Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/114084
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Type: | Journal article |
Title: | Scabies in residential care homes: modelling, inference and interventions for well-connected population sub-units |
Author: | Kinyanjui, T. Middleton, J. Güttel, S. Cassell, J. Ross, J. House, T. |
Citation: | PLoS Computational Biology, 2018; 14(3):e1006046-1-e1006046-24 |
Publisher: | Public Library of Science (PLoS) |
Issue Date: | 2018 |
ISSN: | 1553-734X 1553-7358 |
Editor: | Alizon, S. |
Statement of Responsibility: | Timothy Kinyanjui, Jo Middleton, Stefan GuÈ ttel, Jackie Cassell, Joshua Ross, Thomas House |
Abstract: | In the context of an ageing population, understanding the transmission of infectious diseases such as scabies through well-connected sub-units of the population, such as residential care homes, is particularly important for the design of efficient interventions to mitigate against the effects of those diseases. Here, we present a modelling methodology based on the efficient solution of a large-scale system of linear differential equations that allows statistical calibration of individual-based random models to real data on scabies in residential care homes. In particular, we review and benchmark different numerical methods for the integration of the differential equation system, and then select the most appropriate of these methods to perform inference using Markov chain Monte Carlo. We test the goodness-of-fit of this model using posterior predictive intervals and propagate forward the resulting parameter uncertainty in a Bayesian framework to consider the economic cost of delayed interventions against scabies, quantifying the benefits of prompt action in the event of detection. We also revisit the previous methodology used to assess the safety of treatments in small population sub-units—in this context ivermectin—and demonstrate that even a very slight relaxation of the implicit assumption of homogeneous death rates significantly increases the plausibility of the hypothesis that ivermectin does not cause excess mortality based upon the data of Barkwell and Shields. |
Keywords: | Humans Communicable Diseases Scabies Ivermectin Monte Carlo Method Bayes Theorem Markov Chains Communicable Disease Control Residential Facilities |
Description: | Published: March 26, 2018 |
Rights: | © 2018 Kinyanjui et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
DOI: | 10.1371/journal.pcbi.1006046 |
Grant ID: | http://purl.org/au-research/grants/arc/FT130100254 |
Published version: | http://dx.doi.org/10.1371/journal.pcbi.1006046 |
Appears in Collections: | Aurora harvest 8 Mathematical Sciences publications |
Files in This Item:
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hdl_114084.pdf | Published version | 4.75 MB | Adobe PDF | View/Open |
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