The Experts below are selected from a list of 12225 Experts worldwide ranked by ideXlab platform
Evelina Tacconelli - One of the best experts on this subject based on the ideXlab platform.
-
Gross National Income and antibiotic resistance in invasive isolates analysis of the top ranked antibiotic resistant bacteria on the 2017 who priority list
Journal of Antimicrobial Chemotherapy, 2019Co-Authors: Alessia Savoldi, Elena Carrara, Beryl Primrose Gladstone, Anna Maria Azzini, Siri Göpel, Evelina TacconelliAbstract:OBJECTIVES To assess the association between country Income status and National prevalence of invasive infections caused by the top-ranked bacteria on the WHO priority list: carbapenem-resistant (CR) Acinetobacter spp., Klebsiella spp. and Pseudomonas aeruginosa; third-generation cephalosporin-resistant (3GCR) Escherichia coli and Klebsiella spp.; and MRSA and vancomycin-resistant Enterococcus faecium (VR E. faecium). METHODS Active surveillance systems providing yearly prevalence data from 2012 onwards for the selected bacteria were included. The Gross National Income (GNI) per capita was used as the indicator for Income status of each country and was log transformed to account for non-linearity. The association between antibiotic prevalence data and GNI per capita was investigated individually for each bacterium through linear regression. RESULTS Surveillance data were available from 67 countries: 38 (57%) were high Income, 16 (24%) upper-middle Income, 11 (16%) lower-middle Income and two (3%) low Income countries. The regression showed significant inverse association (P<0.0001) between resistance prevalence of invasive infections and GNI per capita. The highest rate of increase per unit decrease in log GNI per capita was observed in 3GCR Klebsiella spp. (22.5%, 95% CI 18.2%-26.7%), CR Acinetobacter spp. (19.2% 95% CI 11.3%-27.1%) and 3GCR E. coli (15.3%, 95% CI 11.6%-19.1%). The rate of increase per unit decrease in log GNI per capita was lower in MRSA (9.5%, 95% CI 5.2%-13.7%). CONCLUSIONS The prevalence of invasive infections caused by the WHO top-ranked antibiotic-resistant bacteria is inversely associated with GNI per capita at the global level. Public health interventions designed to limit the burden of antimicrobial resistance should also consider determinants of poverty and inequality, especially in lower-middle Income and low Income countries.
-
Gross National Income and antibiotic resistance in invasive isolates: analysis of the top-ranked antibiotic-resistant bacteria on the 2017 WHO priority list.
The Journal of antimicrobial chemotherapy, 2019Co-Authors: Alessia Savoldi, Elena Carrara, Beryl Primrose Gladstone, Anna Maria Azzini, Siri Göpel, Evelina TacconelliAbstract:OBJECTIVES To assess the association between country Income status and National prevalence of invasive infections caused by the top-ranked bacteria on the WHO priority list: carbapenem-resistant (CR) Acinetobacter spp., Klebsiella spp. and Pseudomonas aeruginosa; third-generation cephalosporin-resistant (3GCR) Escherichia coli and Klebsiella spp.; and MRSA and vancomycin-resistant Enterococcus faecium (VR E. faecium). METHODS Active surveillance systems providing yearly prevalence data from 2012 onwards for the selected bacteria were included. The Gross National Income (GNI) per capita was used as the indicator for Income status of each country and was log transformed to account for non-linearity. The association between antibiotic prevalence data and GNI per capita was investigated individually for each bacterium through linear regression. RESULTS Surveillance data were available from 67 countries: 38 (57%) were high Income, 16 (24%) upper-middle Income, 11 (16%) lower-middle Income and two (3%) low Income countries. The regression showed significant inverse association (P
Alessia Savoldi - One of the best experts on this subject based on the ideXlab platform.
