To be sure, being able to forecast epidemics and disease patters won’t be easy. If you think that weather is hard to predict, given all the variables of temperature, air moisture, atmospheric pressure, and the like, imagine predicting disease outbreaks, which are influenced by something much more complex: humans. With our diverse cultures, economic statuses, religions, friends, leaders, and a host of other inputs, human behavior is notoriously difficult to map, yet it has a huge impact on how diseases spread.
Another challenge is that current disease-monitoring systems rely on various sources of data, including patient interviews, medical provider reports, and lab tests, which are sent up a bureaucratic reporting chain and aren’t available to researchers for weeks — or longer. In the time of Covid-19, that timeline has accelerated, but too often when there’s no immediate crisis, by the time the information is made public, it’s not very useful.
Real-time data sources such as social media, cellphone data, satellite imagery, and other data streams can help close this gap.
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