Companion dog welfare information in the United States is not well documented. Efforts towards understanding companion animal welfare in the United States has increased in recent years. Comparison area data are also not well documented as the ability of animal services organizations to report data remains divided through organizational barriers and funding restrictions. This dissertation's investigation focused on data directly related to an individual animal’s welfare status (e.g., body condition, health assessment information), known as animal-based welfare indicators, and the application towards veterinary community outreach program development. To begin, an extensive literature review was performed on the history of companion animal services, control, and sheltering in the United States, companion animal shelter admission and disposition in the United States, animal welfare assessment frameworks, and veterinary community outreach programs. This study integrated applicable animal welfare assessment frameworks to assess the welfare of dogs admitted to open-admission U.S. animal services organizations using animal-based welfare indicators that dogs exhibit during a health or behavioral assessment. The next chapter utilized machine-assisted data mining to extract the previously mentioned animal-based welfare indicators from retrospective dog admission data collected between January 1, 2015, and December 31, 2019, by Athens-Clarke County Animal Services (ACCAS) in Athens, GA. Animal-based welfare indicators aid in strategic decision-making on the best way to allocate limited resources. The final research chapter described how shelter population metrics, animal-based welfare indicators, and integrated human and companion animal data can be applied to develop veterinary community outreach programs using admission data collected by open-admission animal shelters. The results of this dissertation contribute to published companion animal welfare assessments and veterinary outreach program development.
