One of the main goals of modern housing is to ensure living comfort for users. Modern BIM-based house design involves creating a digital, three-dimensional model of a building containing all the information needed to support an integrated design. In addition, modern buildings are being equipped with new smart devices that can communicate with each other, exchanging information and data through the Internet of Things (IoT) paradigm. Integrating BIM and IoT leads to the creation of the so-called Digital Twin (DT), a digital copy of a real element, which, through the use of information, may provide real-time monitoring and management. This paper aims to introduce a methodology that enables the integration of BIM and the IoT to conduct a predictive study of living comfort. In particular, the proposed method includes using an IoT-based platform to collect and store sensor data and software to integrate this data within the BIM environment. The case study involved the implementation of a DT using a BIM model of a real building, from which a real-time output of the information provided by the sensors can be obtained. This information may suitably be used for a predictive study of living comfort. One of this methodology’s strengths lies in its versatility, as it can be applied not only for comfort assessment but in all phases of a building’s life, from its design to its decommissioning and structural or energy monitoring.

Aim: Despite huge efforts in developing specific drugs, vaccination represents the only effective strategy against COVID-19. Efficacy and safety of the COVID-19 vaccines were established during clinical trials. Nonetheless, it is very important to perform continuous surveillance. This observational study aimed to report potential Adverse Events Following Immunization (AEFI) following the first dose of two different COVID-19 vaccines, BNT162b2 and AZD1222. Methods and Results: Subjects who underwent vaccination at the vaccine center of the University Hospital of Salerno, Italy, were interviewed using an ad hoc questionnaire. AZD-vac group (n = 175) who received AZD1222 had a higher number of AEFI than the BNT-vac group (n = 1613) who received BNT162b2 (83% vs. 42%). The most frequent AEFI associated with AZD1222 and BNT162b2 were fever and pain at the injection site, respectively. The AZD-vac group used drugs to contrast AEFI more frequently than the BNT-vac group. In the BNT-vac group, there was a higher incidence of AEFI in women than in men (26.2% vs. 15.8%, p = 0.01), while no gender-related difference was observed in the AZD-vac group. Conclusions: AZD1222 and BNT162b2 vaccines show a good safety profile. Based on our results and literature data, there are no reasons to justify the reluctance that persists towards immunization.