Direct Observation of Dog Density and Composition during Street Counts as a Resource Efficient Method of Measuring Variation in Roaming Dog Populations over Time and between Locations

Abstract

Dog population management is conducted in many countries to address the public health risks from roaming dogs and threats to their welfare. To assess its effectiveness, we need to monitor indicators from both the human and dog populations that are quick and easy to collect, precise and meaningful to intervention managers, donors and local citizens. We propose that the most appropriate indicators from the roaming dog population are population density and composition, based on counting dogs along standard routes using a standard survey protocol. Smart phone apps are used to navigate and record dogs along standard routes. Density expressed as dogs seen per km predicts the number of dogs residents will encounter as they commute to work or school and is therefore more meaningful than total population size. Composition in terms of gender, age and reproductive activity is measured alongside welfare, in terms of body and skin condition. The implementation of this method in seven locations reveals significant difference in roaming dog density between locations and reduction in density within one location subject to intervention. This method provides a resource efficient and reliable measure of roaming dog density, composition and welfare for the assessment of intervention impact.

Keywords

• dog
• stray dog
• dog population management
• animal welfare
• survey
• population density
• strip transect
• monitoring
• evaluation