-
Gross National Income and antibiotic resistance in invasive isolates analysis of the top ranked antibiotic resistant bacteria on the 2017 who priority list
Journal of Antimicrobial Chemotherapy, 2019Co-Authors: Alessia Savoldi, Elena Carrara, Beryl Primrose Gladstone, Anna Maria Azzini, Siri Göpel, Evelina TacconelliAbstract:OBJECTIVES To assess the association between country Income status and National prevalence of invasive infections caused by the top-ranked bacteria on the WHO priority list: carbapenem-resistant (CR) Acinetobacter spp., Klebsiella spp. and Pseudomonas aeruginosa; third-generation cephalosporin-resistant (3GCR) Escherichia coli and Klebsiella spp.; and MRSA and vancomycin-resistant Enterococcus faecium (VR E. faecium). METHODS Active surveillance systems providing yearly prevalence data from 2012 onwards for the selected bacteria were included. The Gross National Income (GNI) per capita was used as the indicator for Income status of each country and was log transformed to account for non-linearity. The association between antibiotic prevalence data and GNI per capita was investigated individually for each bacterium through linear regression. RESULTS Surveillance data were available from 67 countries: 38 (57%) were high Income, 16 (24%) upper-middle Income, 11 (16%) lower-middle Income and two (3%) low Income countries. The regression showed significant inverse association (P<0.0001) between resistance prevalence of invasive infections and GNI per capita. The highest rate of increase per unit decrease in log GNI per capita was observed in 3GCR Klebsiella spp. (22.5%, 95% CI 18.2%-26.7%), CR Acinetobacter spp. (19.2% 95% CI 11.3%-27.1%) and 3GCR E. coli (15.3%, 95% CI 11.6%-19.1%). The rate of increase per unit decrease in log GNI per capita was lower in MRSA (9.5%, 95% CI 5.2%-13.7%). CONCLUSIONS The prevalence of invasive infections caused by the WHO top-ranked antibiotic-resistant bacteria is inversely associated with GNI per capita at the global level. Public health interventions designed to limit the burden of antimicrobial resistance should also consider determinants of poverty and inequality, especially in lower-middle Income and low Income countries.
-
Gross National Income and antibiotic resistance in invasive isolates: analysis of the top-ranked antibiotic-resistant bacteria on the 2017 WHO priority list.
The Journal of antimicrobial chemotherapy, 2019Co-Authors: Alessia Savoldi, Elena Carrara, Beryl Primrose Gladstone, Anna Maria Azzini, Siri Göpel, Evelina TacconelliAbstract:OBJECTIVES To assess the association between country Income status and National prevalence of invasive infections caused by the top-ranked bacteria on the WHO priority list: carbapenem-resistant (CR) Acinetobacter spp., Klebsiella spp. and Pseudomonas aeruginosa; third-generation cephalosporin-resistant (3GCR) Escherichia coli and Klebsiella spp.; and MRSA and vancomycin-resistant Enterococcus faecium (VR E. faecium). METHODS Active surveillance systems providing yearly prevalence data from 2012 onwards for the selected bacteria were included. The Gross National Income (GNI) per capita was used as the indicator for Income status of each country and was log transformed to account for non-linearity. The association between antibiotic prevalence data and GNI per capita was investigated individually for each bacterium through linear regression. RESULTS Surveillance data were available from 67 countries: 38 (57%) were high Income, 16 (24%) upper-middle Income, 11 (16%) lower-middle Income and two (3%) low Income countries. The regression showed significant inverse association (P
Anna Maria Azzini - One of the best experts on this subject based on the ideXlab platform.
-
Gross National Income and antibiotic resistance in invasive isolates analysis of the top ranked antibiotic resistant bacteria on the 2017 who priority list
Journal of Antimicrobial Chemotherapy, 2019Co-Authors: Alessia Savoldi, Elena Carrara, Beryl Primrose Gladstone, Anna Maria Azzini, Siri Göpel, Evelina TacconelliAbstract:OBJECTIVES To assess the association between country Income status and National prevalence of invasive infections caused by the top-ranked bacteria on the WHO priority list: carbapenem-resistant (CR) Acinetobacter spp., Klebsiella spp. and Pseudomonas aeruginosa; third-generation cephalosporin-resistant (3GCR) Escherichia coli and Klebsiella spp.; and MRSA and vancomycin-resistant Enterococcus faecium (VR E. faecium). METHODS Active surveillance systems providing yearly prevalence data from 2012 onwards for the selected bacteria were included. The Gross National Income (GNI) per capita was used as the indicator for Income status of each country and was log transformed to account for non-linearity. The association between antibiotic prevalence data and GNI per capita was investigated individually for each bacterium through linear regression. RESULTS Surveillance data were available from 67 countries: 38 (57%) were high Income, 16 (24%) upper-middle Income, 11 (16%) lower-middle Income and two (3%) low Income countries. The regression showed significant inverse association (P<0.0001) between resistance prevalence of invasive infections and GNI per capita. The highest rate of increase per unit decrease in log GNI per capita was observed in 3GCR Klebsiella spp. (22.5%, 95% CI 18.2%-26.7%), CR Acinetobacter spp. (19.2% 95% CI 11.3%-27.1%) and 3GCR E. coli (15.3%, 95% CI 11.6%-19.1%). The rate of increase per unit decrease in log GNI per capita was lower in MRSA (9.5%, 95% CI 5.2%-13.7%). CONCLUSIONS The prevalence of invasive infections caused by the WHO top-ranked antibiotic-resistant bacteria is inversely associated with GNI per capita at the global level. Public health interventions designed to limit the burden of antimicrobial resistance should also consider determinants of poverty and inequality, especially in lower-middle Income and low Income countries.
