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Spatio-temporal modeling of infectious diseases by integrating compartment and point process models
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Título : Spatio-temporal modeling of infectious diseases by integrating compartment and point process models |
Autor : Ribeiro Amaral, André Victor González, Jonatan A. ![](/image/ORCID.jpg) Moraga, Paula |
Editor : Springer |
Departamento: Departamentos de la UMH::Estadística, Matemáticas e Informática |
Fecha de publicación: 2022-12-13 |
URI : https://hdl.handle.net/11000/30796 |
Resumen :
Infectious disease modeling plays an important role in understanding disease spreading dynamics and can be used for prevention and control. The well-known SIR (Susceptible, Infected, and Recovered) compartment model and spatial and spatio-temporal statistical models are common choices for studying problems of this kind. This paper proposes a spatio-temporal modeling framework to characterize infectious disease dynamics by integrating the SIR compartment and log-Gaussian Cox process (LGCP) models. The method’s performance is assessed via simulation using a combination of real and synthetic data for a region in São Paulo, Brazil. We also apply our modeling approach to analyze COVID-19 dynamics in Cali, Colombia. The results show that our modified LGCP model, which takes advantage of information obtained from the previous SIR modeling step, leads to a better forecasting performance than equivalent models that do not do that. Finally, the proposed method also allows the incorporation of age-stratified contact information, which provides valuable decision-making insights.
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Palabras clave/Materias: Compartment SIR model Infectious diseases Log-Gaussian Cox process Spatial point process Spatio-temporal modeling |
Área de conocimiento : CDU: Ciencias sociales: Demografía. Sociología. Estadística: Estadística |
Tipo documento : application/pdf |
Derechos de acceso: info:eu-repo/semantics/closedAccess Attribution-NonCommercial-NoDerivatives 4.0 Internacional |
DOI : https://doi.org/10.1007/s00477-022-02354-4 |
Aparece en las colecciones: Artículos Estadística, Matemáticas e Informática
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La licencia se describe como: Atribución-NonComercial-NoDerivada 4.0 Internacional.