Evidence map›Paper›PMID 39816251›Full record

ArticleFrontiers in antibiotics2024

Epidemiology of antibiotic consumption and resistance in Mauritius.

Lovena Preeyadarshini Veerapa-Mangroo, Harena Rasamoelina-Andriamanivo, Mohammad Iqbal Issack, Eric Cardinale

Abstract read
In one paragraph

Article in Frontiers in antibiotics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Lovena Preeyadarshini Veerapa-MangrooSurveillance Epidemiologique et Gestion des Alertes (SEGA) One Health network, Indian Ocean Commission, Ebene, Mauritius.
Harena Rasamoelina-AndriamanivoSurveillance Epidemiologique et Gestion des Alertes (SEGA) One Health network, Indian Ocean Commission, Ebene, Mauritius.
Mohammad Iqbal IssackSurveillance Epidemiologique et Gestion des Alertes (SEGA) One Health network, Indian Ocean Commission, Ebene, Mauritius.
Eric CardinaleSurveillance Epidemiologique et Gestion des Alertes (SEGA) One Health network, Indian Ocean Commission, Ebene, Mauritius.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: This study aims at determining the pattern of antibiotic consumption and resistance in Mauritius, a tropical island in the Indian Ocean. Methodology: Antibiotic consumption was measured in kilograms of purchased antibiotics and also in defined daily dose (DDD) in different health institutions from 2015 to 2017. Data on antibiotic resistance was collected at the Central Health Laboratory (CHL) at Victoria Hospital and at Jeetoo Hospital Laboratory, where antibiotic sensitivity testing is done for all public health institutions. For this study, Results: The amount of antibiotics (in kilograms) distributed to the human sector was between 11,000 to 13,000 kg, compared to only 700 to 1,500 kg in the animal sector. The DDD per 1,000 inhabitants per day was 20.9, 22.1, and 21.7 in 2015, 2016, and 2017, respectively, with a greater consumption of WATCH and RESERVE group antibiotics in the private sector. In public health institutions, health centers in the northern region had the highest DDD per 1,000 outpatients per day for beta-lactams penicillins and quinolones. Concerning antibiotic resistance, the proportion of MDR Conclusion: This study provides valuable insights on antibiotic consumption and resistance in the country and emphasizes the significance of adopting a One Health approach to combat antimicrobial resistance (AMR) effectively. These findings will aid policymakers in formulating targeted strategies to address the challenge of AMR and should be integrated into the National Action Plan on AMR in Mauritius.

Indexed as

antibiotic consumptionantibiotic resistancedefined daily doseepidemiologyhuman and animal sectorMauritiusmulti-drug resistant organismstropical island

Identifiers

PMID39816251
PMCPMC11732136

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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.