Predicting cholera using remote sensing data: a glimpse into the future
Cholera remains a significant public health concern globally, with an estimated 1.3 to 4.0 million cases and 21,000 to 143,000 deaths annually (WHO). Despite advancements in medical science and public health infrastructure, cholera continues to pose a threat, particularly in regions with inadequate access to clean water and sanitation.
But there are signs of hope. Remote sensing data are revolutionising the prediction of cholera outbreaks, with a number of strong examples in Africa.
Why cholera is still a concern
Cholera, caused by the bacterium Vibrio cholerae, is an acute diarrheal disease that can be fatal within hours if untreated. The disease is primarily spread through contaminated water and food, making it prevalent in areas with poor sanitation and limited access to clean water.
The WHO reports that cholera outbreaks are often linked to environmental factors such as floods, droughts and population displacement. In Africa, the situation is particularly dire, with the continent experiencing some of the highest cholera case fatality rates globally.
Remote sensing data in cholera prediction
Remote sensing involves the use of satellite or aerial imagery to collect information about the Earth's surface. This technology has proven invaluable in predicting cholera outbreaks by monitoring environmental conditions that favour the proliferation of Vibrio cholerae.
Remote sensing data can track changes in sea surface temperature, precipitation, water quality and chlorophyll concentrations to forecast cholera outbreaks with significant accuracy. There have been a number of notable cases of using satellite data to predict cholera outbreaks in coastal regions of Africa.
Case studies from Africa
Mozambique: Mozambique has been a hotspot for cholera outbreaks due to its extensive coastline and frequent cyclones. Researchers have used remote sensing data to monitor sea surface temperatures and chlorophyll levels, which are indicators of plankton blooms that harbour Vibrio cholerae.
This approach has allowed for the prediction of cholera outbreaks with a high degree of accuracy, facilitating early warning systems and targeted public health responses.
Democratic Republic of the Congo (DRC): Remote sensing data have been combined with ground-based surveillance to predict cholera outbreaks in the Great Lakes region.
By monitoring rainfall patterns, river discharge, and water quality, health officials have been able to anticipate cholera outbreaks and implement preventive measures, such as distributing water purification tablets and setting up emergency treatment centers.
Malawi: Satellite remote sensing data has been used to monitor inland cholera outbreaks using proxy variables such as land surface temperature, precipitation, and information on water infrastructure.
Harnessing the power of Earth Intelligence
Scientists are now collaborating with several agencies in Africa to translate findings into actionable knowledge. To facilitate this, we have developed a train-the-trainer type of course module for those interested in understanding our prediction models, interpreting results, and making decisions across various temporal and spatial scales.
This on-demand course allows stakeholders to request information from our research group, after which we set up personalised meetings (usually through Zoom) to go through the course material.
Our ultimate objective is to provide a real-time assessment of when and where cholera risk is likely to pose a threat to human populations. For instance, we organised a cholera train-the-trainer workshop in Nairobi, Kenya, which was attended by about 50 participants.
The future of cholera in human populations
The future trajectory of cholera in human populations is influenced by multiple factors, including environmental changes, urbanisation and advancements in public health infrastructure. Environmental alterations, such as increased flooding and elevated temperatures, can intensify conditions conducive to cholera outbreaks. However, the integration of remote sensing data with machine learning algorithms presents a promising approach for enhancing cholera prediction and prevention.
Investments in water, sanitation, and hygiene (WASH) infrastructure are pivotal in mitigating cholera incidence. The WHO underscores that access to safe drinking water and improved sanitation facilities constitutes the most effective long-term strategy for cholera prevention. Furthermore, the development and deployment of oral cholera vaccines offer immediate protection in high-risk regions.
Despite cholera's persistent public health challenge, advancements in remote sensing technology provide new opportunities for outbreak prediction and prevention. By leveraging satellite data and machine learning, public health officials can forecast cholera outbreaks and implement timely interventions, thereby saving lives and alleviating the burden of this lethal disease.
Read more about the work of the GEO Health Community of Practice.