[Paper Review] How to restart? An agent-based simulation model towards the definition of strategies for COVID-19 "second phase" in public buildings

Marco D’Orazio, Gabriele Bernardini+1 more|arXiv (Cornell University)|Apr 27, 2020

COVID-19 epidemiological studies51 references39 citations

TL;DR

An agent-based model to evaluate strategies for reopening public buildings during COVID-19, focusing on mask use, occupancy limits, and access control, calibrated with Diamond Princess data and applied to a university campus area.

ABSTRACT

Restarting public buildings activities in the "second phase" of COVID-19 emergency should be supported by operational measures to avoid a second virus spreading. Buildings hosting the continuous presence of the same users and significant overcrowd conditions over space/time (e.g. large offices, universities) are critical scenarios due to the prolonged contact with infectors. Beside individual's risk-mitigation strategies performed (facial masks), stakeholders should promote additional strategies, i.e. occupants' load limitation (towards "social distancing") and access control. Simulators could support the measures effectiveness evaluation. This work provides an Agent-Based Model to estimate the virus spreading in the closed built environment. The model adopts a probabilistic approach to jointly simulate occupants' movement and virus transmission according to proximity-based and exposure-time-based rules proposed by international health organizations. Scenarios can be defined in terms of building occupancy, mitigation strategies and virus-related aspects. The model is calibrated on experimental data ("Diamond Princess" cruise) and then applied to a relevant case-study (a part of a university campus). Results demonstrate the model capabilities. Concerning the case-study, adopting facial masks seems to be a paramount strategy to reduce virus spreading in each initial condition, by maintaining an acceptable infected people's number. The building capacity limitation could support such measure by potentially moving from FFPk masks to surgical masks use by occupants (thus improving users' comfort issues). A preliminary model to combine acceptable mask filters-occupants' density combination is proposed. The model could be modified to consider other recurring scenarios in other public buildings (e.g. tourist facilities, cultural buildings).

Motivation & Objective

• Motivate operational measures to avoid a second wave in buildings with continuous occupancy and potential overcrowding.
• Develop an agent-based model to simulate movement and virus transmission under proximity- and exposure-time-based rules.
• Calibrate the model with experimental data (Diamond Princess) and apply it to a real university campus case-study.
• Assess the impact of masks, occupancy limits, and access-control strategies on infection spread.

Proposed method

• Construct an agent-based model that jointly simulates occupants' movement and virus transmission.
• Implement probabilistic rules for proximity-based and exposure-time-based transmission inspired by international health guidelines.
• Define scenarios by varying building occupancy, mitigation strategies, and virus-related parameters.
• Calibrate the model using Diamond Princess data and validate on a university campus case-study.
• Provide a preliminary approach to combine mask filter effectiveness with occupants’ density.

Experimental results

Research questions

• RQ1 How do occupancy limits and access-control measures affect COVID-19 spread in long-occupied public buildings?
• RQ2 What is the relative impact of different mask types and densities on infection dynamics in the modeled environments?
• RQ3 Can the model reproduce observed transmission patterns when calibrated with Diamond Princess data and applied to a university campus scenario?

Key findings

• Mask use appears to be a paramount strategy for reducing spread under initial conditions.
• Capacity limitation can support mask-wearing by allowing a shift from higher-filtration (FFPk) masks to surgical masks for occupants.
• A preliminary model suggests a feasible combination of mask effectiveness and occupant density to mitigate infections.
• The framework can be adapted to other public buildings beyond the case-study setting.