One digital technology from the article that I find particularly interesting is web-based epidemic intelligence tools and online syndromic surveillance driven by machine learning.
How it works: These tools collect data from many digital sources and conduct pre-processing and filtering. Machine learning is used to detect signals in this data by identifying symptom-related search queries, recognizing clusters of news and social media posts about respiratory symptoms, and forecasting trends. The outputs are shown on dashboards to help public health decisions.
How important it is: A Digital signal can provide an early warning and alert of rising transmission than a formal report. Once the infrastructure is set up, these tools can continuously monitor a large volume of data across the globe with low incremental cost compared to traditional surveillance systems that have delays. These tools enable public health authorities to make decisions for effective interventions.
But some limitations remain.