Association of Meteorological Factors and Population Characteristics with Cutaneous Leishmaniasis Occurrence in an Urban Area of Southeastern Morocco: An Application of the PLS-SEM Model

Authors

  • Hanane Ismekh Engineering Science Laboratory, Polydisciplinary Faculty of Ouarzazate, Ibn Zohr University, Ouarzazate, Morocco
  • Adnane Hakem Lab-SIV, Polydisciplinary Faculty of Ouarzazate, Ibn Zohr University, Ouarzazate, Morocco
  • Hafssa Abdellaoui Laboratory of Pharmacology, Neurobiology, Anthropology, Environment, and Behavior, Faculty of Sciences Semlalia Cadi Ayyad University, Marrakesh, Morocco
  • Ghizlan Maymoun Faculty of Sciences, Ibn Zohr University, Agadir, Morocco
  • Ali El-Alaoui Computer Science Department, Computer Systems Engineering Laboratory, Faculty of Sciences Semlalia Cadi Ayyad University, Marrakesh, Morocco
  • Abdellatif El Ghazi National Institute for Urban and Regional Planning (INAU), Rabat, Morocco
  • Meriem Bouziane Higher Institute of Nursing Professions and Health Techniques, Ministry of Health, Ouarzazate, Morocco
  • Brahim El Houate Higher Institute of Nursing Professions and Health Techniques, Ministry of Health, Ouarzazate, Morocco
  • Mourad El Ouali Engineering Science Laboratory, Polydisciplinary Faculty of Ouarzazate, Ibn Zohr University, Ouarzazate, Morocco

DOI:

https://doi.org/10.18502/jad.v20i3.23181

Keywords:

Cutaneous leishmaniasis; Disease control; PLS-SEM; Time series analysis; Climate Change

Abstract

Background: Cutaneous leishmaniasis (CL) remains a major public health concern in Morocco, particularly in arid and semi-arid regions where environmental and demographic conditions favor transmission. Understanding the determinants of CL occurrence is essential for improving surveillance and control. This study investigated climatic and demographic factors associated with CL in an endemic area of southeastern Morocco during 2014−2023.

Methods: This retrospective ecological time-series study used monthly data from 2014 to 2023, and Partial Least Squares Structural Equation Modelling (PLS-SEM) was used to analyse structural relationships. PLS-SEM was chosen for its ability to analyze complex relationships among latent variables and its suitability for relatively small samples and non-normal data. The conceptual model incorporated climatic variables (temperature, humidity, precipitation, wind speed) and population characteristics. Additional diagnostic analyses assessed trend, seasonality, stationarity, and auto­correlation.

Results: Climatic factors were significantly associated with CL occurrence (β= −0.576, p< 0.001), and the model ex­plained 33% of the variance in CL occurrence. Population characteristics were also positively associated with CL occur­rence (β= 0.247, p< 0.001). However, the hypothesized relationship between climatic factors and population character­istics was not statistically significant (β= 0.207, p= 0.053).

Conclusions: Both climatic variability and population characteristics are associated with CL occurrence in southeastern Morocco, highlighting complex relationships shaping disease dynamics. Integrating these determinants into surveillance systems may improve early detection and guide targeted control strategies for vector-borne diseases in endemic regions.

Published

2026-11-07

Issue

Volume (20) issue (3)

Section

Articles