A Platform for Monitoring Regional Antimicrobial Resistance, Using Online Data Sources: ResistanceOpen. (14th November 2016)

• Record Type: Journal Article
• Authors: MacFadden, Derek R.; Fisman, David; Andre, Jeff; Ara, Yuki; Majumder, Maimuna S.; Bogoch, Isaac I.; Daneman, Nick; Wang, Annie; Vavitsas, Marianna; Castellani, Lucas; Brownstein, John S.
• Is Part Of: Journal of infectious diseases. Volume 214(2016)Supplement 4
• Page Start: S393
• Page End: S398
• Publication Date: 2016-11-14
• Subjects: antimicrobial resistance -- antibiotic resistance -- surveillance -- big data -- digital surveillance -- digital disease detection; Communicable diseases -- Periodicals; Diseases -- Causes and theories of causation -- Periodicals; Medicine -- Periodicals; Communicable Diseases -- Periodicals; Electronic journals; 616.9
• DOI: 10.1093/infdis/jiw343
• Languages: English
• ISSNs: 0022-1899

Abstract

Abstract : Background: Our understanding of the global burden of antimicrobial resistance is limited. Complementary approaches to antimicrobial resistance surveillance are needed. Methods: We developed a Web-based/mobile platform for aggregating, analyzing, and disseminating regional antimicrobial resistance information. Antimicrobial resistance indices from existing but disparate online sources were identified and abstracted. To validate antimicrobial resistance data, in the absence of regional comparators, US and Canadian indices were aggregated and compared to existing national and state estimates. Measures of variability of antimicrobial susceptibility were determined for the United States and Canada to evaluate magnitudes of differences within countries. Results: Over 850 resistance indices globally were identified and abstracted, totaling >5 million isolates, from 340 unique locations. Resistance index coverage spanned 41 countries, 6 continents, 43 of 50 US states, and 8 of 10 Canadian provinces. When compared to reported values, aggregated resistance values for the United States and Canada during 2013 and 2014 demonstrated agreements ranging from 94% to 97%. For the United States, state-specific resistance estimates demonstrated an agreement of 92%. Large differences in antimicrobial susceptibility were seen within countries. Conclusions: Using existing nontraditional data sources, we have developed a Web-based platform for aggregating antimicrobial resistance indices to support monitoring of regional antimicrobial resistance patterns.