FAU Smart City Project Paves the Way for Forecasting COVID-19 Infection Transmission

Researchers are exploring the untapped potential of emerging smart cities to enable hyper-contextualized computational epidemiology to tackle COVID-19. The idea is to partner with the computational epidemiology community to integrate evidence-based models of COVID-19 transmission with hyper-local mobility data to provide place-specific forecasts of disease transmission. When these tools are integrated into city planning efforts, they will provide real-time insights into how mobility changes within the city affect the local population’s susceptibility to future outbreaks.

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‘Are Noncommunicable Diseases Communicable?’ Rutgers Experts Available to Discuss Paper in Science Today

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