scholarly journals A comparison of multiple neighborhood matrix specifications for spatio-temporal model fitting: a case study on COVID-19 data

2021 ◽  
Author(s):  
Álvaro Briz-Redón ◽  
Adina Iftimi ◽  
Juan Francisco Correcher ◽  
Jose De Andrés ◽  
Manuel Lozano ◽  
...  
Keyword(s):  
Model Fitting ◽  
Temporal Model ◽  
Spatio Temporal

scholarly journals Space–Time Relationship between Short-Term Exposure to Fine and Coarse Particles and Mortality in a Nationwide Analysis of Korea: A Bayesian Hierarchical Spatio-Temporal Model

2019 ◽  
Vol 16 (12) ◽  
pp. 2111 ◽  
Author(s):  
Dayun Kang ◽  
Yujin Jang ◽  
Hyunho Choi ◽  
Seung-sik Hwang ◽  
Younseo Koo ◽  
...  
Keyword(s):  
Air Pollution ◽  
South Korea ◽  
Fine Particulate Matter ◽  
Model Fitting ◽  
Ambient Air ◽  
Ambient Air Pollution ◽  
Respiratory Mortality ◽  
Short Term Exposure ◽  
Temporal Model ◽  
Spatio Temporal

Previous studies have shown an association between mortality and ambient air pollution in South Korea. However, these studies may have been subject to bias, as they lacked adjustment for spatio-temporal structures. This paper addresses this research gap by examining the association between air pollution and cause-specific mortality in South Korea between 2012 and 2015 using a two-stage Bayesian spatio-temporal model. We used 2012–2014 mortality and air pollution data for parameter estimation (i.e., model fitting) and 2015 data for model validation. Our results suggest that the relative risks of total, cardiovascular, and respiratory mortality were 1.028, 1.047, and 1.045, respectively, with every 10-µg/m3 increase in monthly PM2.5 (fine particulate matter) exposure. These findings warrant protection of populations who experience elevated ambient air pollution exposure to mitigate mortality burden in South Korea.

Spatio-temporal modelling of disease incidence with missing covariate values

2014 ◽  
Vol 143 (8) ◽  
pp. 1777-1788 ◽  
Author(s):  
R. C. HOLLAND ◽  
G. JONES ◽  
J. BENSCHOP
Keyword(s):  
Risk Factors ◽  
Missing Values ◽  
Disease Incidence ◽  
Analysis Framework ◽  
Temporal Correlations ◽  
Temporal Modelling ◽  
Temporal Model ◽  
Spatio Temporal ◽  
Underlying Risk

SUMMARYThe search for an association between disease incidence and possible risk factors using surveillance data needs to account for possible spatial and temporal correlations in underlying risk. This can be especially difficult if there are missing values for some important covariates. We present a case study to show how this problem can be overcome in a Bayesian analysis framework by adding to the usual spatio-temporal model a component for modelling the missing data.

Multimodal Spatio-Temporal Model of the Natural History of Alzheimer's Disease from Joint Serial Assessment of Amyloidosis, Tauopathy, Hypometabolism, and Atrophy

2019 ◽  
Author(s):  
Marco Lorenzi ◽  
Federica Ribaldi ◽  
Valentina Garibotto ◽  
Frederik Barkhof ◽  
Giovanni B. Frisoni ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Natural History ◽  
History Of ◽  
Temporal Model ◽  
Spatio Temporal

Spatio-temporal approach for identification of critical conservation areas: a case study with two pine species from a threatened temperate forest in Mexico

2019 ◽  
Vol 28 (7) ◽  
pp. 1863-1883 ◽  
Author(s):  
Agustín Molina Sánchez ◽  
Patricia Delgado ◽  
Antonio González-Rodríguez ◽  
Clementina González ◽  
A. Francisco Gómez-Tagle Rojas ◽  
...  
Keyword(s):  
Temperate Forest ◽  
Conservation Areas ◽  
Spatio Temporal ◽  
Pine Species

scholarly journals Spatio-temporal analysis of COVID-19 incidence rate using GIS: a case study—Tehran metropolitan, Iran

GeoJournal ◽  
2021 ◽  
Author(s):  
R. Nasiri ◽  
S. Akbarpour ◽  
AR. Zali ◽  
N. Khodakarami ◽  
MH. Boochani ◽  
...  
Keyword(s):  
Incidence Rate ◽  
Temporal Analysis ◽  
Spatio Temporal
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