Modelling of Leishmaniasis Infection Dynamics: A Comparative Time Series Analysis with VAR, VECM, Generalized Linear and Markov Switching Models

Abstract

In this paper, we are interested in modeling the dynamics of cutaneous leishmaniasis (CL) in Errachidia province (Morocco), using epidemiologic data and the most notable climatic factors associated with leishmaniasis, namely humidity, wind speed, rainfall, and temperature. To achieve our objective, we compare the performance of three statistical models, namely the Vector Auto-Regressive (VAR) model, the Vector Error Correction model (VECM), and the Generalized Linear model (GLM), using different metrics. The modeling framework will be compared with the Markov Switching (MSM) approach.

Keywords

• leishmaniasis dynamics
• generalized linear model (GLM)
• Markov switching model (MSM)
• meteorological data
• vector auto-regressive model (VAR)
• vector error correction model (VECM)