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Excess cases of influenza and the coronavirus epidemic in Catalonia: a time-series analysis of primary-care electronic medical records covering over 6 million people

OBJECTIVES: There is uncertainty about when the first cases of COVID-19 appeared in Spain. We aimed to determine whether influenza diagnoses masked early COVID-19 cases and estimate numbers of undetected COVID-19 cases. DESIGN: Time-series study of influenza and COVID-19 cases, 2010–2020. SETTING: P...

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Autores principales: Coma Redon, Ermengol, Mora, Nuria, Prats-Uribe, Albert, Fina Avilés, Francesc, Prieto-Alhambra, Daniel, Medina, Manuel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7431772/
https://www.ncbi.nlm.nih.gov/pubmed/32727740
http://dx.doi.org/10.1136/bmjopen-2020-039369
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author Coma Redon, Ermengol
Mora, Nuria
Prats-Uribe, Albert
Fina Avilés, Francesc
Prieto-Alhambra, Daniel
Medina, Manuel
author_facet Coma Redon, Ermengol
Mora, Nuria
Prats-Uribe, Albert
Fina Avilés, Francesc
Prieto-Alhambra, Daniel
Medina, Manuel
author_sort Coma Redon, Ermengol
collection PubMed
description OBJECTIVES: There is uncertainty about when the first cases of COVID-19 appeared in Spain. We aimed to determine whether influenza diagnoses masked early COVID-19 cases and estimate numbers of undetected COVID-19 cases. DESIGN: Time-series study of influenza and COVID-19 cases, 2010–2020. SETTING: Primary care, Catalonia, Spain. PARTICIPANTS: People registered in primary-care practices, covering >6 million people and >85% of the population. MAIN OUTCOME MEASURES: Weekly new cases of influenza and COVID-19 clinically diagnosed in primary care. ANALYSES: Daily counts of both cases were computed using the total cases recorded over the previous 7 days to avoid weekly effects. Epidemic curves were characterised for the 2010–2011 to 2019–2020 influenza seasons. Influenza seasons with a similar epidemic curve and peak case number as the 2019–2020 season were used to model expected case numbers with Auto Regressive Integrated Moving Average models, overall and stratified by age. Daily excess influenza cases were defined as the number of observed minus expected cases. RESULTS: Four influenza season curves (2011–2012, 2012–2013, 2013–2014 and 2016–2017) were used to estimate the number of expected cases of influenza in 2019–2020. Between 4 February 2020 and 20 March 2020, 8017 (95% CI: 1841 to 14 718) excess influenza cases were identified. This excess was highest in the 15–64 age group. CONCLUSIONS: COVID-19 cases may have been present in the Catalan population when the first imported case was reported on 25 February 2020. COVID-19 carriers may have been misclassified as influenza diagnoses in primary care, boosting community transmission before public health measures were taken. The use of clinical codes could misrepresent the true occurrence of the disease. Serological or PCR testing should be used to confirm these findings. In future, this surveillance of excess influenza could help detect new outbreaks of COVID-19 or other influenza-like pathogens, to initiate early public health responses.
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spelling pubmed-74317722020-08-20 Excess cases of influenza and the coronavirus epidemic in Catalonia: a time-series analysis of primary-care electronic medical records covering over 6 million people Coma Redon, Ermengol Mora, Nuria Prats-Uribe, Albert Fina Avilés, Francesc Prieto-Alhambra, Daniel Medina, Manuel BMJ Open Epidemiology OBJECTIVES: There is uncertainty about when the first cases of COVID-19 appeared in Spain. We aimed to determine whether influenza diagnoses masked early COVID-19 cases and estimate numbers of undetected COVID-19 cases. DESIGN: Time-series study of influenza and COVID-19 cases, 2010–2020. SETTING: Primary care, Catalonia, Spain. PARTICIPANTS: People registered in primary-care practices, covering >6 million people and >85% of the population. MAIN OUTCOME MEASURES: Weekly new cases of influenza and COVID-19 clinically diagnosed in primary care. ANALYSES: Daily counts of both cases were computed using the total cases recorded over the previous 7 days to avoid weekly effects. Epidemic curves were characterised for the 2010–2011 to 2019–2020 influenza seasons. Influenza seasons with a similar epidemic curve and peak case number as the 2019–2020 season were used to model expected case numbers with Auto Regressive Integrated Moving Average models, overall and stratified by age. Daily excess influenza cases were defined as the number of observed minus expected cases. RESULTS: Four influenza season curves (2011–2012, 2012–2013, 2013–2014 and 2016–2017) were used to estimate the number of expected cases of influenza in 2019–2020. Between 4 February 2020 and 20 March 2020, 8017 (95% CI: 1841 to 14 718) excess influenza cases were identified. This excess was highest in the 15–64 age group. CONCLUSIONS: COVID-19 cases may have been present in the Catalan population when the first imported case was reported on 25 February 2020. COVID-19 carriers may have been misclassified as influenza diagnoses in primary care, boosting community transmission before public health measures were taken. The use of clinical codes could misrepresent the true occurrence of the disease. Serological or PCR testing should be used to confirm these findings. In future, this surveillance of excess influenza could help detect new outbreaks of COVID-19 or other influenza-like pathogens, to initiate early public health responses. BMJ Publishing Group 2020-07-29 /pmc/articles/PMC7431772/ /pubmed/32727740 http://dx.doi.org/10.1136/bmjopen-2020-039369 Text en © Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY. Published by BMJ. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/.
spellingShingle Epidemiology
Coma Redon, Ermengol
Mora, Nuria
Prats-Uribe, Albert
Fina Avilés, Francesc
Prieto-Alhambra, Daniel
Medina, Manuel
Excess cases of influenza and the coronavirus epidemic in Catalonia: a time-series analysis of primary-care electronic medical records covering over 6 million people
title Excess cases of influenza and the coronavirus epidemic in Catalonia: a time-series analysis of primary-care electronic medical records covering over 6 million people
title_full Excess cases of influenza and the coronavirus epidemic in Catalonia: a time-series analysis of primary-care electronic medical records covering over 6 million people
title_fullStr Excess cases of influenza and the coronavirus epidemic in Catalonia: a time-series analysis of primary-care electronic medical records covering over 6 million people
title_full_unstemmed Excess cases of influenza and the coronavirus epidemic in Catalonia: a time-series analysis of primary-care electronic medical records covering over 6 million people
title_short Excess cases of influenza and the coronavirus epidemic in Catalonia: a time-series analysis of primary-care electronic medical records covering over 6 million people
title_sort excess cases of influenza and the coronavirus epidemic in catalonia: a time-series analysis of primary-care electronic medical records covering over 6 million people
topic Epidemiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7431772/
https://www.ncbi.nlm.nih.gov/pubmed/32727740
http://dx.doi.org/10.1136/bmjopen-2020-039369
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