Alessia Savoldi1,2, Elena Carrara2, Beryl Primrose Gladstone1, Anna Maria Azzini2, Siri Göpel1, Evelina Tacconelli1,2. 1. Division of Infectious Diseases, Department of Internal Medicine I, German Center for Infection Research, University of Tübingen, Otfried Müller Straße 12, 72074 Tübingen, Germany. 2. Division of Infectious Diseases, Department of Diagnostic and Public Health, G. B. Rossi University Hospital, University of Verona, P.le L.A. Scuro 10, 37100 Verona, Italy.
Abstract
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.
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.
Authors: Charlotte Z Woods-Hill; Anping Xie; John Lin; Heather A Wolfe; Alex S Plattner; Sara Malone; Kathleen Chiotos; Julia E Szymczak Journal: JAC Antimicrob Resist Date: 2022-01-22
Authors: Claas Kirchhelle; Paul Atkinson; Alex Broom; Komatra Chuengsatiansup; Jorge Pinto Ferreira; Nicolas Fortané; Isabel Frost; Christoph Gradmann; Stephen Hinchliffe; Steven J Hoffman; Javier Lezaun; Susan Nayiga; Kevin Outterson; Scott H Podolsky; Stephanie Raymond; Adam P Roberts; Andrew C Singer; Anthony D So; Luechai Sringernyuang; Elizabeth Tayler; Susan Rogers Van Katwyk; Clare I R Chandler Journal: BMJ Glob Health Date: 2020-09