Using Precipitation Data to Assess Risk of Cholera Outbreaks
Narration: Ryan Fitzgibbons
VO: Decades of research and technology for better forecasting of the when, where and how intense a hurricane will be? But what if we could predict a disease outbreak in the wake of a storm? That's the question some researchers asked about cholera in Haiti in the aftermath of Hurricane Matthew. Cholera is a water-borne infectious disease that occurs when a person ingests food or water contaminated with the Vibrio bacterium. Cholera causes severe diarrhea, nausea, vomiting and dehydration and can lead to death if untreated. Researchers estimate that hundreds of thousands of cases are reported each year worldwide.
Colwell: The bacterium is found in world oceans globally, especially in the temperate regions and in the tropics. So in the countries less developed with infrastructure that is not the equivalent, let's say, of Europe or the United States or Canada, then the population that has to rely on river water or pond water is at risk for cholera.
VO: In addition to water insecurity, high seasonal temperatures followed by extreme rainfall, concentrated populations and a natural disaster are all conditions conducive to a cholera epidemic. This was the case for Haiti in 2010.
Colwell: The data that we were able to pull together showed that in 2010 it was the hottest summer in fifty years. And then as if that weren't enough, there was a hurricane that skirted the island, but it dumped the heaviest rainfall in fifty years.
Jutla: We tried to make an algorithm in a cohesive form to determine the risk. And then that basically provided us with the first clues on the risk of outbreak of cholera in Haiti after this earthquake. Then we used the same algorithm with improved satellite datasets from Global Precipitation Measurement mission after Hurricane Matthew struck that region again. And we were able to, in real time, predict the risk of cholera infection in human population at least four weeks in advance. We did the same thing for Yemen. We knew there was a mass movement of human population due to civil unrest in that part of the world, and then we had very heavy precipitation. And then we immediately started monitoring conditions. And that basically converged to give us a risk on where and when this disease will risk on where and when this disease will lock in on human population.
Colwell: I think we can predict and prevent and I'd like to see that happen very quickly, in the next three to five years, and I'd like to see the satellite system to be part of the regular public health tools so that we can do prediction as well as the tracking of epidemics that's done traditionally now.