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

  1. Ermengol Coma Redon
  2. Nuria Mora
  3. Albert Prats-Uribe
  4. Francesc Fina Avilés
  5. Daniel Prieto-Alhambra
  6. Manuel Medina

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Abstract

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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  1. Version published to 10.1136/bmjopen-2020-039369
  2. ScreenIT

    SciScore for 10.1101/2020.04.09.20056259: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Our study has several limitations. We used ecological data and modelled it using data from previous seasons, therefore assuming a direct causal link between excess influenza cases and the COVID-19 pandemic. Although we lack confirmatory tests or antigenic data for the estimated excess influenza cases, our results agree with a recent study that tested all influenza samples in Los Angeles for SARS-CoV-2, finding 2.2-10.7% of the tested samples positive for the pathogen.[17] The observed excess influenza cases could have been due to a panic effect, in which the current coronavirus infodemic, a rapid spread of misinformation, has encouraged people to consult healthcare professionals more frequently and for milder symptoms than usual. However, our data showed that the number of influenza diagnoses dropped drastically and COVID-19 diagnoses increased after 15 March 2020. New COVID-19 guidelines were released on 15 March 2020 in Spain that recommended only testing hospital-admitted patients and healthcare staff and encouraging GPs to diagnose COVID-19 clinically without PCR confirmation.[14] At least some of the excess ILI cases were thus likely to have actually been COVID-19 cases. Our study also has strengths. The data used were good quality, as demonstrated in many previous publications,[18–24] were obtained directly from primary-care records, and have been validated against gold-standard sentinel systems. This existing database covers over 85% of the population of Catalonia, whi...

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

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  3. Version published to 10.1101/2020.04.09.20056259v1 on medRxiv