Coupled Atlantic atmosphere-ocean variability modulates cutaneous leishmaniasis in North Africa, enabling long-lead seasonal forecasts
Abstract
Early warning systems for climate-driven diseases require predictors with sufficient lead time, a persistent challenge for many diseases and regions. While coupled atmosphere-ocean phenomena offer a potential solution, they remain largely underexploited in temperate zones. Here, we establish a multiscale connection between cutaneous leishmaniasis (CL) dynamics in North Africa, the North Atlantic Oscillation (NAO), and the Atlantic Multidecadal Variability (AMV). Beyond the NAO’s influence on seasonal rainfall, we uncover low-frequency variability in the NAO-AMV system that modulates interannual rainfall patterns in North Africa, yielding multiyear periods of high and low CL activity. To quantify this predictability, we develop a unified transmission model applied across Morocco and Tunisia for both anthroponotic ( Leishmania tropica ) and zoonotic ( Leishmania major ) forms. Predictive skill up to 12 months ahead improves across all contexts when we incorporate local temperature and precipitation alongside the multiscale signals of the NAO and AMV. This study shows how coupled Atlantic climate variability modulates an infectious disease across timescales, enabling an operational, long-lead seasonal forecast system for a vector-borne disease in the Mediterranean region.
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BibTeX
@article{sanjose2026coupled,
title = {{Coupled Atlantic atmosphere-ocean variability modulates cutaneous leishmaniasis in North Africa, enabling long-lead seasonal forecasts}},
author = {Adrià San-José and Karim Aoun and Meryem Lemrani and Leonardo López and Idris Mhaidi and Aida Bouratbine and Richard E. Paul and Xavier Rodó},
journal = {Science Advances},
year = {2026},
month = aug,
doi = {10.1126/sciadv.aeb0774},
url = {https://pasteur.hal.science/pasteur-05732339v1},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Coupled Atlantic atmosphere-ocean variability modulates cutaneous leishmaniasis in North Africa, enabling long-lead seasonal forecasts
AU - Adrià San-José
AU - Karim Aoun
AU - Meryem Lemrani
AU - Leonardo López
AU - Idris Mhaidi
AU - Aida Bouratbine
AU - Richard E. Paul
AU - Xavier Rodó
PY - 2026
DA - 2026/08/21
JO - Science Advances
DO - 10.1126/sciadv.aeb0774
UR - https://pasteur.hal.science/pasteur-05732339v1
AB - Early warning systems for climate-driven diseases require predictors with sufficient lead time, a persistent challenge for many diseases and regions. While coupled atmosphere-ocean phenomena offer a potential solution, they remain largely underexploited in temperate zones. Here, we establish a multiscale connection between cutaneous leishmaniasis (CL) dynamics in North Africa, the North Atlantic Oscillation (NAO), and the Atlantic Multidecadal Variability (AMV). Beyond the NAO’s influence on seasonal rainfall, we uncover low-frequency variability in the NAO-AMV system that modulates interannual rainfall patterns in North Africa, yielding multiyear periods of high and low CL activity. To quantify this predictability, we develop a unified transmission model applied across Morocco and Tunisia for both anthroponotic ( Leishmania tropica ) and zoonotic ( Leishmania major ) forms. Predictive skill up to 12 months ahead improves across all contexts when we incorporate local temperature and precipitation alongside the multiscale signals of the NAO and AMV. This study shows how coupled Atlantic climate variability modulates an infectious disease across timescales, enabling an operational, long-lead seasonal forecast system for a vector-borne disease in the Mediterranean region.
SN - 2375-2548
ER -