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

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,...

Full description

Saved in:
Bibliographic Details
Published inEngineering proceedings Vol. 39; no. 1; p. 38
Main Authors Fadoua Badaoui, Souad Bouhout, Amine Amar, Kenza Khomsi
Format Journal Article
LanguageEnglish
Published MDPI AG 01.07.2023
Subjects
generalized linear model (GLM)
leishmaniasis dynamics
Markov switching model (MSM)
meteorological data
vector auto-regressive model (VAR)
vector error correction model (VECM)
Online AccessGet full text

Cover

More Information
Summary: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.
ISSN:2673-4591
DOI:10.3390/engproc2023039038