Atlantic climate variability enables the prediction of leishmaniasis outbreaks in North Africa

Climate variability in the Atlantic Ocean can help predict cutaneous leishmaniasis outbreaks in North Africa several months in advance. This is the finding of a new study led by the Barcelona Institute for Global Health (ISGlobal), together with researchers from the Pasteur Institutes of Tunisia, Morocco and France.

The study identifies how specific climate patterns affecting rainfall across the region influence, over different time scales, the transmission of this disease and make it possible to develop a seasonal forecasting system with up to one year’s lead time.

Cutaneous leishmaniasis is a parasitic disease transmitted through the bite of phlebotomine sand flies, tiny insects commonly known as “sand flies.” Although it is not usually life-threatening, it causes skin lesions and ulcers that may persist for months or even years and can leave permanent scarring, with significant physical, psychological and social consequences.

It is estimated that there are around one million new cases worldwide each year, particularly across the Mediterranean Basin, the Middle East, Central Asia and the Americas.

Until now, early warning systems for climate-sensitive diseases had been developed mainly for tropical regions, where phenomena such as El Niño make it possible to produce forecasts several months ahead. In temperate regions, by contrast, the atmosphere has been considered far less predictable, making it difficult to develop similar tools for vector-borne diseases.

The study, published in Science Advances, shows that this limitation can be overcome by incorporating two major patterns of Atlantic climate variability: the North Atlantic Oscillation (NAO) and the Atlantic Multidecadal Variability (AMV).

The NAO is an atmospheric phenomenon that modulates winds over the Atlantic and influences winter rainfall across Europe and North Africa, while the AMV describes slow changes in Atlantic sea surface temperatures that unfold over years or even decades. The study’s findings show that the interaction between these two patterns modulates rainfall across North Africa and, indirectly, influences the evolution of leishmaniasis.

From Atlantic climate to disease transmission

Variations in Atlantic sea surface temperatures alter atmospheric circulation and the winds that transport moisture toward North Africa, thereby influencing rainfall. These rains regulate vegetation growth in desert ecosystems and, in turn, the populations of rodents that act as reservoirs for the parasite. Because cutaneous leishmaniasis depends closely on this chain of processes, its occurrence can also be predicted from Atlantic climate signals.

“The desert acts as a natural filter that reveals the Atlantic’s climate memory. Because it is influenced by fewer climate processes, it allows the Atlantic signal in rainfall patterns to be isolated much more clearly. Thanks to this, we identified a region where rainfall is remarkably predictable, the deserts of Tunisia and Morocco, and demonstrated that this predictability is also transferred to an infectious disease,” says Adrià San-José, ISGlobal researcher and first author of the study.

Building on this understanding of disease transmission, the research team developed a dynamic model that reproduces transmission of the parasite between humans, sand flies and rodents. The model integrates local temperature and rainfall with information from both the atmosphere and the Atlantic Ocean.

As a result, it was able to predict both the timing and intensity of outbreaks of Leishmania major and Leishmania tropica in Morocco and Tunisia up to 12 months in advance. In Tunisia, however, where the Atlantic’s climatic influence is weaker and more heterogeneous, improvements in forecasting were more modest.

Implications for public health

“It was widely believed that this type of forecasting was only possible in the tropics. What is remarkable is that we have identified a source of predictability in a temperate region as well and incorporated it into a model that is ready for operational use. In this respect, our study is clearly pioneering and opens up new opportunities to develop early warning systems in places where they were previously considered unfeasible,” explains Xavier Rodó, ICREA researcher at ISGlobal and senior author of the study.

The ability to anticipate risk several months in advance provides valuable time to implement preventive measures, such as vector control, management of animal reservoirs and preparation of health care systems for potential outbreaks.

Beyond leishmaniasis, the research team believes that the methodology developed could also be applied to other rainfall-modulated diseases across both Europe and North Africa.

Who’s behind this story?

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Sadie Harley

BSc Life Sciences & Ecology. Microbiology lab background with pharmaceutical news experience in oil, gas, and renewable industries.

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Robert Egan

Bachelor’s in mathematical biology, Master’s in creative writing. Well-traveled with unique perspectives on science and language.

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