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Rethinking Antimicrobial Resistance Surveillance: A Role for Lot Quality Assurance Sampling
Global surveillance of antimicrobial resistance (AMR) is a key component of the 68th World Health Assembly Global Action Plan on AMR. Laboratory-based surveillance is inherently biased and lacks local relevance due to aggregation of data. We assessed the feasibility, sensitivity, and affordability o...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6438814/ https://www.ncbi.nlm.nih.gov/pubmed/30608516 http://dx.doi.org/10.1093/aje/kwy276 |
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author | Ginting, Franciscus Sugianli, Adhi Kristianto Bijl, Gidion Saragih, Restuti Hidayani Kusumawati, R Lia Parwati, Ida de Jong, Menno D Schultsz, Constance van Leth, Frank |
author_facet | Ginting, Franciscus Sugianli, Adhi Kristianto Bijl, Gidion Saragih, Restuti Hidayani Kusumawati, R Lia Parwati, Ida de Jong, Menno D Schultsz, Constance van Leth, Frank |
author_sort | Ginting, Franciscus |
collection | PubMed |
description | Global surveillance of antimicrobial resistance (AMR) is a key component of the 68th World Health Assembly Global Action Plan on AMR. Laboratory-based surveillance is inherently biased and lacks local relevance due to aggregation of data. We assessed the feasibility, sensitivity, and affordability of a population-based AMR survey using lot quality assurance sampling (LQAS), which classifies a population as having a high or low prevalence of AMR based on a priori defined criteria. Three studies were carried out in Medan and Bandung, Indonesia, between April 2014 and June 2017. LQAS classifications for 15 antibiotics were compared with AMR estimates from a conventional population-based survey, with an assessment of the cost of a single LQAS classification using microcosting methodology, among patients suspected of urinary tract infection at 11 sites in Indonesia. The sensitivity of LQAS was above 98%. The approach detected local variation in the prevalence of AMR across sites. Time to reach LQAS results ranged from 47 to 138 days. The average cost of an LQAS classification in a single facility was US$466. The findings indicate that LQAS-based AMR survey is a feasible, sensitive, and affordable strategy for population-based AMR surveys, providing essential data to inform local empirical treatment guidelines and antimicrobial stewardship efforts. |
format | Online Article Text |
id | pubmed-6438814 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-64388142019-04-04 Rethinking Antimicrobial Resistance Surveillance: A Role for Lot Quality Assurance Sampling Ginting, Franciscus Sugianli, Adhi Kristianto Bijl, Gidion Saragih, Restuti Hidayani Kusumawati, R Lia Parwati, Ida de Jong, Menno D Schultsz, Constance van Leth, Frank Am J Epidemiol Practice of Epidemiology Global surveillance of antimicrobial resistance (AMR) is a key component of the 68th World Health Assembly Global Action Plan on AMR. Laboratory-based surveillance is inherently biased and lacks local relevance due to aggregation of data. We assessed the feasibility, sensitivity, and affordability of a population-based AMR survey using lot quality assurance sampling (LQAS), which classifies a population as having a high or low prevalence of AMR based on a priori defined criteria. Three studies were carried out in Medan and Bandung, Indonesia, between April 2014 and June 2017. LQAS classifications for 15 antibiotics were compared with AMR estimates from a conventional population-based survey, with an assessment of the cost of a single LQAS classification using microcosting methodology, among patients suspected of urinary tract infection at 11 sites in Indonesia. The sensitivity of LQAS was above 98%. The approach detected local variation in the prevalence of AMR across sites. Time to reach LQAS results ranged from 47 to 138 days. The average cost of an LQAS classification in a single facility was US$466. The findings indicate that LQAS-based AMR survey is a feasible, sensitive, and affordable strategy for population-based AMR surveys, providing essential data to inform local empirical treatment guidelines and antimicrobial stewardship efforts. Oxford University Press 2019-04 2019-01-04 /pmc/articles/PMC6438814/ /pubmed/30608516 http://dx.doi.org/10.1093/aje/kwy276 Text en © The Author(s) 2019. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. http://creativecommons.org/licenses/by-nc/4.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journalpermissions@oup.com. |
spellingShingle | Practice of Epidemiology Ginting, Franciscus Sugianli, Adhi Kristianto Bijl, Gidion Saragih, Restuti Hidayani Kusumawati, R Lia Parwati, Ida de Jong, Menno D Schultsz, Constance van Leth, Frank Rethinking Antimicrobial Resistance Surveillance: A Role for Lot Quality Assurance Sampling |
title | Rethinking Antimicrobial Resistance Surveillance: A Role for Lot Quality Assurance Sampling |
title_full | Rethinking Antimicrobial Resistance Surveillance: A Role for Lot Quality Assurance Sampling |
title_fullStr | Rethinking Antimicrobial Resistance Surveillance: A Role for Lot Quality Assurance Sampling |
title_full_unstemmed | Rethinking Antimicrobial Resistance Surveillance: A Role for Lot Quality Assurance Sampling |
title_short | Rethinking Antimicrobial Resistance Surveillance: A Role for Lot Quality Assurance Sampling |
title_sort | rethinking antimicrobial resistance surveillance: a role for lot quality assurance sampling |
topic | Practice of Epidemiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6438814/ https://www.ncbi.nlm.nih.gov/pubmed/30608516 http://dx.doi.org/10.1093/aje/kwy276 |
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