02731nas a2200325 4500000000100000008004100001260001200042653001200054653002100066653001200087653001600099653002500115653003700140100001400177700001400191700001200205700001300217700001300230700001300243700001400256700001500270700001200285700001200297245014600309856015300455300001100608490000700619520176500626022001402391 2026 d c06/202610aAlgeria10aClimatic factors10adrought10aRisk factor10aVector-borne disease10aZoonotic cutaneous leishmaniasis1 aOuachek K1 aMedrouh B1 aZebsa R1 aFerdes I1 aTahtah A1 aSeddas F1 aSouttou K1 aBenallal K1 aHakem A1 aLafri I00aSpatio-temporal modeling of zoonotic cutaneous leishmaniasis (ZCL) in the Algerian steppe: Epidemiological insights and climatic associations uhttps://www.sciencedirect.com/science/article/pii/S1755436526000460/pdfft?md5=b982517cd48d10a03fc719f68f8bccf2&pid=1-s2.0-S1755436526000460-main.pdf a1 - 110 v563 a

Zoonotic cutaneous leishmaniasis (ZCL) caused by Leishmania major remains a significant public health concern in Algeria. The disease is maintained through a zoonotic cycle involving wild rodents as reservoirs and sand flies as vectors, whose population dynamics are influenced by climatic conditions. In the context of global climate change, this study investigated the relationship between climatic factors and ZCL incidence, and mapped high-risk areas in the Algerian central steppe. Epidemiological and climatic data from Djelfa, Laghouat, and Tiaret Wilayas collected between 2010 and 2022 were analyzed using generalized additive models (GAMs) to assess spatiotemporal patterns and climatic associations. A total of 8488 ZCL cases were reported over the study period, with an incidence rate of 3.10/10,000 inhabitants. The highest burden was observed in Laghouat, with a declining gradient northward, although incidence in northern areas increased over time. Seasonal peaks of reported cases occurred between November and February, primarily affecting adults aged between 45-65 and children under 10 years old. Incidence was slightly higher in men, though sex and age differences were not significant. Modeling results revealed that Palmer Drought Severity Index at a two-month lag showed a strong nonlinear association with ZCL incidence, with higher risk under extreme drought and wet conditions, and reduced transmission under moderate drought. Precipitation exhibited a marginal, inverse nonlinear effect, with higher rainfall associated with lower case counts. These findings underscore the role of climate variability in ZCL dynamics and highlight the need for climate-informed early warning systems and targeted public health interventions.

 a1878-0067