bell@tufts.edu) Cummings School of Veterinary Medicine at Tufts University presented this article at the 2019 AKC Canine Health Foundation National Parent Club Canine Health Conference. The article has been reprinted here with the written permission of the author.

Effective canine health surveillance systems can be used to monitor disease in the general population, prioritise disorders for strategic control and focus clinical research, and to evaluate the success of these measures. The key attributes for optimal data collection systems that support canine disease surveillance are representativeness of the general population, validity of disorder data and sustainability. Limitations in these areas present as selection bias, misclassification bias and discontinuation of the system respectively. Canine health data sources are reviewed to identify their strengths and weaknesses for supporting effective canine health surveillance. It is concluded that active collection systems using secondary health data provide the optimal resource for canine health surveillance.  

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See Jerold Bell's presentation at the 2019 AKC-CHF Parent Club Conference. This article is for breeders and Breed Club Health management teams. The take home message is an improved understanding of selection of dogs for breeding.