Evidence map›Paper›PMID 41394022›Full record

ArticleBMJ public health2025

Impact of COVID-19 non-pharmaceutical interventions on bacterial infections in children: an international electronic health record-based study.

Joany M Zachariasse, Alba Gutiérrez-Sacristán, Simran Makwana, Xiudi Li, Surbhi Bhatnagar, David A Hanauer, Mundeep K Kainth, Michele Morris, Paula Rubio-Mayo, Carlos Sáez and 19 more

Abstract read
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In one paragraph

Article in BMJ public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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

29 authors.

Joany M ZachariasseDepartment of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA.
Alba Gutiérrez-SacristánDepartment of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA.ORCID https://orcid.org/0000-0002-1245-198X
Simran MakwanaDepartment of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA.
Xiudi LiDepartment of Biostatistics, Harvard School of Public Health, Boston, Massachusetts, USA.
Surbhi BhatnagarDivision of Biomedical Informatics, University of Cincinnati, Cincinnati, Ohio, USA.
David A HanauerDepartment of Learning Health Sciences, University of Michigan-Ann Arbor, Ann Arbor, Michigan, USA.
Mundeep K KainthDepartment of Pediatrics, Cohen Children's Medical Center, New York, New York, USA.
Michele MorrisDepartment of Biomedical Informatics, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
Paula Rubio-MayoHealth Informatics, Hospital Universitario 12 de Octubre, Madrid, Spain.
Carlos SáezBiomedical Data Science Lab, Instituto Universitario de Tecnologías de la Información y Comunicaciones, Universitat Politècnica de València, Valencia, Spain.
Mohsin Ali ShahDigital Research, Informatics and Virtual Environments (DRIVE), Great Ormond Street Hospital for Children, London, England, UK.ORCID https://orcid.org/0000-0003-2563-319X
Bruce J AronowDepartments of Biomedical Informatics, Pediatrics, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA.
Rafael BadenesDepartment of Anesthesiology, SurgicalTrauma Intensive Care and Pain Clinic, Hospital Clinico Universitario de Valencia, Valencia, Spain.
Tianxi CaiDepartment of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA.
Noelia Garcia BarrioHealth Informatics, Hospital Universitario 12 de Octubre, Madrid, Spain.
Richard W IssittDigital Research, Informatics and Virtual Environments (DRIVE), Great Ormond Street Hospital for Children, London, England, UK.
Kenneth D MandlComputational Health Informatics Program, Boston Children's Hospital, Boston, Massachusetts, USA.
Gregorio P MilaniDepartment of Clinical Science and Community Health, University of Milan, Milan, Italy.
Karyn MoshalDepartment of Infectious Diseases, Great Ormond Street Hospital for Children NHS Trust, London, UK.
Jane W NewburgerDepartment of Cardiology, Boston Children's Hospital, Boston, Massachusetts, USA.
Gilbert S OmennDepartments of Computational Medicine and Bioinformatics, Internal Medicine, Human Genetics, Environmental Health, University of Michigan, Ann Arbor, Michigan, USA.
Nekane Romero-GarciaDepartment of Anesthesiology, SurgicalTrauma Intensive Care and Pain Clinic, Hospital Clinico Universitario de Valencia, Valencia, Spain.
Francesca SperottoDepartment of Cardiology, Boston Children's Hospital, Boston, Massachusetts, USA.
Anastasia SpiridouGenomic Medicine, Great Ormond Street Hospital for Children, London, UK.
Shyam VisweswaranDepartment of Biomedical Informatics, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
Zongqi XiaDepartment of Neurology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
Florence T BourgeoisDepartment of Pediatrics, Harvard Medical School, Boston, Massachusetts, USA.
Paul AvillachDepartment of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA.ORCID https://orcid.org/0000-0002-0235-7543
Consortium for Clinical Characterization of COVID-19 by EHR (4CE)

Funding

Strategic Vision & Impact on Environmental HealthP30ES017885 · NIEHS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Dana Dolinoy · 2011 to 2026
$21.3M
Leveraging electronic health records to optimize treatment selection and response in multiple sclerosisR01NS098023 · NINDS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Zongqi Xia · 2016 to 2026
$4.6M
NIEHS NIH HHS P30 ES017885NINDS NIH HHS R01 NS098023
6 · The paper itself

Abstract

Introduction: Non-pharmaceutical interventions (NPIs) such as mask-wearing and social distancing, implemented as public health measures to slow COVID-19 transmission, had a major impact on the epidemiology of viral infections. However, little is known about their influence on bacterial infections in children. Methods: We performed a multicentre observational study including eight hospitals in three countries (Spain, UK and USA). All hospitalisations in children under the age of 18 from January 2019 to February 2023 were included. Electronic health record data were used to assess changes in hospitalisations for bacterial infections in three different periods based on NPI stringency, classified as pre-NPI (January 2019 to February 2020), full NPI (March 2020 to February 2021) and partial NPI (March 2021 to February 2023). The primary outcomes were the counts of hospitalisations for invasive, respiratory and skin-associated bacterial infections. To identify changes in the monthly counts of bacterial infections in a data-driven manner, we used a multivariable quasi-Poisson regression model adjusting for important covariates with adaptive lasso penalty. We then assessed the statistical significance of the identified changes and examined the temporal trend before and after each change point. Results: We found that of the 508 585 paediatric hospitalisations, 41 076 (8.1%) were associated with any bacterial infection. 14 656 (35.7%) were invasive bacterial infections, 6763 (16.5%) were respiratory tract-associated and 7757 (18.9%) were skin-associated. Counts of bacterial infections decreased during the full-NPI period (average count 93.7 infections/month) compared with the pre-NPI period (average count 104.8 infections/month) and increased during the partial NPI period (average count 112.4 infections/month). A quasi-Poisson regression model showed a significant decrease in respiratory tract-associated bacterial infections after the start of the COVID-19 pandemic and a subsequent significant increase after the gradual lifting of NPIs, peaking during the winter of 2022-2023. No significant changes were observed over time for skin-associated and invasive bacterial infections. Conclusions: The implementation of COVID-19 NPIs was significantly associated with changes in hospitalisations for respiratory associated-bacterial infections, but not invasive and skin-associated bacterial infections. These findings suggest that the impact of NPIs has been greatest for respiratory infections and indicate the potential of targeted NPIs to reduce these infections among children in the future.

Indexed as

Disease OutbreaksDisease Transmission, InfectiousPublic Health

Identifiers

PMID41394022
PMCPMC12699615

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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.