A probabilistic model to evaluate the effectiveness of main solutions to COVID-19 spreading in university buildings according to proximity and time-based consolidated criteria

Abstract

Crowds in buildings open to the public can alter the occupants’ safety in different emergency conditions, including those related to a pandemic. In this sense, university buildings are one of the most relevant scenarios in which the COVID-19 event clearly pointed out the stakeholders’ needs toward safety issues, especially because of the possibility of day-to-day presences of the same users (i.e. students, teachers) and overcrowding causing long-lasting contacts with possible “infectors” in such closed environments. While waiting for the vaccine, as for other public buildings, policy-makers’ measures to limit (second) virus outbreaks combine individual’s strategies (facial masks), occupants’ capacity and access control to avoid lockdowns and ensure adequate conditions for occupants. Simulators could support effectiveness evaluations of such measures. To fill this gap, this work proposes a quick and probabilistic simulation model based on consolidated proximity and exposure-time-based rules for virus transmission (confirmed by international health organizations). The building occupancy is defined according to university schedule, identifying the main “attraction areas” in the building (classrooms, break-areas). Scenarios are defined in terms of occupants’ densities, mitigation strategies, virus-related aspects. The model is calibrated on experimental data and applied to a relevant university building. Results demonstrate the model capabilities. In the case study, occupants’ capacity limitation could support the adoption of surgical masks by users instead of FFPk masks (thus improving users’ comfort issues). Preliminary correlations to combine acceptable mask filters-occupants’ density are proposed to support stakeholders in organizing users’ presences in the building during the pandemic.

On the Effectiveness of the Measures in Supermarkets for Reducing Contact among Customers during COVID-19 Period

“…The pandemic and these control measures also have a huge impact on pedestrian dynamics at different scales, e.g., touristic urban areas [8,9] and university buildings [10,11]. In this work, we focus on supermarkets, which are kept open during the outbreak.…”

COVID-19 safe campus evaluation for universities by a hybrid interval type-2 fuzzy decision-making model

“…Sousan et al ( 2021 ), Dhama et al ( 2021 ) Reducing touch It means limiting the use of common materials, preventing contact as much as possible to reduce the virus’s spread, and ensuring the disinfection of common materials at frequent intervals. It also includes measures to reduce the number of people in the environment and to use personal protective equipment McGee et al ( 2021 ), Esmaeilzadeh ( 2022 ), World Health Organization ( 2020a ) Social distance In order to prevent the spread of the disease, it means taking measures such as keeping the number of patients at a level that will not force the health system, making capacity plans, restricting mobility, providing different entrance and exit doors, and not speaking loudly in the environment Poole et al ( 2021 ), D’Orazio et al ( 2021 ), Kobayashi et al ( 2020 ), Shen et al ( 2021 ), Byrne et al ( 2020 ), McGee et al ( 2021 ), Wilson et al ( 2020 ), Mossa-Basha et al ( 2020 ), Greenhalgh et al ( 2021 ), Fischetti et al ( 2021 ), Bartolucci et al ( 2022 ), Ugail et al ( 2021 ) Planning Training plans It covers the education plans for the personnel of higher education institutions, students, and visitors Lordan et al ( 2021 ), Wilson et al ( 2020 ), Chisita et al ( 2022 ) Emergency action plan It covers the plans made to be able to organize immediately, intervene regularly, ensure that the institution remains operational, and minimize the damages that may arise in case of a diagnosis and/or suspicion of contagious disease among staff and students Izumi et al ( 2020 ) Infection and control plans It covers the necessary arrangements and plans to minimize the risk of people encountering the virus Poole et al ( 2021 ), Shen et al ( 2021 ), Wilson et al ( 2020 ), Esmaeilzadeh ( 2022 ), Cohen et al ( 2021 ) Cleaning plans …”

“…Simulation studies have been carried out following the spread of the disease, isolation, and monitoring processes with different methods during the COVID-19 epidemic (Li and Yin 2021 ; McGee et al 2021 ; Gressman and Peck 2020 ; Sherby et al 2022 ; Junge et al 2021 ; D’Orazio et al 2021 ). Memari et al ( 2021 ) studied easier coordination and case management thanks to a nerve center established within the university.…”

Occupancy-aided ventilation for airborne infection risk control: Continuously or intermittently reduced occupancies?

“…Infectious respiratory diseases significantly affect occupants' health and society development (Desai et al 2021;Guo et al 2021;Dong et al 2022). Airborne transmission can be one of the infection routes of respiratory diseases (D'Orazio et al 2021), e.g., influenza, measles, chickenpox, smallpox, tuberculosis, MERS, SARS, and rhinovirus (Peng et al 2022). Particularly, more and more evidence supports the airborne transmission route of Corona Virus Disease 2019 (COVID-19) with the detected viruses in exhaled air and in indoor air (Tellier 2022).…”