COVID-19 cases presenting to the Emergency Department predict Qatar National COVID-19 trends and numbers

In this short communication, we summarized the analyses, models, and interpretations of the corporate department of emergency medicine's (CDEM) COVID-19 numbers and their relationship to predict the national COVID-19 trends and numbers in Qatar. Data included in this analysis were obtained betw...

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Autores principales: Pathan, Sameer A., Moinudheen, Jibin, Simon, Katie, Thomas, Stephen H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: HBKU Press 2021
Materias:
Letter to the Editor
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8542101/
https://www.ncbi.nlm.nih.gov/pubmed/34733709
http://dx.doi.org/10.5339/qmj.2021.56
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author Pathan, Sameer A.
Moinudheen, Jibin
Simon, Katie
Thomas, Stephen H.
author_facet Pathan, Sameer A.
Moinudheen, Jibin
Simon, Katie
Thomas, Stephen H.
author_sort Pathan, Sameer A.
collection PubMed
description In this short communication, we summarized the analyses, models, and interpretations of the corporate department of emergency medicine's (CDEM) COVID-19 numbers and their relationship to predict the national COVID-19 trends and numbers in Qatar. Data included in this analysis were obtained between March 1, 2020 and July 31, 2021. It included the number of COVID-19 cases that presented to four major EDs under the Hamad Medical Corporation CDEM umbrella and published data from the Qatar Ministry of public health (MoPH). On plotting weighted scatterplot smoothing (lowess) trend lines, there were striking similarities between CDEM and national COVID-19 n curves for overall trends and peaks. In conclusion, CDEM COVID-19 spike may be useful to predict national COVID-19 spike in 2–3 weeks.
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spelling pubmed-85421012021-11-02 COVID-19 cases presenting to the Emergency Department predict Qatar National COVID-19 trends and numbers Pathan, Sameer A. Moinudheen, Jibin Simon, Katie Thomas, Stephen H. Qatar Med J Letter to the Editor In this short communication, we summarized the analyses, models, and interpretations of the corporate department of emergency medicine's (CDEM) COVID-19 numbers and their relationship to predict the national COVID-19 trends and numbers in Qatar. Data included in this analysis were obtained between March 1, 2020 and July 31, 2021. It included the number of COVID-19 cases that presented to four major EDs under the Hamad Medical Corporation CDEM umbrella and published data from the Qatar Ministry of public health (MoPH). On plotting weighted scatterplot smoothing (lowess) trend lines, there were striking similarities between CDEM and national COVID-19 n curves for overall trends and peaks. In conclusion, CDEM COVID-19 spike may be useful to predict national COVID-19 spike in 2–3 weeks. HBKU Press 2021-10-21 /pmc/articles/PMC8542101/ /pubmed/34733709 http://dx.doi.org/10.5339/qmj.2021.56 Text en © 2021 Pathan, Moinudheen, Simon, Thomas, licensee HBKU Press. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution license CC BY 4.0, which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Letter to the Editor
Pathan, Sameer A.
Moinudheen, Jibin
Simon, Katie
Thomas, Stephen H.
COVID-19 cases presenting to the Emergency Department predict Qatar National COVID-19 trends and numbers
title COVID-19 cases presenting to the Emergency Department predict Qatar National COVID-19 trends and numbers
title_full COVID-19 cases presenting to the Emergency Department predict Qatar National COVID-19 trends and numbers
title_fullStr COVID-19 cases presenting to the Emergency Department predict Qatar National COVID-19 trends and numbers
title_full_unstemmed COVID-19 cases presenting to the Emergency Department predict Qatar National COVID-19 trends and numbers
title_short COVID-19 cases presenting to the Emergency Department predict Qatar National COVID-19 trends and numbers
title_sort covid-19 cases presenting to the emergency department predict qatar national covid-19 trends and numbers
topic Letter to the Editor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8542101/
https://www.ncbi.nlm.nih.gov/pubmed/34733709
http://dx.doi.org/10.5339/qmj.2021.56
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AT simonkatie covid19casespresentingtotheemergencydepartmentpredictqatarnationalcovid19trendsandnumbers
AT thomasstephenh covid19casespresentingtotheemergencydepartmentpredictqatarnationalcovid19trendsandnumbers

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