{"database":"biostudies-literature","file_versions":[],"scores":{"citationCount":0,"reanalysisCount":0,"viewCount":45,"searchCount":0},"additional":{"submitter":["Piotrowska MJ"],"funding":["Bundesministerium für Bildung und Forschung","Narodowe Centrum Nauki","ZonMw","Joint Programming Initiative on Antimicrobial Resistance"],"pagination":["e1008442"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC7728397"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["16(11)"],"pubmed_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."],"journal":["PLoS computational biology"],"pubmed_title":["Modelling pathogen spread in a healthcare network: Indirect patient movements."],"pmcid":["PMC7728397"],"funding_grant_id":["681055","01KI1704C","2016/22/Z/ST1/00690","547001005"],"pubmed_authors":["Tahir H","Sakowski K","Kretzschmar ME","Mikolajczyk RT","Horn J","Karch A","Piotrowska MJ"],"view_count":["45"],"additional_accession":[]},"is_claimable":false,"name":"Modelling pathogen spread in a healthcare network: Indirect patient movements.","description":"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.","dates":{"release":"2020-01-01T00:00:00Z","publication":"2020 Nov","modification":"2024-02-15T19:27:15.895Z","creation":"2021-02-20T13:44:11Z"},"accession":"S-EPMC7728397","cross_references":{"pubmed":["33253154"],"doi":["10.1371/journal.pcbi.1008442"]}}