Cholera is a waterborne bacterial disease that infects millions each year and kills hundreds of thousands. Many coastal communities regularly deal with small cholera outbreaks and are well prepared for them. Other outbreaks however, can be much less predictable and can take communities by surprise. The majority of cases occur in developing countries and are made worse by poor sanitation and over crowding.
In May of 2017 scientists used satellite data to see whether an outbreak would occur in Yemen, and ended up unexpectedly predicting an outbreak that spread across the country the next month. As explained in Scientific American:
The team used a handful of satellites to monitor temperatures, water storage, precipitation and land around the country. By processing that information in algorithms they developed, the team predicted areas most at risk for an outbreak over the upcoming month.
Weeks later an epidemic occurred that closely resembled what the model had predicted. “It was something we did not expect,” Jutla says, because they had built the algorithms—and calibrated and validated them—on data from the Bengal Delta in southern Asia as well as parts of Africa.
Because cholera progresses so rapidly, advance warning of an epidemic would allow communities to stockpile re-hydration supplies and vaccines. This could significantly alter the deadly outcome of the disease.
