Bayesian spatial models of injury severity at railway crossings

Author(s):  
Renato Guadamuz ◽  
Jonathan Aguero-Valverde
PLoS ONE ◽  
2019 ◽  
Vol 14 (8) ◽  
pp. e0218310 ◽  
Author(s):  
Nicholas J. Tierney ◽  
Antonietta Mira ◽  
H. Jost Reinhold ◽  
Giuseppe Arbia ◽  
Samuel Clifford ◽  
...  

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Olena Oliveira ◽  
Ana Isabel Ribeiro ◽  
Elias Teixeira Krainski ◽  
Teresa Rito ◽  
Raquel Duarte ◽  
...  

Abstract Multidrug-resistant tuberculosis (MDR-TB) is a major threat to the eradication of tuberculosis. TB control strategies need to be adapted to the necessities of different countries and adjusted in high-risk areas. In this study, we analysed the spatial distribution of the MDR- and non-MDR-TB cases across municipalities in Continental Portugal between 2000 and 2016. We used Bayesian spatial models to estimate age-standardized notification rates and standardized notification ratios in each area, and to delimitate high- and low-risk areas, those whose standardized notification ratio is significantly above or below the country’s average, respectively. The spatial distribution of MDR- and non-MDR-TB was not homogeneous across the country. Age-standardized notification rates of MDR-TB ranged from 0.08 to 1.20 and of non-MDR-TB ranged from 7.73 to 83.03 notifications per 100,000 population across the municipalities. We identified 36 high-risk areas for non-MDR-TB and 8 high-risk areas for MDR-TB, which were simultaneously high-risk areas for non-MDR-TB. We found a moderate correlation (ρ = 0.653; 95% CI 0.457–0.728) between MDR- and non-MDR-TB standardized notification ratios. We found heterogeneity in the spatial distribution of MDR-TB across municipalities and we identified priority areas for intervention against TB. We recommend including geographical criteria in the application of molecular drug resistance to provide early MDR-TB diagnosis, in high-risk areas.


2015 ◽  
Vol 31 ◽  
pp. 285-295 ◽  
Author(s):  
Cyrille Brun ◽  
Alex R. Cook ◽  
Janice Ser Huay Lee ◽  
Serge A. Wich ◽  
Lian Pin Koh ◽  
...  

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