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Updated: May 6, 2026

Experimental Paradigm for Measuring the Effects of Self-distancing in Young Children
Published on: March 1, 2019
Implications for distancing measures on in-person school and work attendance from Italian post-pandemic social
Lorenzo Lucchini1, Valentina Marziano2, Filippo Trentini3
1DONDENA Centre for Research on Social Dynamics and Public Policy, Bocconi University, Milano, Italy.
Background:
The collection of updated post-COVID-19 data on social contacts is critical for future epidemiological assessment and evaluation of non-pharmaceutical interventions.
Methods:
We conducted two waves of an online survey in Italy (March 2022 and March 2023), collecting representative data on direct (verbal/physical) and indirect (indoor co-location) contacts. Using a generalised linear mixed model, we analysed social contact determinants and the impact of work-from-home and distance learning on reducing a pathogen's reproduction number (R). Additionally, we calibrated an age-structured model to the 2023-2024 influenza A epidemic in Italy to explore the impact of alternative in-person attendance scenarios on infection attack rates.
Results:
We find that in-person attendance significantly increases contacts: adults attending in person have 1.69 times (95%CI: 1.55-1.83) more contacts than those staying home, while children/adolescents 2.36 (95%CI: 1.96-2.84). Limiting in-person work alone marginally affects R, whereas combining work-from-home with distance learning (from primary school onwards) reduces R by up to 23.2% (95%CI: 13.7-30.1%), with minimal additional benefit from suspending early childcare. In the influenza A case study, seasonal infection attack rates range from 14.7% (95%PI: 12.8-16.5%) under full in-person attendance to <0.2% under the most restrictive scenario. Moderate interventions (suspension of tertiary education and work-from-home) reduce attack rates by up to one fourth among adults (15-64 years) and one sixth among older individuals.
Conclusions:
This study provides post-pandemic contact matrices for Italy, essential for modelling transmission of respiratory pathogens, and quantitative evidence on the epidemiological impact of targeted physical distancing measures, thereby supporting future policy design.
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