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Spatiotemporal patterns of zoonotic cutaneous leishmaniasis in the high-burden provinces of Morocco, 1995-2022: an exploratory analysis of environmental and socio-demographic correlates.

Created on 14 Aug 2026

Authors

Chaymaa Harkat, Denis Sereno, Oussama Rida, Hicham Hafiane, Souad Bouhout, Laila Hoummadi, Kholoud Kahime

Published in

Parasite (Paris, France). Volume 33. Pages 44. Epub Aug 13, 2026.

Abstract

Zoonotic cutaneous leishmaniasis (ZCL) caused by Leishmania major remains a major public health concern in Morocco, especially in certain semi-arid and pre-Saharan regions where ecological conditions favor transmission. In recent decades, the epidemiology of ZCL has evolved significantly, particularly in its temporal patterns and the persistence of transmission in major endemic provinces. In this study, we adopted a retrospective observational approach to explore the long-term spatiotemporal dynamics of ZCL across nine endemic provinces in Morocco and to assess its potential environmental, socio-economic, and demographic determinants using a descriptive analytical framework.
A total of 58,880 ZCL cases were reported during the study period between 1995 and 2022, with incidence peaks observed in 2010 and 2018, reflecting cyclical epidemic dynamics. The Drâa-Tafilalet region accounted for the highest disease burden, with Zagora province identified as the main epidemiological hotspot. Children aged ≤10 represented the most affected age group (40.8% of total cases), whereas infection rates did not differ significantly between the sexes (female-to-male ratio = 1.17). Higher incidence was observed in hyper-arid provinces characterized by sandy-clay-loam soils. However, incidence was not statistically correlated with either environmental or social variables (p > 0.05).
ZCL remains endemic in Morocco, with persistent hotspots linked to specific ecological contexts. These findings highlight the importance of geographically targeted surveillance and control measures to support the integration of environmental indicators into risk monitoring and early-warning systems for leishmaniasis.

PMID:
42599014
Bibliographic data and abstract were imported from PubMed on 14 Aug 2026.

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