-
Gross National Income and antibiotic resistance in invasive isolates: analysis of the top-ranked antibiotic-resistant bacteria on the 2017 WHO priority list.
The Journal of antimicrobial chemotherapy, 2019Co-Authors: Alessia Savoldi, Elena Carrara, Beryl Primrose Gladstone, Anna Maria Azzini, Siri Göpel, Evelina TacconelliAbstract:OBJECTIVES To assess the association between country Income status and National prevalence of invasive infections caused by the top-ranked bacteria on the WHO priority list: carbapenem-resistant (CR) Acinetobacter spp., Klebsiella spp. and Pseudomonas aeruginosa; third-generation cephalosporin-resistant (3GCR) Escherichia coli and Klebsiella spp.; and MRSA and vancomycin-resistant Enterococcus faecium (VR E. faecium). METHODS Active surveillance systems providing yearly prevalence data from 2012 onwards for the selected bacteria were included. The Gross National Income (GNI) per capita was used as the indicator for Income status of each country and was log transformed to account for non-linearity. The association between antibiotic prevalence data and GNI per capita was investigated individually for each bacterium through linear regression. RESULTS Surveillance data were available from 67 countries: 38 (57%) were high Income, 16 (24%) upper-middle Income, 11 (16%) lower-middle Income and two (3%) low Income countries. The regression showed significant inverse association (P
Siri Göpel - One of the best experts on this subject based on the ideXlab platform.
-
Gross National Income and antibiotic resistance in invasive isolates analysis of the top ranked antibiotic resistant bacteria on the 2017 who priority list
Journal of Antimicrobial Chemotherapy, 2019Co-Authors: Alessia Savoldi, Elena Carrara, Beryl Primrose Gladstone, Anna Maria Azzini, Siri Göpel, Evelina TacconelliAbstract:OBJECTIVES To assess the association between country Income status and National prevalence of invasive infections caused by the top-ranked bacteria on the WHO priority list: carbapenem-resistant (CR) Acinetobacter spp., Klebsiella spp. and Pseudomonas aeruginosa; third-generation cephalosporin-resistant (3GCR) Escherichia coli and Klebsiella spp.; and MRSA and vancomycin-resistant Enterococcus faecium (VR E. faecium). METHODS Active surveillance systems providing yearly prevalence data from 2012 onwards for the selected bacteria were included. The Gross National Income (GNI) per capita was used as the indicator for Income status of each country and was log transformed to account for non-linearity. The association between antibiotic prevalence data and GNI per capita was investigated individually for each bacterium through linear regression. RESULTS Surveillance data were available from 67 countries: 38 (57%) were high Income, 16 (24%) upper-middle Income, 11 (16%) lower-middle Income and two (3%) low Income countries. The regression showed significant inverse association (P<0.0001) between resistance prevalence of invasive infections and GNI per capita. The highest rate of increase per unit decrease in log GNI per capita was observed in 3GCR Klebsiella spp. (22.5%, 95% CI 18.2%-26.7%), CR Acinetobacter spp. (19.2% 95% CI 11.3%-27.1%) and 3GCR E. coli (15.3%, 95% CI 11.6%-19.1%). The rate of increase per unit decrease in log GNI per capita was lower in MRSA (9.5%, 95% CI 5.2%-13.7%). CONCLUSIONS The prevalence of invasive infections caused by the WHO top-ranked antibiotic-resistant bacteria is inversely associated with GNI per capita at the global level. Public health interventions designed to limit the burden of antimicrobial resistance should also consider determinants of poverty and inequality, especially in lower-middle Income and low Income countries.
-
Gross National Income and antibiotic resistance in invasive isolates: analysis of the top-ranked antibiotic-resistant bacteria on the 2017 WHO priority list.
