Gerardo Alvarez-Uria1, Sumanth Gandra2, Ramanan Laxminarayan3. 1. Department of Infectious Diseases, Rural Development Trust Hospital, Bathalapalli, Andhra Pradesh, India. 2. Center for Disease Dynamics, Economics and Policy, New Delhi, India. 3. Center for Disease Dynamics, Economics and Policy, New Delhi, India; Public Health Foundation of India, Gurgaon, India; Princeton Environmental Institute, Princeton, New Jersey, USA; Center for Disease Dynamics, Economics and Policy, 1400 Eye Street NW, Suite 500, Washington, DC, 20005, USA. Electronic address: ramanan@cddep.org.
Abstract
OBJECTIVES: To evaluate the association between the income status of a country and the prevalence of antimicrobial resistance (AMR) in the three most common bacteria causing infections in hospitals and in the community: third-generation cephalosporin (3GC)-resistant Escherichia coli, methicillin-resistant Staphylococcus aureus (MRSA), and 3GC-resistant Klebsiella species. METHODS: Using 2013-2014 country-specific data from the ResistanceMap repository and the World Bank, the association between the prevalence of AMR in invasive samples and the gross national income (GNI) per capita was investigated through linear regression with robust standard errors. To account for non-linear association with the dependent variable, GNI per capita was log-transformed. RESULTS: The models predicted an 11.3% (95% confidence interval (CI) 6.5-16.2%), 18.2% (95% CI 11-25.5%), and 12.3% (95% CI 5.5-19.1%) decrease in the prevalence of 3GC-resistant E. coli, 3GC-resistant Klebsiella species, and MRSA, respectively, for each log GNI per capita. The association was stronger for 3GC-resistant E. coli and Klebsiella species than for MRSA. CONCLUSIONS: A significant negative association between GNI per capita and the prevalence of MRSA and 3GC-resistant E. coli and Klebsiella species was found. These results underscore the urgent need for new policies aimed at reducing AMR in resource-poor settings.
OBJECTIVES: To evaluate the association between the income status of a country and the prevalence of antimicrobial resistance (AMR) in the three most common bacteria causing infections in hospitals and in the community: third-generation cephalosporin (3GC)-resistant Escherichia coli, methicillin-resistant Staphylococcus aureus (MRSA), and 3GC-resistant Klebsiella species. METHODS: Using 2013-2014 country-specific data from the ResistanceMap repository and the World Bank, the association between the prevalence of AMR in invasive samples and the gross national income (GNI) per capita was investigated through linear regression with robust standard errors. To account for non-linear association with the dependent variable, GNI per capita was log-transformed. RESULTS: The models predicted an 11.3% (95% confidence interval (CI) 6.5-16.2%), 18.2% (95% CI 11-25.5%), and 12.3% (95% CI 5.5-19.1%) decrease in the prevalence of 3GC-resistant E. coli, 3GC-resistant Klebsiella species, and MRSA, respectively, for each log GNI per capita. The association was stronger for 3GC-resistant E. coli and Klebsiella species than for MRSA. CONCLUSIONS: A significant negative association between GNI per capita and the prevalence of MRSA and 3GC-resistant E. coli and Klebsiella species was found. These results underscore the urgent need for new policies aimed at reducing AMR in resource-poor settings.
Authors: Michael Brandl; Alexandra Hoffmann; Niklas Willrich; Annicka Reuss; Felix Reichert; Jan Walter; Tim Eckmanns; Sebastian Haller Journal: Microorganisms Date: 2021-04-22