## 1 Introduction  
Extensive damage and structural collapse observed in Italian school buildings during past seismic events have pointed out the need for seismic risk mitigation programs. These should identify the most vulnerable building typologies and reduce earthquake-related economic losses and casualties through adequate seismic retrofit strategies. The collapse of a school in San Giuliano di Puglia during the 2002 Molise earthquake in Italy, which caused 30 fatalities, is a key example of the seismic vulnerability of the existing Italian school building stock ([PERSON] et al. [1]). The vulnerability of existing public buildings is not only related to structural components but also to all the non-structural components within it that could cause fatalities and economic losses. Adequate seismic performance of non-structural components should indeed be achieved to ensure safe public buildings, as also pointed out in [2, 3]. Simplified or advanced methodologies to assess the safety of non-structural components [4] would ensure a higher level of safety, avoiding dramatic events, such as the death of a student in a school building in Rivoli (Italy) [4] caused by the collapse of a classroom ceiling. The need for a seismic risk identification scheme for Italian school buildings, comprising both structural and non-structural elements, becomes therefore evident. In line with this, the regional interventions for the infrastructural and seismic upgrading of school buildings were approved by the decree (n\({}^{\circ}\) 943 23 December 2015) of the Italian Ministry of Education, University and Research, following years of dedicated research on the seismic vulnerability of Italian school buildings and the need to prioritize rehabilitation interventions. Some examples include the risk-management framework to prioritize rehabilitation interventions for Italian school buildings, proposed by [PERSON] et al. [5] or the research project \"Progetto Scuole\", which carried out a comprehensive structural performance and retrofitting assessment of typical Italian school buildings, from a comprehensive database of approximately 49,000 school buildings [6]. Data related to structural behavior, as well as other features concerning non-structural component typologies and their quantities, were collected, allowing the identification of representative case-study school buildings in order to perform detailed seismic assessment and loss estimation studies. Despite the very large amount of data that can be collected for detailed seismic assessments and economic loss estimation, the uncertainty related to the masonry infill properties is expected to significantly affect their seismic response and risk. Their full characterization and the definition of a mechanical model that represents their real behavior under seismic loads is particularly complex. Such associated uncertainty should thus be properly accounted for in the collapse assessment of existing structures when detailed nonlinear structural analysis methodologies are adopted. In this sense, the collapse assessment of existing structures should account for both aleatory and epistemic uncertainties: the former is quantified by means of a selected ground motion set, while the latter requires a set of model realizations [7; 8; 9; 10], defined from a random variable set, to propagate the modeling uncertainty in the numerical analysis. Several studies have investigated and quantified the dispersion in the seismic response of existing RC buildings due to epistemic uncertainty surrounding the RC members, whereas less attention was paid to the impact of the uncertainty related to both the premature shear failure of poorly detailed columns and the variability of masonry infill properties. Recently, [PERSON] and [PERSON] [11], using the Correlated Latin Hypercube Sampling method proposed by [PERSON] et al. [12], have investigated the epistemic uncertainty of existing RC buildings built in Italy before the 1960s, with different structural configurations (bare, infilled, and pilotis frames).