Evidence map›Paper›PMID 38118007›Full record

ArticleClinical infectious diseases : an official publication of the Infectious Diseases Society of America2023

Methodological Approach to Identify and Expand the Volume of Antimicrobial Resistance (AMR) Data in the Human Health Sector in Low- and Middle-Income Countries in Asia: Implications for Local and Regional AMR Surveillance Systems Strengthening.

Hea Sun Joh, Corin Yeats, Alina Shaw, Nimesh Poudyal, Patrick Gallagher, Jong-Hoon Kim, Affan Shaikh, Hye Jin Seo, Kyu-Young Kevin Chi, Kristi Prifti and 22 more

Abstract read
In one paragraph

Article in Clinical infectious diseases : an official publication of the Infectious Diseases Society of America, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Review
  2. Review
  3. CAPTURA Regional Workshop Proceedings (28-30 June 2022, Virtual).Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2023
    Article
  4. Key Recommendations for Antimicrobial Resistance Surveillance: Takeaways From the CAPTURA Project.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2023
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

32 authors.

Hea Sun JohInternational Vaccine Institute, Seoul, Republic of Korea.ORCID 0000-0002-2107-0919
Corin YeatsCentre for Genomic Pathogen Surveillance, Big Data Institute, University of Oxford, Oxford, United Kingdom.
Alina ShawPublic Health Surveillance Group, LLC, Princeton, New Jersey, USA.
Nimesh PoudyalInternational Vaccine Institute, Seoul, Republic of Korea.
Patrick GallagherPublic Health Surveillance Group, LLC, Princeton, New Jersey, USA.
Jong-Hoon KimInternational Vaccine Institute, Seoul, Republic of Korea.
Affan ShaikhPublic Health Surveillance Group, LLC, Princeton, New Jersey, USA.
Hye Jin SeoInternational Vaccine Institute, Seoul, Republic of Korea.
Kyu-Young Kevin ChiInternational Vaccine Institute, Seoul, Republic of Korea.
Kristi PriftiInternational Vaccine Institute, Seoul, Republic of Korea.
Alyssa ChoInternational Vaccine Institute, Seoul, Republic of Korea.
Mohammad Julhas SujanInternational Vaccine Institute, Seoul, Republic of Korea.
Emmanuel EralyInternational Vaccine Institute, Seoul, Republic of Korea.
Kien Duc PhamInternational Vaccine Institute, Seoul, Republic of Korea.
Subha ShresthaInternational Vaccine Institute, Seoul, Republic of Korea.
Ahmed Taha AboushadyInternational Vaccine Institute, Seoul, Republic of Korea.
Gideok PakInternational Vaccine Institute, Seoul, Republic of Korea.
GeunHyeog JangInternational Vaccine Institute, Seoul, Republic of Korea.
Eun Lyeong ParkInternational Vaccine Institute, Seoul, Republic of Korea.
Hyeong-Won SeoInternational Vaccine Institute, Seoul, Republic of Korea.
Khalil AbudahabCentre for Genomic Pathogen Surveillance, Big Data Institute, University of Oxford, Oxford, United Kingdom.
Ben E W TaylorCentre for Genomic Pathogen Surveillance, Big Data Institute, University of Oxford, Oxford, United Kingdom.
Adam ClarkBrigham & Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.
Brooke DolabellaPublic Health Surveillance Group, LLC, Princeton, New Jersey, USA.
Hyein YoonInternational Vaccine Institute, Seoul, Republic of Korea.
Jihyun HanInternational Vaccine Institute, Seoul, Republic of Korea.
Soo Young KwonInternational Vaccine Institute, Seoul, Republic of Korea.
Florian MarksInternational Vaccine Institute, Seoul, Republic of Korea.
John StellingBrigham & Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.
David M AanensenCentre for Genomic Pathogen Surveillance, Big Data Institute, University of Oxford, Oxford, United Kingdom.
William R MacWrightPublic Health Surveillance Group, LLC, Princeton, New Jersey, USA.
Marianne HolmInternational Vaccine Institute, Seoul, Republic of Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Antimicrobial resistance (AMR) is a multifaceted global health problem disproportionately affecting low- and middle-income countries (LMICs). The Capturing data on Antimicrobial resistance Patterns and Trends in Use in Regions of Asia (CAPTURA) project was tasked to expand the volume of AMR and antimicrobial use data in Asia. The CAPTURA project used 2 data-collection streams: facility data and project metadata. Project metadata constituted information collected to map out data sources and assess data quality, while facility data referred to the retrospective data collected from healthcare facilities. A down-selection process, labelled "the funnel approach" by the project, was adopted to use the project metadata in prioritizing and selecting laboratories for retrospective AMR data collection. Moreover, the metadata served as a guide for understanding the AMR data once they were collected. The findings from CAPTURA's metadata add to the current discourse on the limitation of AMR data in LMICs. There is generally a low volume of AMR data generated as there is a lack of microbiology laboratories with sufficient antimicrobial susceptibility testing capacity. Many laboratories in Asia are still capturing data on paper, resulting in scattered or unused data not readily accessible or shareable for analyses. There is also a lack of clinical and epidemiological data captured, impeding interpretation and in-depth understanding of the AMR data. CAPTURA's experience in Asia suggests that there is a wide spectrum of capacity and capability of microbiology laboratories within a country and region. As local AMR surveillance is a crucial instrument to inform context-specific measures to combat AMR, it is important to understand and assess current capacity-building needs while implementing activities to enhance surveillance systems.

Indexed as

Anti-Bacterial AgentsDeveloping CountriesAsiaDrug Resistance, BacterialHumansRetrospective StudiesAnti-Bacterial AgentsAMR surveillanceAntimicrobial Resistance (AMR)capacity buildingCAPTURAproject implementation

Identifiers

PMID38118007
PMCPMC10732564

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.