Evidence map›Paper›PMID 39875841›Full record

ArticleBMC microbiology2025

Changes in incidence and epidemiology of antimicrobial resistant pathogens before and during the COVID-19 pandemic in Germany, 2015-2022.

Jonathan H J Baum, Achim Dörre, Felix Reichert, Ines Noll, Marcel Feig, Tim Eckmanns, Mirco Sandfort, Sebastian Haller

Abstract read
In one paragraph

Article in BMC microbiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Incidence of colonization and infection with carbapenemase-producing Enterobacterales in Toronto and Peel Region, Ontario, 2007-2024.Journal of the Association of Medical Microbiology and Infectious Disease Canada = Journal officiel de l'Association pour la microbiologie medicale et l'infectiologie Canada · 2026
    Article
  3. Review
  4. Article
  5. Trends, Seasonality, and the Impact of COVID-19 on ClinicalAntibiotics (Basel, Switzerland) · 2026
    Article
  6. Article
  7. Review
  8. Article
  9. Epidemiological and Antimicrobial Resistance Trends ofInfection and drug resistance · 2025
    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

8 authors.

Jonathan H J BaumDepartment of Infectious Disease Epidemiology, Robert Koch Institute (RKI), Berlin, Germany.ORCID 0000-0002-9272-5863
Achim DörreDepartment of Infectious Disease Epidemiology, Robert Koch Institute (RKI), Berlin, Germany.ORCID 0000-0001-9297-3675
Felix ReichertDepartment of Infectious Disease Epidemiology, Robert Koch Institute (RKI), Berlin, Germany.ORCID 0000-0003-3205-3513
Ines NollDepartment of Infectious Disease Epidemiology, Robert Koch Institute (RKI), Berlin, Germany.
Marcel FeigDepartment of Method Development, Research Infrastructure and Information Technology, Robert Koch Institute (RKI), Berlin, Germany.ORCID 0009-0002-5251-8410
Tim EckmannsDepartment of Infectious Disease Epidemiology, Robert Koch Institute (RKI), Berlin, Germany.ORCID 0000-0002-4022-4944
Mirco Sandfort *Department of Infectious Disease Epidemiology, Robert Koch Institute (RKI), Berlin, Germany.ORCID 0000-0001-7078-6537
Sebastian Haller *Department of Infectious Disease Epidemiology, Robert Koch Institute (RKI), Berlin, Germany. HallerS@rki.de.ORCID 0000-0001-8242-711X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCarbapenem-resistant Gram-negative bacteria and methicillin-resistant Staphylococcus aureus (MRSA) are among WHO's priority pathogens with antimicrobial resistance (AMR). Studies suggest potential impacts of the COVID-19-pandemic on AMR. We described changes in AMR incidence and epidemiology in Germany during the COVID-19-pandemic.

methodsWe used two independent datasets, statutory surveillance and laboratory-based Antibiotic Resistance Surveillance (ARS). We included statutory notifications of infections/colonisations of carbapenem-resistant Acinetobacter spp., Klebsiella pneumoniae, Escherichia coli (CRA/CRKP/CREC) and invasive MRSA. Using Poisson/negative binomial regression and assuming continued pre-pandemic (2015/2017-2020) trends, we projected hypothetical notifications as if the pandemic had not occurred. We quantified annual changes during the pandemic period (2020-2022) by comparing to observed notifications. Additional models considered inpatient reductions, seasonality, infections only, or resistant isolates from ARS.

resultsCRA notified cases were reduced by -30% (95%CI -39%|-20%) in 2020, -23% (-36%|-8%) in 2021, but + 32% (+ 6%|+64%) higher in 2022 relative to hypothetical pre-pandemic projections. Changes were - 35%/-31%/+6% for CRKP, -40%/-61%/-48% for CREC and - 33%/-25%/-20% for MRSA. Statutory-models accounting for fewer inpatients, seasonality and infections only showed similar trends, as did ARS-models for resistant isolates and infections. International mobility for CRA, CRKP and CREC decreased in 2020-2021, then increased in 2022.

conclusionsWe observed significant reductions of AMR notifications and infections during 2020-2021, also when accounting for fewer inpatients. We conclude a genuine reduction of AMR spread occurred during the pandemic. Factors like fewer hospitalisations and reduced international mobility contributed. Rising international mobility may partly explain increases for CRA, CRKP and CREC in 2022. A solid understanding of AMR trends improves infection prevention and control.

Indexed as

Bacterial InfectionsCOVID-19Drug Resistance, BacterialAnti-Bacterial AgentsGermanyHumansIncidenceKlebsiella pneumoniaeMethicillin-Resistant Staphylococcus aureusPandemicsSARS-CoV-2Anti-Bacterial AgentsAcinetobacterAntimicrobial resistanceCOVID-19Drug resistanceEscherichia coliKlebsiella pneumoniaeMethicillin-resistant staphylococcus aureus

Identifiers

PMID39875841
PMCPMC11773696

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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.