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Probabilistic differential diagnosis of Middle East respiratory syndrome (MERS) using the time from immigration to illness onset among imported cases
Middle East respiratory syndrome (MERS) has spread worldwide since 2012. As the clinical symptoms of MERS tend to be non-specific, the incubation period has been shown to complement differential diagnosis, especially to rule out influenza. However, because an infection event is seldom directly obser...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd.
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7094128/ https://www.ncbi.nlm.nih.gov/pubmed/24406808 http://dx.doi.org/10.1016/j.jtbi.2013.12.024 |
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author | Ejima, Keisuke Aihara, Kazuyuki Nishiura, Hiroshi |
author_facet | Ejima, Keisuke Aihara, Kazuyuki Nishiura, Hiroshi |
author_sort | Ejima, Keisuke |
collection | PubMed |
description | Middle East respiratory syndrome (MERS) has spread worldwide since 2012. As the clinical symptoms of MERS tend to be non-specific, the incubation period has been shown to complement differential diagnosis, especially to rule out influenza. However, because an infection event is seldom directly observable, the present study aims to construct a diagnostic model that predicts the probability of MERS diagnosis given the time from immigration to illness onset among imported cases which are suspected of MERS. Addressing censoring by considering the transmission dynamics in an exporting country, we demonstrate that the illness onset within 2 days from immigration is suggestive of influenza. Two exceptions to suspect MERS even for those with illness onset within 2 days since immigration are (i) when we observe substantial community transmissions of MERS and (ii) when the cases are at high risk of MERS (e.g. cases with close contact in hospital or household). It is vital to collect the information of the incubation period upon emergence of a novel infectious disease, and moreover, in our model, the fundamental transmission dynamics including the initial growth rate has to be explored to differentiate the disease diagnoses with non-specific symptoms. |
format | Online Article Text |
id | pubmed-7094128 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-70941282020-03-25 Probabilistic differential diagnosis of Middle East respiratory syndrome (MERS) using the time from immigration to illness onset among imported cases Ejima, Keisuke Aihara, Kazuyuki Nishiura, Hiroshi J Theor Biol Article Middle East respiratory syndrome (MERS) has spread worldwide since 2012. As the clinical symptoms of MERS tend to be non-specific, the incubation period has been shown to complement differential diagnosis, especially to rule out influenza. However, because an infection event is seldom directly observable, the present study aims to construct a diagnostic model that predicts the probability of MERS diagnosis given the time from immigration to illness onset among imported cases which are suspected of MERS. Addressing censoring by considering the transmission dynamics in an exporting country, we demonstrate that the illness onset within 2 days from immigration is suggestive of influenza. Two exceptions to suspect MERS even for those with illness onset within 2 days since immigration are (i) when we observe substantial community transmissions of MERS and (ii) when the cases are at high risk of MERS (e.g. cases with close contact in hospital or household). It is vital to collect the information of the incubation period upon emergence of a novel infectious disease, and moreover, in our model, the fundamental transmission dynamics including the initial growth rate has to be explored to differentiate the disease diagnoses with non-specific symptoms. Elsevier Ltd. 2014-04-07 2014-01-06 /pmc/articles/PMC7094128/ /pubmed/24406808 http://dx.doi.org/10.1016/j.jtbi.2013.12.024 Text en Copyright © 2014 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Ejima, Keisuke Aihara, Kazuyuki Nishiura, Hiroshi Probabilistic differential diagnosis of Middle East respiratory syndrome (MERS) using the time from immigration to illness onset among imported cases |
title | Probabilistic differential diagnosis of Middle East respiratory syndrome (MERS) using the time from immigration to illness onset among imported cases |
title_full | Probabilistic differential diagnosis of Middle East respiratory syndrome (MERS) using the time from immigration to illness onset among imported cases |
title_fullStr | Probabilistic differential diagnosis of Middle East respiratory syndrome (MERS) using the time from immigration to illness onset among imported cases |
title_full_unstemmed | Probabilistic differential diagnosis of Middle East respiratory syndrome (MERS) using the time from immigration to illness onset among imported cases |
title_short | Probabilistic differential diagnosis of Middle East respiratory syndrome (MERS) using the time from immigration to illness onset among imported cases |
title_sort | probabilistic differential diagnosis of middle east respiratory syndrome (mers) using the time from immigration to illness onset among imported cases |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7094128/ https://www.ncbi.nlm.nih.gov/pubmed/24406808 http://dx.doi.org/10.1016/j.jtbi.2013.12.024 |
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