A conceptual framework for holistic goal setting for companion animal populations: a balanced cat population case study

Companion animals are part of modern society, yet the conditions they experience are highly context-specific; they can vary across populations, regions and time and are impacted by people and other animals. This paper merges considerations from different perspectives to open new discussions around setting population goals for companion animals that reflect this complexity. It critiques the limitations of purely numbers-based approaches, which often fail to capture the nuances of animal welfare and the specific environments these animals inhabit. Instead, it introduces the concept of a balanced population that relates companion animals, humans and other animals and sustainability with exogenous factors. Applied to cat populations in the UK, the framework highlights key interconnected themes for achieving balance: acquisition methods, health, husbandry, interactions with other animals including humans and genetic considerations. It considers factors from these themes through the context of three lenses: the target population (in this case, cats), humans and other animals and environmental sustainability, in the manner of a One Health and Welfare approach. It also considers the wider context in which cats live, including the socio-political and environmental situation. Rather than prescribing fixed interventions, the framework serves as a flexible tool to identify context-specific goals, rooted in understanding interlinks within communities and evolving over time. It encourages a shift in animal welfare management from reactive strategies to visionary planning. While the framework lays the groundwork for more integrated decision-making, further development is needed to translate it into actionable tools and interventions. As companion animals remain central to society, this approach offers a valuable foundation for research and policy, promoting a deeper understanding of what constitutes a balanced population.