The spread of SARS-Covid-19 virus has impacted the world as it continues to raise questions on the long-term impacts. With the absence of historic/big data sets, digital public health surveillance measures are informed via modelling using real-time data, which is collected and validated by public health agencies; and also aggregated/merged with self/open reported data by the public, via mobile apps and social media channels. This chapter informs on such conduits (using two case studies: Australia and Canada) that enabled AI-based solutions for informing public health strategies. Blue tooth technology used in contact tracing apps seems to allay privacy concerns to an extent, in both countries. Real-time streamed data collection to train predictive models and combining AI methods with active learning seems to be the way forward.