A toolkit combining computer modelling research and urban planning could help societies respond to infectious diseases and combat future pandemics.

Scientists from Imperial College London, in collaboration with Southeast University and the University of Chinese Academy of Sciences, have produced a cutting-edge toolkit for urban designers, decision-makers and practitioners to help evaluate the impacts of different urban-design interventions on the transmission of infectious diseases, including COVID-19. 

To develop the toolkit, scientists from the Department of Chemical Engineering and the Faculty of Medicine worked with their overseas colleagues to conduct a multidisciplinary systematic review of state-of-the-art literature, exploring the research at the interface of infectious diseases, urban design, and computational modelling. The field of computational modelling includes computer models and simulations, statistical models, artificial intelligence algorithms and computer-aided decision-making techniques.

The study, published in Progress in Planning, investigates to what extent urban designers can consider and support the fight against infectious diseases whilst designing a healthy and resilient built environment.

Urban design for improving public health

Public health issues are an inherent challenge to cities and planning has been an important means of solving such issues, most recently during the COVID-19 pandemic.

Urban design is the process of making better places for people, by considering spatial scales ranging from buildings, streets, public spaces, neighbourhoods, districts to entire cities. Urban design offers solutions to public health problems such as non-pharmaceutical interventions. These include short term responses such as environmental and pandemic infrastructure and the treatment of medical waste, and long-term responses such as decreased population density and enhanced public services for improved access to amenities.

To support urban designers in responding to infectious diseases, computer models can help designers and decision makers evaluate possible interventions against other public health resilience or sustainability metrics.

The novel toolkit

In their study, the team assembled researchers from the fields of urban design, architecture, geography, infectious disease, and computer science to collectively identify relevant frameworks and keywords for a systematic literature review. 

From this, they were able to compile a toolkit mapping out possible design interventions, the relevant infectious diseases and computer modelling tools for the whole urban design process.

One possible use of the toolkit is to provide information about simulation models. For example, evaluating different designs of public buildings or urban transport systems and assessing the impact each would have on social distancing or the role of ventilation and air filtration. This can help to understand how design changes can influence infection rates in cities.

According to co-author Dr Koen van Dam: “We intend that this toolkit will benefit urban designers, planners, decision-makers, and computer modellers to help empower cities to develop strategies in response to COVID-19 and prepare for future uncertain disasters in pursuing and creating healthy and resilient cities.” 

Future developments

According to Dr van Dam the field is moving quickly, with new developments in research relating to Covid-specific modifications published rapidly.

He said: “It would be interesting to see how the field is changing as a result of the global pandemic and more awareness of the impacts of the built environment on diseases, as well as any long-term behavioural change we might see as a result.”

Further investigations into how changes to urban environments supporting sustainable development might also have co-benefits in the health sector, is a line of inquiry important in future research.

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‘Computational decision-support tools for urban design to improve resilience against COVID-19 and other infectious diseases. A systematic review’ by Yang et al., published on 9 March 2022 in Progress in Planning.