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Surveillance strategies using routine microbiology for antimicrobial resistance in low- and middle-income countries.
Lim, Cherry; Ashley, Elizabeth A; Hamers, Raph L; Turner, Paul; Kesteman, Thomas; Akech, Samuel; Corso, Alejandra; Mayxay, Mayfong; Okeke, Iruka N; Limmathurotsakul, Direk; van Doorn, H Rogier.
Afiliação
  • Lim C; Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand; Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK. Electronic address: cherry@tropmedres.ac.
  • Ashley EA; Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK; Lao-Oxford-Mahosot Hospital Wellcome Trust Research Unit, Vientiane, Laos.
  • Hamers RL; Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK; Eijkman-Oxford Clinical Research Unit, Jakarta, Indonesia.
  • Turner P; Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK; Cambodia Oxford Medical Research Unit, Angkor Hospital for Children, Siem Reap, Cambodia.
  • Kesteman T; Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK; Oxford University Clinical Research Unit, National Hospital for Tropical Diseases, Hanoi, Viet Nam.
  • Akech S; KEMRI-Wellcome Trust Research Programme, Nairobi, Kenya.
  • Corso A; National/Regional Reference Laboratory for Antimicrobial Resistance (NRL), Servicio Antimicrobianos, Instituto Nacional de Enfermedades Infecciosas ANLIS Dr. Carlos G. Malbrán, Buenos Aires, Argentina.
  • Mayxay M; Lao-Oxford-Mahosot Hospital Wellcome Trust Research Unit, Vientiane, Laos; Institute of Research and Education Development (IRED), University of Health Sciences, Vientiane, Laos.
  • Okeke IN; Department of Pharmaceutical Microbiology, Faculty of Pharmacy, University of Ibadan, Ibadan, Nigeria.
  • Limmathurotsakul D; Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand; Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
  • van Doorn HR; Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK; Oxford University Clinical Research Unit, National Hospital for Tropical Diseases, Hanoi, Viet Nam. Electronic address: rvandoorn@oucru.org.
Clin Microbiol Infect ; 27(10): 1391-1399, 2021 Oct.
Article em En | MEDLINE | ID: mdl-34111583
BACKGROUND: Routine microbiology results are a valuable source of antimicrobial resistance (AMR) surveillance data in low- and middle-income countries (LMICs) as well as in high-income countries. Different approaches and strategies are used to generate AMR surveillance data. OBJECTIVES: We aimed to review strategies for AMR surveillance using routine microbiology results in LMICs and to highlight areas that need support to generate high-quality AMR data. SOURCES: We searched PubMed for papers that used routine microbiology to describe the epidemiology of AMR and drug-resistant infections in LMICs. We also included papers that, from our perspective, were critical in highlighting the biases and challenges or employed specific strategies to overcome these in reporting AMR surveillance in LMICs. CONTENT: Topics covered included strategies of identifying AMR cases (including case-finding based on isolates from routine diagnostic specimens and case-based surveillance of clinical syndromes), of collecting data (including cohort, point-prevalence survey, and case-control), of sampling AMR cases (including lot quality assurance surveys), and of processing and analysing data for AMR surveillance in LMICs. IMPLICATIONS: The various AMR surveillance strategies warrant a thorough understanding of their limitations and potential biases to ensure maximum utilization and interpretation of local routine microbiology data across time and space. For instance, surveillance using case-finding based on results from clinical diagnostic specimens is relatively easy to implement and sustain in LMIC settings, but the estimates of incidence and proportion of AMR is at risk of biases due to underuse of microbiology. Case-based surveillance of clinical syndromes generates informative statistics that can be translated to clinical practices but needs financial and technical support as well as locally tailored trainings to sustain. Innovative AMR surveillance strategies that can easily be implemented and sustained with minimal costs will be useful for improving AMR data availability and quality in LMICs.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Farmacorresistência Bacteriana / Monitoramento Epidemiológico / Antibacterianos Tipo de estudo: Prognostic_studies / Risk_factors_studies / Screening_studies Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Farmacorresistência Bacteriana / Monitoramento Epidemiológico / Antibacterianos Tipo de estudo: Prognostic_studies / Risk_factors_studies / Screening_studies Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article