Comparison of time series and mechanistic models of vector-borne diseases.
ARIMA
Modelling
SEIR-SEI
Vector-borne diseases
Journal
Spatial and spatio-temporal epidemiology
ISSN: 1877-5853
Titre abrégé: Spat Spatiotemporal Epidemiol
Pays: Netherlands
ID NLM: 101516571
Informations de publication
Date de publication:
06 2022
06 2022
Historique:
received:
27
01
2020
revised:
21
10
2020
accepted:
10
01
2022
entrez:
12
6
2022
pubmed:
13
6
2022
medline:
15
6
2022
Statut:
ppublish
Résumé
Vector-borne disease models are widely used to understand the dynamics involved in virus transmission. The simplest version of the mechanistic SEIR-SEI model is the most widely used representation of the dynamics involved in vector-borne diseases. Modifications to the basic model can improve the complex dynamics' acuracy. This work evaluates the capability of different models to represent the dynamics involved in dengue virus transmission. The models include a vector life stage representation, a re-susceptibility factor, and environmental variables in a mechanistic form. Furthermore, Autoregressive Integrated Moving Average methodologies (ARIMA method) were also used for comparison. The inclusion of environmental variables and vector life cycle improves the model's accuracy for mechanistic models, but the modification's complexity can restrict its applicability. Data-driven techniques were shown to be less accurate than all the mechanistic-based models (based on all criteria adopted).
Identifiants
pubmed: 35691636
pii: S1877-5845(22)00002-8
doi: 10.1016/j.sste.2022.100478
pii:
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
100478Informations de copyright
Copyright © 2022. Published by Elsevier Ltd.