Insights about the Epidemiology of Dog Bites in a Canadian City Using a Dog Aggression Scale and Administrative Data

Abstract

Dog bites are a public health concern that also implicates animal welfare, with negative outcomes such as rehoming or euthanasia for the animals responsible. Previous research has shown that the severity of dog-bite injuries reflects multiple factors, including the degree of inhibition exhibited by dogs and how people behave towards dogs. This study utilizes an objective dog bite injury assessment tool: The Dunbar aggression scale. Trained officers employed by The City of Calgary systematically use the Dunbar scale whenever investigating dog-bite complaints. We analyzed The City of Calgary's administrative data on confirmed dog-bite injuries in people, 2012-2017, with a multivariable generalized ordered logistic regression model. Severe dog-bite injuries occurred more frequently in the family home than in any other setting. Young children, youths and older adults were at higher risk of more serious bites than adults. There has been a decreasing trend in the probability of a high or medium severity bite, and an increasing trend in the probability of a low severity bite since 2012. These results indicate that greater public awareness regarding dog-bite injuries is needed. Consideration should be given to campaigns targeted towards different demographics, including older adults, to provide an understanding of dog behaviour and to emphasize the need to supervise children closely in the presence of all dogs at all times, including family dogs in the home environment. Given that dog-bite injuries are not just a public health issue, but also an animal welfare issue, we endorse One Health responses in educational campaigns, policy development, and professional practice.

Keywords: Dunbar scale; One Health; animal welfare; bite prevention; dog aggression; dog bite; dogs; wounds and injuries.

Figure 1

Predictive margins for the different severity incidents depending on the breed grouping and controlling for other variables in the model.

Figure 2

Predictive margins for the different severity incidents depending on the incident location and controlling for other variables in the model.

Figure 3

Predictive margins for the different severity incidents depending on the sex of the dog and controlling for other variables in the model.

Figure 4

Predictive margins for the different level of dog chase/bite incidents depending on the victim age category and controlling for other variables in the model.

Figure 5

Predictive margins for the different severity incidents depending on the victim age category and controlling for other variables in the model.

Figure 6

Predictive margins for the different severity incidents depending on the year and controlling for other variables in the model.

Figure 7

Predictive margins for the different severity incidents depending on the incident location and the victim age and controlling for other variables in the model.