Forecasting Cholera Outbreaks from Space

When most people think of climate change, it is likely they will picture ice caps melting or extreme weather events. Not many people associate the impacts of climate change with health and well-being.

Full blog found at Space4Climate.

The reality is that the Earth’s changing climate is also affecting our health. The health of our planet and of its people are intrinsically interlaced and so, as the world changes, so too does the dynamic of climate-sensitive diseases.

Scientists are now trying to improve understanding of how changes in climate are already, and will in the future, impact upon human health, including threats from pathogens, viruses and diseases. This is where space comes in – satellites provide us with a range of environmental datasets to allow us to start drawing connections between outbreaks of climate-sensitive infectious disease, such as cholera, and climate anomalies.

Around 1.3 billion people are currently at risk of cholera, with an estimated 2.9 million cases annually. On the densely populated coast of India, home to approximately 200 million people, cholera is endemic. This means there is a long history of cholera outbreaks, appearing year after year, and seasonally, which suggests that there is more at play than just human-to-human transmission.

Studies have discovered that certain environmental variables drive the coastal distribution and seasonal dynamics of the bacteria that causes cholera (Vibrio cholerae). The bacteria exist naturally in coastal waters, however cholera outbreaks are associated with optimum water temperatures and salinities, and the presence of plankton (which the bacteria can latch on to, increasing survival). While it wouldn’t be feasible to collect water samples around the whole of the Indian coast to survey the dynamics of cholera bacteria, satellites monitoring the Earth are providing high-resolution global data on environmental variables that drive the bacteria, daily.

Working with Marie-Fanny Racault, from the Plymouth Marine Laboratory, we set out to explore whether we could forecast cholera outbreaks on the Indian coast, using environmental data, machine learning (ML) and artificial intelligence (AI). We created a model trained on historic environmental data, including satellite data, and previous cholera outbreak data.

The model was able to detect 89.5% of outbreaks in the test dataset. We also found that chlorophyll-a concentration – a pigment marker for phytoplankton presence – as well as salinity and temperature, were the strongest predictors of cholera outbreaks in our dataset.

Read full blog at Space4Climate.