A Synthetic Contact-Network Simulation Framework for Infection Risk and Appointment Control in Outpatient Care Facilities

Outpatient care facilities combine high patient turnover, repeated short contacts, accompanying persons, clinically vulnerable subgroups, and healthcare-worker movement across functional zones. This study develops a synthetic dynamic contact-network simulation framework to evaluate how outpatient flow-control strategies affect simulated respiratory-infection risk and service efficiency. Public descriptions of the SocioPatterns hospital-ward study were used only to shape role composition and qualitative contact heterogeneity. A parameterized outpatient process model generated time-stamped locations for patients, accompanying persons, high-risk patients, and healthcare workers over a simulated clinic day. Zone- and role-dependent temporal contacts were then coupled to a stochastic SEIR process, with 500 replications per main scenario. In the baseline scenario, mean cumulative secondary infections were 0.502 per clinic day, the probability of at least one secondary infection was 0.354, and mean waiting time was 23.1 min. Time-spaced appointments reduced mean secondary infections by 45.4–52.2% while also reducing waiting time. Accompaniment restriction reduced risk by removing non-service nodes, whereas waiting-capacity control, protected scheduling, and healthcare-worker grouping were more context dependent. The strongest combined strategy reduced mean secondary infections by 52.6% and maintained a mean waiting time of 13.6 min. These results are comparative outputs under stated assumptions, not predictions for a specific clinic. The framework provides a reproducible computational basis for testing how operational policies reshape temporal contact opportunities before local implementation.