Delivering Value for Money: Cost-Effectiveness of One Health Responses to Rift Valley Fever in Kenya

Abstract Rift Valley fever (RVF) is a recurring zoonotic disease in Kenya, yet little economic evidence exists to demonstrate the value of applying a One Health (OH) approach during outbreaks. This study conducted a cost-effectiveness analysis (CEA) to compare Kenya’s OH intervention with a non-OH counterfactual during RVF outbreaks between 2017 and 2021. Seven counties affected during this period – Garissa, Isiolo, Kajiado, Marsabit, Mandera, Siaya, and Wajir – were included in the analysis. Data were obtained using a standardized costing tool, official government records, and information gathered during a 2-day stakeholder workshop. Costs were estimated using an ingredient-based approach. A scenario-based analysis compared the coordinated OH response with a non-OH counterfactual. Disability-adjusted life years (DALYs) were estimated from reported human morbidity and mortality for the OH scenario and from validated counterfactual assumptions for the non-OH scenario. The total cost of the OH intervention was estimated at US 1, 095, 356. 07, compared with US 910, 427. 52 for the non-OH response. Across the outbreak period, 19 human deaths and 334 livestock deaths were recorded. The OH intervention resulted in 222. 62 DALYs, while the non-OH scenario produced 292. 63 DALYs. The incremental cost-effectiveness ratio (ICER) was US 2, 641. 84 for each of the 70 DALYs averted, which falls within the accepted cost-effectiveness range based on Kenya’s GDP per capita. Results show that the OH intervention reduced the disease burden more effectively than a non-OH approach, with 70 DALYS averted, demonstrating clear value for money. However, the higher operational cost of the OH response indicates the need to improve efficiency in resource use, strengthen subnational preparedness, and refine coordination mechanisms to optimize future OH interventions. However, as the analysis was based on constructed scenarios and stakeholder-informed assumptions, causal attribution of individual intervention components could not be established. Information © The Authors 2026