Page 243 - Contributed Paper Session (CPS) - Volume 3
P. 243
CPS2003 Bruno de S. et al.
Algarve’s population is foreigner, making it the region with the greatest
representativeness of foreigners’ residents (Census 2011, Statistics Portugal).
Future research will focus on the risk factors associated with the identified
four regions, namely Region I – Metropolitan Area of Porto and Upper North
(34 municipalities), Region II –Metropolitan Area of Lisbon (20 municipalities),
Region III – Algarve and Lower Alentejo (17 municipalities), and the Low Risk
region with the remaining municipalities (207 municipalities).
As a final note, it is essential to emphasize how Structured Additive Regression
(STAR) models offer a rich framework that allows the presence of a wide range
of covariates while simultaneously exploring possible spatial and temporal
correlations within a very diverse type of response variables.
Acknowledgments
This work was supported by the Portuguese National Funding Agency for
Science, Research and Technology, Fundação para a Ciência e Tecnologia –
Ministério da Educação e Ciência, through the research project [PTDC/SAU-
SAP/116950/2010]. The third and fourth authors are also supported through
the project [UID/MAT/04674/2019].
References
1. World Health Organization. Global Tuberculosis Report 2018. Geneva:
World Health Organization, 2018.
2. European Centre for Disease Prevention and Control/WHO Regional Office
for Europe. Tuberculosis surveillance and monitoring in Europe 2014.
Stockholm: European Centre for Disease Prevention and Control, 2014.
3. Nunes C, Briz T, Gomes D, & Filipe PA (2011). Pulmonary Tuberculosis and
HIV/AIDS: joint space-time clustering under an epidemiological
perspective. In: Cafarelli B, editors. Proceedings of the Spatial Data
Methods for Environmental and Ecological Processes - 2nd Edition; Foggia
e Gargano, p. 1-4.
4. Kneib T (2006). Mixed model based inference in structured additive
regression. PhD Thesis. Munchen: Universität Munchen, Fakultät für
Mathematik, Informatik und Statistik der Ludwig-Maximilians.
5. Fahrmeir L, Kneib T, & Lang, S (2004). Penalized structured additive
regression for space-time data - a bayesian perspective. Stat Sinica,
14:731-761.
6. Lang S, & Brezger A (2004). Bayesian P-splines. J Comput Graph Stat.,
13:183-212.
7. Brezger A, & Lang S (2006). Generalized additive regression based on
Bayesian P-splines. Comput Stat Data An., 50:967-991.
8. Rue H, & Held L. (2005). Gaussian Markov Random Fields: Theory and
Applications. Boca Raton, FL: Chapman & Hall/CRC.
232 | I S I W S C 2 0 1 9