Lopez Garcia, M orcid.org/0000-0003-3833-8595, Aruru, M and Pyne, S (2018) Health analytics and disease modeling for better understanding of healthcare-associated infections. BLDE University Journal of Health Sciences, 3 (2). pp. 69-74. ISSN 2468-838X
Abstract
Healthcare-associated infections (HAIs) are a growing challenge and a major cause of health concern worldwide. It is difficult to understand precisely the dynamics of spread of hospital-acquired infections owing to the usual involvement of different populations, risk factors, environments, and pathogens. Mathematical and computational models have proved to be useful tools in providing realistic representations of HAI dynamics and the means of evaluating interventions to minimize the risk of HAIs.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | (c) 2018, BLDE University Journal of Health Sciences. Published by Wolters Kluwer - Medknow. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-Share Alike License CC BY-NC-SA [https://creativecommons.org/licenses/by-nc-sa/3.0/] |
Keywords: | Agent-based modeling, compartmental modeling, hospital-acquired infections, nosocomial infections |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mathematics (Leeds) > Applied Mathematics (Leeds) |
Funding Information: | Funder Grant number MRC MR/N014855/1 |
Depositing User: | Symplectic Publications |
Date Deposited: | 21 Jan 2019 15:44 |
Last Modified: | 21 Jan 2019 15:44 |
Published Version: | http://www.bldeujournalhs.in/article.asp?issn=2468... |
Status: | Published |
Publisher: | Medknow Publications |
Identification Number: | 10.4103/bjhs.bjhs_36_18 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:140939 |
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