• Yasmine Saadene, Amina Salhi, Feriel Mliki, and Zihad Bouslama.
• From the Laboratory of Ecology of Earth and Aquatic Systems, University of Badji Mokhtar, Annaba, Algeria.
• Ann Saudi Med. 2023 Sep 1; 43 (5): 263276263-276.

BackgroundCutaneous leishmaniasis (CL) is a vector-borne disease prevalent in Algeria since 2000. The disease has significant impacts on affected communities, including morbidity and social stigma.ObjectiveInvestigate the association between environmental factors and the incidence of CL in the province of Ghardaïa and assess the predictive capacity of these factors for disease occurrence.DesignRetrospective SETTING: The study area included both urban and rural communities.MethodsWe analyzed a dataset on CL in the province of Ghardaïa, Algeria, spanning from 2000 to 2020. The dataset included climatic variables such as temperature, average humidity, wind speed, rainfall, and the normalized difference vegetation index (NDVI). Using generalized additive models, we examined the relationships and interactions between these variables to predict the emergence of CL in the study area.Main Outcome MeasuresThe identification of the most significant environmental factors associated with the incidence and the predicted incidence rates of CL in the province of Ghardaïa, Algeria.Sample Size And Characteristics252 monthly observations of both climatic and epidemiological variables.ResultsRelative humidity and wind speed were the primary climatic factors influencing the occurrence of CL epidemics in Ghardaïa, Algeria. Additionally, NDVI was a significant environmental factor associated with CL incidence. Surprisingly, temperature did not show a strong effect on CL occurrence, while rainfall was not statistically significant. The final fitted model predictions were highly correlated with real cases.ConclusionThis study provides a better understanding of the long-term trend in how environmental and climatic factors contribute to the emergence of CL. Our results can inform the development of effective early warning systems for preventing the transmission and emergence of vector-borne diseases.LimitationsIncorporating additional reservoir statistics such as rodent density and a human development index in the region could improve our understanding of disease transmission.

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