

Pietro Ceccato, Research Scientist at IRI

Pietro Ceccato, Research Scientist at IRI


Climate variability and change is an important facet of public health studies of infectious vector-borne diseases such as malaria, leishmaniasis, and rift valley fever. Many other variables, such as migration patterns, economic resources, and intervention techniques, influence the spread of such diseases, but climate data presents the unique ability to be objectively measured in ways that other data cannot be. The ability to access such data is improving as the use of satellite data has expanded and improved, allowing scientists to access information that wasn’t before possible, particularly in remote regions.

Pietro Ceccato and colleagues at the City College of New York and NASA’s Jet Propulsion Laboratory are developing new products to improve the public health community’s capacity to understand, use and demand the appropriate climate data and information to mitigate the impacts of climate on vector-borne diseases. In particular, they are working on new and improved ways to monitor water bodies in the hopes of more effectively monitoring and predicting certain diseases. Learn more about these products in the Q&A below and stop by his poster at AGU.

Last year, Ceccato explained the basics of remotely sensed data and how it helps climate and health researchers. View that post here.

Why is it important to monitor water bodies? Can you give an example of how this capability improves the ability to mitigate health impacts?

Water bodies are important to monitor because of their influence on vectors, such as mosquitos and sandflies, that transmit diseases. For example, we did research on the relationship between leishmaniasis, which is transported via the sandfly, and inundation in South Sudan. The transmission period for leishmanaias is in April-June, and we found that when the area is more inundated, meaning more water bodies, during that period, we don’t have as many cases of leishmaniasis in September through January the following year. When we don’t have inundation, there are more cases. We hypothesize, based on this result, that the flies are able to stay around longer, thus increasing the risk of biting someone and transmitting the disease.

With regard to malaria, we can detect small water bodies that are favorable breeding for mosquitoes (such as in irrigated areas). Since we don’t have many field observations, the use of remote sensing allows us to gather data at high spatial resolution over a large area. We can then use the results to determine if there is high risk for transmission, and public health officials can use this information to mitigate the risk and prepare for outbreaks.

Your research for this project focuses on East Africa. Why did you choose to work in this region?

We are part of the NASA SERVIR project, which has 3 hubs, one in Central America, one in Kenya, and one in Nepal. We work mostly in East Africa because we have many long-standing collaborations with Ministries of Health and National Meteorological Agencies in Ethiopia, Kenya, Tanzania and Madagascar. And, of course, there is the need and usefulness of climate and health information to decision makers in this region.

What exactly are the products?

We use two sets of data – one is data in the visible spectrum from the high spatial resolution LANDSAT at 30 m to detect small water bodies, and the other is passive microwave data at lower resolution of 25 km that allows us to see larger water bodies through the clouds. Inundation often occurs when there are a lot of clouds; using visible you can’t see through the clouds, but using passive we can.

We then process these datasets with algorithms that detect different combinations of channels that allow us to identify water bodies. Our final products will be maps that show the water bodies.

You’re in the process of integrating the products into the IRI Data Library and NASA’s SERVIR program. How do those systems make it easier for end-users to apply climate information, and who is then able to use the tools?

Once the products are made accessible to the user community they will have easy access to the maps. From a web browser, users like the Ministries of Health and Médecins Sans Frontières (also known as Doctors Without Borders) can visualize areas where there is inundation, and then they can make decisions based on the risk of leishmaniasis and malaria transmissions. Since the final products are simply maps of the water bodies, they require minimal training to utilize.

What are your plans for continuing this work? Are there any research questions you especially eager to address?

The research is part of a four-year project, and we just finished the first year. In the second year, we will refine the detection methods and provide the product in a more accessible way. Then we will show the users how to use the products.

We are also going to analyze the inundation data and explore links to extreme rainfall events. We would like to use this method to predict floods, which could create useful products for the International Federation of Red Cross and Red Crescent Societies.