Vector-borne infectious disease mapping with stochastic difference equations: an analysis of dengue disease in Malaysia

DOI10.1080/02664763.2012.700450OpenAlexW2069095769MaRDI QIDQ5127068

Nor Azah Samat, David F. Percy

Publication date: 21 October 2020

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02664763.2012.700450

zbMATH Keywords

relative riskdisease mappingdengue diseaseSIR-SI modelstract-count data

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (5)

Relative risk analysis of dengue cases using convolution extended into spatio-temporal model ⋮ The development of a deterministic dengue epidemic model with the influence of temperature: a case study in Malaysia ⋮ Stability of a dengue epidemic model with independent stochastic perturbations ⋮ Fractal control and synchronization of the discrete fractional SIRS model ⋮ Mixed-effects modelling for crossed and nested data: an analysis of dengue fever in the state of Goiás, Brazil

Uses Software

• WinBUGS
• MLwiN

Cites Work

• Unnamed Item
• Unnamed Item
• Bayesian image restoration, with two applications in spatial statistics (with discussion)
• Analysis of a dengue disease transmission model
• A tutorial introduction to Bayesian inference for stochastic epidemic models using Markov chain Monte Carlo methods
• Bayesian estimation of the basic reproduction number in stochastic epidemic models
• A Generalized Stochastic Model for the Analysis of Infectious Disease Final Size Data
• A stochastic SIS infection model incorporating indirect transmission
• Bayesian Disease Mapping
• Hierarchical Spatio-Temporal Mapping of Disease Rates

This page was built for publication: Vector-borne infectious disease mapping with stochastic difference equations: an analysis of dengue disease in Malaysia