First quantitative assessment of the effects of parasite control in dogs and cats in the UK.

Abstract

BACKGROUND: Dogs and cats in the UK are routinely exposed to a range of internal and external parasites that can adversely affect their health and welfare. Among endoparasites, roundworms and lungworms are of particular concern, while ectoparasites such as fleas and ticks remain persistent veterinary challenges. Although preventive parasiticide use is widespread, its broader health and economic benefits have not been comprehensively quantified. Moreover, evolving parasite epidemiology and increasing scrutiny of the environmental impacts of some treatments have prompted debate about their continued use. This study presents a preliminary modelling framework designed to estimate the health and economic benefits of parasite prevention in UK companion animals, focusing on averted infections and associated veterinary cost savings. METHODS: A spreadsheet-based model was developed using available data on parasite prevalence, parasiticide usage, treatment frequency, and estimated veterinary costs, supplemented by expert consultation. Two scenarios were assessed: (A) current parasiticide coverage, and (B) optimal coverage assuming full adherence to recommended treatment guidelines. RESULTS: Preliminary findings suggest that existing parasite control measures targeting Toxocara canis, Toxocara cati, Angiostrongylus vasorum, fleas, and ticks prevent approximately 5.5 million infections in UK dogs and cats each year. Under optimal compliance, the number of averted infections could increase by 70.6%, reaching 9.3 million annually. Economically, current prevention practices are estimated to save UK households around £53 million per year in veterinary costs, with potential savings rising to £95.2 million under optimal coverage and reduced parasite prevalence. CONCLUSIONS: These findings underscore the substantial health and economic value of preventive parasite control in UK pets. While the model relies on simplified assumptions and available data that may overrepresent higher-risk populations, it provides a valuable foundation for future refinement. Incorporating more granular epidemiological, geographical, and seasonal data will enhance precision. As a preliminary framework, this model reinforces the importance of preventive strategies and highlights the potential for even enhanced impact through improved compliance and targeted interventions.