In this paper, a method to study how the design of indoor spaces and people's movement within them affect disease spread is proposed by integrating computer-aided modeling, multi-agent movement simulation, and airborne viral transmission modeling. Topologicpy spatial design and analysis software is used to model indoor environments, connect spaces, and construct a navigation graph. Pathways for agents, each with unique characteristics such as walking speed, infection status, and activities, are computed using this graph. Agents follow a schedule of events with specific locations and times. The software calculates "time-to-leave" based on walking speed and event start times, and agents are moved along the shortest path within the navigation graph, accurately considering obstacles, doorways, and walls. Precise distance calculations between agents are enabled by this setup. Viral aerosol concentration is then computed and visualized using a reaction-diffusion equation, and each agent's infection risk is determined with an extension of the Wells-Riley ansatz. Infection risk simulations are improved by this spatio-temporal and topological approach, incorporating realistic human behavior and spatial dynamics. The resulting software is designed as a rapid decision-support tool for policymakers, facility managers, stakeholders, architects, and engineers to mitigate disease spread in existing buildings and inform the design of new ones. The software's effectiveness is demonstrated through a comparative analysis of cellular and open commercial office plan layouts.

A Viral Infection Risk Indoor Simulator (VIRIS) has been developed to quickly assess and compare mitigations for airborne disease spread. This agent-based simulator combines people movement in an indoor space, viral transmission modelling and detailed architectural design, and it is powered by topologicpy, an open-source Python library. VIRIS generates very fast predictions of the viral concentration and the spatiotemporal infection risk for individuals as they move through a given space. The simulator is validated with data from a courtroom superspreader event. A sensitivity study for unknown parameter values is also performed. We compare several non-pharmaceutical interventions (NPIs) issued in UK government guidance, for two indoor settings: a care home and a supermarket. Additionally, we have developed the user-friendly VIRIS web app that allows quick exploration of diverse scenarios of interest and visualisation, allowing policymakers, architects and space managers to easily design or assess infection risk in an indoor space.

We study viral transmission in crowds via the short-ranged airborne pathway using a purely model-based approach. Our goal is two-pronged. Firstly, we illustrate with a concrete and pedagogical case study how to estimate the risks of new viral infections by coupling pedestrian simulations with the transmission algorithm that we recently released as open-source code. The algorithm hinges on pre-computed viral concentration maps derived from computational fluid dynamics (CFD) simulations. Secondly, we investigate to what extent the transmission risk predictions depend on the pedestrian dynamics model in use. For the simple bidirectional flow under consideration, the predictions are found to be surprisingly stable across initial conditions and models, despite the different microscopic arrangements of the simulated crowd, as long as the crowd evolves in a qualitatively similarly way. On the other hand, when major changes are observed in the crowd's behaviour, notably whenever a jam occurs at the centre of the channel, the estimated risks surge drastically.

It might seem strange to be making predictions about 2021, when it's far from certain how the remainder of 2020 is going to play out. No-one foresaw the world-changing events of this year, but one thing is clear: tech has been affected just as much as every other part of our lives. Another thing that is clear is that today's most important tech trends will play a big part in helping us cope with and adapt to the many challenges facing us. From the shift to working from home to new rules about how we meet and interact in public spaces, tech trends will be the driving force in managing the change. In many ways, Covid-19 will act as a catalyst for a whole host of changes that were already on the cards anyway, thanks to our increasingly online and digital lives.

It might seem strange to be making predictions about 2021, when it's far from certain how the remainder of 2020 is going to play out. No-one foresaw the world-changing events of this year, but one thing is clear: tech has been affected just as much as every other part of our lives. Another thing that is clear is that today's most important tech trends will play a big part in helping us cope with and adapt to the many challenges facing us. From the shift to working from home to new rules about how we meet and interact in public spaces, tech trends will be the driving force in managing the change. In many ways, Covid-19 will act as a catalyst for a whole host of changes that were already on the cards anyway, thanks to our increasingly online and digital lives.