Evidence map›Paper›PMID 33253154›Full record

ArticlePLoS computational biology2020

Modelling pathogen spread in a healthcare network: Indirect patient movements.

Monika J Piotrowska, Konrad Sakowski, André Karch, Hannan Tahir, Johannes Horn, Mirjam E Kretzschmar, Rafael T Mikolajczyk

Abstract read
In one paragraph

Article in PLoS computational biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Effect of an antibiotic stewardship program on antimicrobial use and resistance in a high prescribing, high resistance setting: A single-center, interrupted time series analysis.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2026
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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

7 authors.

Monika J PiotrowskaInstitute of Applied Mathematics and Mechanics, University of Warsaw, Warsaw, Poland.ORCID 0000-0003-0156-8290
Konrad SakowskiInstitute of Applied Mathematics and Mechanics, University of Warsaw, Warsaw, Poland.ORCID 0000-0003-1511-074X
André KarchInstitute for Epidemiology and Social Medicine, Münster, Germany.
Hannan TahirJulius Center for Health Sciences & Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.ORCID 0000-0003-3047-9174
Johannes HornInstitute for Medical Epidemiology, Biometrics and Informatics, Martin Luther University Halle-Wittenberg, Halle (Saale), Germany.
Mirjam E KretzschmarJulius Center for Health Sciences & Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.ORCID 0000-0002-4394-7697
Rafael T MikolajczykInstitute for Medical Epidemiology, Biometrics and Informatics, Martin Luther University Halle-Wittenberg, Halle (Saale), Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Inter-hospital patient transfers (direct transfers) between healthcare facilities have been shown to contribute to the spread of pathogens in a healthcare network. However, the impact of indirect transfers (patients re-admitted from the community to the same or different hospital) is not well studied. This work aims to study the contribution of indirect transfers to the spread of pathogens in a healthcare network. To address this aim, a hybrid network-deterministic model to simulate the spread of multiresistant pathogens in a healthcare system was developed for the region of Lower Saxony (Germany). The model accounts for both, direct and indirect transfers of patients. Intra-hospital pathogen transmission is governed by a SIS model expressed by a system of ordinary differential equations. Our results show that the proposed model reproduces the basic properties of healthcare-associated pathogen spread. They also show the importance of indirect transfers: restricting the pathogen spread to direct transfers only leads to 4.2% system wide prevalence. However, adding indirect transfers leads to an increase in the overall prevalence by a factor of 4 (18%). In addition, we demonstrated that the final prevalence in the individual healthcare facilities depends on average length of stay in a way described by a non-linear concave function. Moreover, we demonstrate that the network parameters of the model may be derived from administrative admission/discharge records. In particular, they are sufficient to obtain inter-hospital transfer probabilities, and to express the patients' transfers as a Markov process. Using the proposed model, we show that indirect transfers of patients are equally or even more important as direct transfers for the spread of pathogens in a healthcare network.

Indexed as

Models, TheoreticalPatient TransferCross InfectionGermanyHumansLength of StayPrevalenceProbability

Identifiers

PMID33253154
PMCPMC7728397

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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.