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

Benedict Celestine, Agbata; Dervishi, Raimonda

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

Inhaltsangabe

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.

Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.

Über die Autorin bzw. den Autor

Dr. Agbata Benedict Celestine is a Lecturer in the Department of Mathematics and Statistics, Faculty of Science, at Confluence University of Science and Technology, Osara, Nigeria. He specializes in mathematical epidemiology and computational modeling, with research focused on understanding the dynamics of infectious diseases.

„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.

Verlag
GlobeEdit
Erscheinungsdatum
2026
Sprache
Englisch
ISBN 10 
6209557910
ISBN 13 
9786209557910
Einband
Taschenbuch
Anzahl der Seiten
76
Kontakt zum Hersteller
Editions Muse
customerservice@vdm-vsg.de

Brivibas gatve 197
Riga
1039
Lettland