Statistical Modeling and Bayesian Methods for Disease Mapping: Bayesian Spatio-Temporal Analysis of COVID-19 and Tuberculosis - Couverture souple

Benedict Celestine, Agbata; Dervishi, Raimonda

 
9786209557910: Statistical Modeling and Bayesian Methods for Disease Mapping: Bayesian Spatio-Temporal Analysis of COVID-19 and Tuberculosis
Couverture souple
ISBN 10 : 6209557910 ISBN 13 : 9786209557910
Editeur : GlobeEdit, 2026

Synopsis

This book investigates the spatio-temporal patterns of COVID-19 and tuberculosis using complementary statistical and Bayesian modeling approaches. COVID-19 is analyzed at weekly scale to capture short-term epidemic waves, while TB is studied annually to assess long-term spatial trends. The study applied Generalized Additive Models and Bayesian hierarchical models using INLA to estimate nonlinear effects, spatial dependence, and temporal variation. Results revealed strong seasonality and mobility-related effects for COVID-19, while TB shows stable but uneven geographic distribution across districts. The models produce reliable risk maps and highlight the importance of targeted surveillance, improved monitoring, and resource allocation for effective disease control.

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Éditeur
GlobeEdit
Date d'édition
2026
Langue
anglais
ISBN 10 
6209557910
ISBN 13 
9786209557910
Reliure
Broché
Nombre de pages
76
Coordonnées du fabricant
non disponible
Personne responsable
non disponible