The Journal of antimicrobial chemotherapy, 2019Co-Authors: Alessia Savoldi, Elena Carrara, Beryl Primrose Gladstone, Anna Maria Azzini, Siri Göpel, Evelina TacconelliAbstract:OBJECTIVES To assess the association between country Income status and National prevalence of invasive infections caused by the top-ranked bacteria on the WHO priority list: carbapenem-resistant (CR) Acinetobacter spp., Klebsiella spp. and Pseudomonas aeruginosa; third-generation cephalosporin-resistant (3GCR) Escherichia coli and Klebsiella spp.; and MRSA and vancomycin-resistant Enterococcus faecium (VR E. faecium). METHODS Active surveillance systems providing yearly prevalence data from 2012 onwards for the selected bacteria were included. The Gross National Income (GNI) per capita was used as the indicator for Income status of each country and was log transformed to account for non-linearity. The association between antibiotic prevalence data and GNI per capita was investigated individually for each bacterium through linear regression. RESULTS Surveillance data were available from 67 countries: 38 (57%) were high Income, 16 (24%) upper-middle Income, 11 (16%) lower-middle Income and two (3%) low Income countries. The regression showed significant inverse association (P
Beryl Primrose Gladstone - One of the best experts on this subject based on the ideXlab platform.
-
Gross National Income and antibiotic resistance in invasive isolates analysis of the top ranked antibiotic resistant bacteria on the 2017 who priority list
Journal of Antimicrobial Chemotherapy, 2019Co-Authors: Alessia Savoldi, Elena Carrara, Beryl Primrose Gladstone, Anna Maria Azzini, Siri Göpel, Evelina TacconelliAbstract:OBJECTIVES To assess the association between country Income status and National prevalence of invasive infections caused by the top-ranked bacteria on the WHO priority list: carbapenem-resistant (CR) Acinetobacter spp., Klebsiella spp. and Pseudomonas aeruginosa; third-generation cephalosporin-resistant (3GCR) Escherichia coli and Klebsiella spp.; and MRSA and vancomycin-resistant Enterococcus faecium (VR E. faecium). METHODS Active surveillance systems providing yearly prevalence data from 2012 onwards for the selected bacteria were included. The Gross National Income (GNI) per capita was used as the indicator for Income status of each country and was log transformed to account for non-linearity. The association between antibiotic prevalence data and GNI per capita was investigated individually for each bacterium through linear regression. RESULTS Surveillance data were available from 67 countries: 38 (57%) were high Income, 16 (24%) upper-middle Income, 11 (16%) lower-middle Income and two (3%) low Income countries. The regression showed significant inverse association (P<0.0001) between resistance prevalence of invasive infections and GNI per capita. The highest rate of increase per unit decrease in log GNI per capita was observed in 3GCR Klebsiella spp. (22.5%, 95% CI 18.2%-26.7%), CR Acinetobacter spp. (19.2% 95% CI 11.3%-27.1%) and 3GCR E. coli (15.3%, 95% CI 11.6%-19.1%). The rate of increase per unit decrease in log GNI per capita was lower in MRSA (9.5%, 95% CI 5.2%-13.7%). CONCLUSIONS The prevalence of invasive infections caused by the WHO top-ranked antibiotic-resistant bacteria is inversely associated with GNI per capita at the global level. Public health interventions designed to limit the burden of antimicrobial resistance should also consider determinants of poverty and inequality, especially in lower-middle Income and low Income countries.
-
Gross National Income and antibiotic resistance in invasive isolates: analysis of the top-ranked antibiotic-resistant bacteria on the 2017 WHO priority list.
The Journal of antimicrobial chemotherapy, 2019Co-Authors: Alessia Savoldi, Elena Carrara, Beryl Primrose Gladstone, Anna Maria Azzini, Siri Göpel, Evelina TacconelliAbstract:OBJECTIVES To assess the association between country Income status and National prevalence of invasive infections caused by the top-ranked bacteria on the WHO priority list: carbapenem-resistant (CR) Acinetobacter spp., Klebsiella spp. and Pseudomonas aeruginosa; third-generation cephalosporin-resistant (3GCR) Escherichia coli and Klebsiella spp.; and MRSA and vancomycin-resistant Enterococcus faecium (VR E. faecium). METHODS Active surveillance systems providing yearly prevalence data from 2012 onwards for the selected bacteria were included. The Gross National Income (GNI) per capita was used as the indicator for Income status of each country and was log transformed to account for non-linearity. The association between antibiotic prevalence data and GNI per capita was investigated individually for each bacterium through linear regression. RESULTS Surveillance data were available from 67 countries: 38 (57%) were high Income, 16 (24%) upper-middle Income, 11 (16%) lower-middle Income and two (3%) low Income countries. The regression showed significant inverse association (P
