Application of the WHO Workload Indicators of Staffing Need (WISN) method to estimate workforce requirements in...

This study presents the application of the World Health Organization's "Workload Indicators of Staffing Need" (WISN) methodology to the Prevention Departments of Local Health Units (LHUs) in Italy, with a focus on the Campania Region. These departments are responsible for essential public health activities, particularly food safety and animal health, which differ significantly from traditional healthcare settings because of their decentralized and inspection-based nature.

The Campania Region developed a performance-based staffing model using WISN principles, introducing two key units, the unit of individual performance (U.I.P.) and the unit of structural performance (U.P.S.), to quantify the actual workload and staffing needs. The U.I.P. was defined as the time required for an operator to perform a simple inspection (4 h, including ancillary activities), while the U.P.S. was calculated by aggregating U.I.P.s at structure level and applying correction factors (such as the legal requirement to perform inspections in pairs), representing an original adaptation of the WISN approach to the Italian veterinary and food safety prevention setting. The model accounts for institutional duties, ancillary tasks, territorial logistics, and regulatory constraints such as the need for paired inspections.

Applied to 2022 data, the system identified a substantial staffing shortfall, with an estimated overall deficit of approximately 76 full-time equivalents (FTEs) across the Campania LHUs, ranging from about 18 missing FTEs in some urban LHUs to over 38 FTEs in predominantly rural or livestock-oriented areas. The most critical gaps were consistently observed in the animal health sector (SA), which concentrated the majority of missing FTEs and highlighted a structural shortage of veterinary staff dedicated to animal health activities.

The model, acknowledged by the Italian Court of Auditors as an excellent tool for rationalising food safety and veterinary public health services, offers an evidence-based, scalable solution for optimising human resource allocation. Its success depends on continued data integration, training, and formalization through regional and national agreements. This approach lays the groundwork for more efficient, accountable, and transparent management of public health personnel.