Evidence map›Paper›PMID 38880893›Full record

SynthesisBMC infectious diseases2024

How to protect long-term care facilities from pandemic-like events? - A systematic review on the effectiveness of non-pharmacological measures to prevent viral respiratory infections.

Laura Arnold, Simon Bimczok, Hannah Schütt, Stefanie Lisak-Wahl, Barbara Buchberger, Jan M Stratil

Abstract readSystematic Review
In one paragraph

Synthesis in BMC infectious diseases, 2024. 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. Trial
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. [Recommendations on prevention and treatment of respiratory infections in institutionalised older people].Revista espanola de quimioterapia : publicacion oficial de la Sociedad Espanola de Quimioterapia · 2025
    Review
  8. Article
  9. Review
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

6 authors.

Laura ArnoldAcademy of Public Health Services, Kanzlerstraße 4, Duesseldorf, 40472, Germany.ORCID http://orcid.org/0000-0002-2573-3644
Simon BimczokAcademy of Public Health Services, Kanzlerstraße 4, Duesseldorf, 40472, Germany.
Hannah SchüttAcademy of Public Health Services, Kanzlerstraße 4, Duesseldorf, 40472, Germany.
Stefanie Lisak-WahlAcademy of Public Health Services, Kanzlerstraße 4, Duesseldorf, 40472, Germany.
Barbara BuchbergerRobert Koch Institute, Berlin, Germany.
Jan M StratilRobert Koch Institute, Berlin, Germany. stratilJ@rki.de.ORCID http://orcid.org/0000-0002-7905-0558

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe SARS-CoV-2 pandemic underscored the need for pandemic preparedness, with respiratory-transmitted viruses considered as a substantial risk. In pandemics, long-term care facilities (LTCFs) are a high-risk setting with severe outbreaks and burden of disease. Non-pharmacological interventions (NPIs) constitute the primary defence mechanism when pharmacological interventions are not available. However, evidence on the effectiveness of NPIs implemented in LTCFs remains unclear.

methodsWe conducted a systematic review assessing the effectiveness of NPIs implemented in LTCFs to protect residents and staff from viral respiratory pathogens with pandemic potential. We searched Medline, Embase, CINAHL, and two COVID-19 registries in 09/2022. Screening and data extraction was conducted independently by two experienced researchers. We included randomized controlled trials and non-randomized observational studies of intervention effects. Quality appraisal was conducted using ROBINS-I and RoB2. Primary outcomes encompassed number of outbreaks, infections, hospitalizations, and deaths. We synthesized findings narratively, focusing on the direction of effect. Certainty of evidence (CoE) was assessed using GRADE.

resultsWe analysed 13 observational studies and three (cluster) randomized controlled trials. All studies were conducted in high-income countries, all but three focused on SARS-CoV-2 with the rest focusing on influenza or upper-respiratory tract infections. The evidence indicates that a combination of different measures and hand hygiene interventions can be effective in protecting residents and staff from infection-related outcomes (moderate CoE). Self-confinement of staff with residents, compartmentalization of staff in the LTCF, and the routine testing of residents and/or staff in LTCFs, among others, may be effective (low CoE). Other measures, such as restricting shared spaces, serving meals in room, cohorting infected and non-infected residents may be effective (very low CoE). An evidence gap map highlights the lack of evidence on important interventions, encompassing visiting restrictions, pre-entry testing, and air filtration systems.

conclusionsAlthough CoE of interventions was low or very low for most outcomes, the implementation of NPIs identified as potentially effective in this review often constitutes the sole viable option, particularly prior to the availability of vaccinations. Our evidence-gap map underscores the imperative for further research on several interventions. These gaps need to be addressed to prepare LTCFs for future pandemics.

trial registrationCRD42022344149.

Indexed as

COVID-19Long-Term CareRespiratory Tract InfectionsSARS-CoV-2HumansInfection ControlPandemicsRandomized Controlled Trials as TopicCommunicable disease controlCOVID-19HygieneInfluenzaMandatory testingNursing homesPandemicsPhysical distancingPublic health practiceRespiratory tract infections

Identifiers

PMID38880893
PMCPMC11181531

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.