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Nowcasting (Short-Term Forecasting) of COVID-19 Hospitalizations Using Syndromic Healthcare Data, Sweden, 2020

We report on local nowcasting (short-term forecasting) of coronavirus disease (COVID-19) hospitalizations based on syndromic (symptom) data recorded in regular healthcare routines in Östergötland County (population ≈465,000), Sweden, early in the pandemic, when broad laboratory testing was unavailab...

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Autores principales: Spreco, Armin, Jöud, Anna, Eriksson, Olle, Soltesz, Kristian, Källström, Reidar, Dahlström, Örjan, Eriksson, Henrik, Ekberg, Joakim, Jonson, Carl-Oscar, Fraenkel, Carl-Johan, Lundh, Torbjörn, Gerlee, Philip, Gustafsson, Fredrik, Timpka, Toomas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Centers for Disease Control and Prevention 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8888224/
https://www.ncbi.nlm.nih.gov/pubmed/35201737
http://dx.doi.org/10.3201/eid2803.210267
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author Spreco, Armin
Jöud, Anna
Eriksson, Olle
Soltesz, Kristian
Källström, Reidar
Dahlström, Örjan
Eriksson, Henrik
Ekberg, Joakim
Jonson, Carl-Oscar
Fraenkel, Carl-Johan
Lundh, Torbjörn
Gerlee, Philip
Gustafsson, Fredrik
Timpka, Toomas
author_facet Spreco, Armin
Jöud, Anna
Eriksson, Olle
Soltesz, Kristian
Källström, Reidar
Dahlström, Örjan
Eriksson, Henrik
Ekberg, Joakim
Jonson, Carl-Oscar
Fraenkel, Carl-Johan
Lundh, Torbjörn
Gerlee, Philip
Gustafsson, Fredrik
Timpka, Toomas
author_sort Spreco, Armin
collection PubMed
description We report on local nowcasting (short-term forecasting) of coronavirus disease (COVID-19) hospitalizations based on syndromic (symptom) data recorded in regular healthcare routines in Östergötland County (population ≈465,000), Sweden, early in the pandemic, when broad laboratory testing was unavailable. Daily nowcasts were supplied to the local healthcare management based on analyses of the time lag between telenursing calls with the chief complaints (cough by adult or fever by adult) and COVID-19 hospitalization. The complaint cough by adult showed satisfactory performance (Pearson correlation coefficient r>0.80; mean absolute percentage error <20%) in nowcasting the incidence of daily COVID-19 hospitalizations 14 days in advance until the incidence decreased to <1.5/100,000 population, whereas the corresponding performance for fever by adult was unsatisfactory. Our results support local nowcasting of hospitalizations on the basis of symptom data recorded in routine healthcare during the initial stage of a pandemic.
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spelling pubmed-88882242022-03-02 Nowcasting (Short-Term Forecasting) of COVID-19 Hospitalizations Using Syndromic Healthcare Data, Sweden, 2020 Spreco, Armin Jöud, Anna Eriksson, Olle Soltesz, Kristian Källström, Reidar Dahlström, Örjan Eriksson, Henrik Ekberg, Joakim Jonson, Carl-Oscar Fraenkel, Carl-Johan Lundh, Torbjörn Gerlee, Philip Gustafsson, Fredrik Timpka, Toomas Emerg Infect Dis Research We report on local nowcasting (short-term forecasting) of coronavirus disease (COVID-19) hospitalizations based on syndromic (symptom) data recorded in regular healthcare routines in Östergötland County (population ≈465,000), Sweden, early in the pandemic, when broad laboratory testing was unavailable. Daily nowcasts were supplied to the local healthcare management based on analyses of the time lag between telenursing calls with the chief complaints (cough by adult or fever by adult) and COVID-19 hospitalization. The complaint cough by adult showed satisfactory performance (Pearson correlation coefficient r>0.80; mean absolute percentage error <20%) in nowcasting the incidence of daily COVID-19 hospitalizations 14 days in advance until the incidence decreased to <1.5/100,000 population, whereas the corresponding performance for fever by adult was unsatisfactory. Our results support local nowcasting of hospitalizations on the basis of symptom data recorded in routine healthcare during the initial stage of a pandemic. Centers for Disease Control and Prevention 2022-03 /pmc/articles/PMC8888224/ /pubmed/35201737 http://dx.doi.org/10.3201/eid2803.210267 Text en https://creativecommons.org/licenses/by/4.0/Emerging Infectious Diseases is a publication of the U.S. Government. This publication is in the public domain and is therefore without copyright. All text from this work may be reprinted freely. Use of these materials should be properly cited.
spellingShingle Research
Spreco, Armin
Jöud, Anna
Eriksson, Olle
Soltesz, Kristian
Källström, Reidar
Dahlström, Örjan
Eriksson, Henrik
Ekberg, Joakim
Jonson, Carl-Oscar
Fraenkel, Carl-Johan
Lundh, Torbjörn
Gerlee, Philip
Gustafsson, Fredrik
Timpka, Toomas
Nowcasting (Short-Term Forecasting) of COVID-19 Hospitalizations Using Syndromic Healthcare Data, Sweden, 2020
title Nowcasting (Short-Term Forecasting) of COVID-19 Hospitalizations Using Syndromic Healthcare Data, Sweden, 2020
title_full Nowcasting (Short-Term Forecasting) of COVID-19 Hospitalizations Using Syndromic Healthcare Data, Sweden, 2020
title_fullStr Nowcasting (Short-Term Forecasting) of COVID-19 Hospitalizations Using Syndromic Healthcare Data, Sweden, 2020
title_full_unstemmed Nowcasting (Short-Term Forecasting) of COVID-19 Hospitalizations Using Syndromic Healthcare Data, Sweden, 2020
title_short Nowcasting (Short-Term Forecasting) of COVID-19 Hospitalizations Using Syndromic Healthcare Data, Sweden, 2020
title_sort nowcasting (short-term forecasting) of covid-19 hospitalizations using syndromic healthcare data, sweden, 2020
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8888224/
https://www.ncbi.nlm.nih.gov/pubmed/35201737
http://dx.doi.org/10.3201/eid2803.210267
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