Real-world data (RWD) will prepare us for the next pandemic
19 April 2022
- Machine-learning techniques within a shared database could generate predictive insights, showing the patterns in communities that precede outbreaks and helping dictate where and when lockdowns and social distancing orders should be implemented
- For example, Germany is using de-identified tracking apps to identify anomalies in day-to-day habits, such as regularly active users skipping exercising or walks to predict when a community is likely about to experience an outbreak—and prevent it before it worsens
- The experience of Israel offers a great example of how real-world data can be analysed and shared. By swiftly rolling out the Pfizer vaccine to more than half its population and tracking the results, the country was able to demonstrate a dramatic decrease in serious infections and hospitalizations as a consequence of the vaccine