Divergences on expected pneumonia cases during the COVID-19 epidemic in Catalonia: a time-series analysis of primary care electronic health records covering about 6 million people

  1. Ermengol Coma
  2. Leonardo Méndez-Boo
  3. Núria Mora
  4. Carolina Guiriguet
  5. Mència Benítez
  6. Francesc Fina
  7. Mireia Fàbregas
  8. Elisabet Balló
  9. Francisa Ramos
  10. Manuel Medina
  11. Josep M. Argimon

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Abstract

Background

Pneumonia is one of the complications of COVID-19. Primary care electronic health records (EHR) have shown the utility as a surveillance system. We therefore analyse the trends of pneumonia during two waves of COVID-19 pandemic in order to use it as a clinical surveillance system and an early indicator of severity.

Methods

Time series analysis of pneumonia cases, from January 2014 to December 2020. We collected pneumonia diagnoses from primary care EHR, a software system covering > 6 million people in Catalonia (Spain). We compared the trend of pneumonia in the season 2019–2020 with that in the previous years. We estimated the expected pneumonia cases with data from 2014 to 2018 using a time series regression adjusted by seasonality and influenza epidemics.

Results

Between 4 March and 5 May 2020, 11,704 excess pneumonia cases (95% CI: 9909 to 13,498) were identified. Previously, we identified an excess from January to March 2020 in the population older than 15 years of 20%. We observed another excess pneumonia period from 22 october to 15 november of 1377 excess cases (95% CI: 665 to 2089). In contrast, we observed two great periods with reductions of pneumonia cases in children, accounting for 131 days and 3534 less pneumonia cases (95% CI, 1005 to 6064) from March to July; and 54 days and 1960 less pneumonia cases (95% CI 917 to 3002) from October to December.

Conclusions

Diagnoses of pneumonia from the EHR could be used as an early and low cost surveillance system to monitor the spread of COVID-19.

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  1. Version published to 10.1186/s12879-021-05985-0
  2. ScreenIT

    SciScore for 10.1101/2020.12.31.20249076: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: All data and analytical code are provided at https://github.com/ErmengolComa/pneumonia.git Ethical statement: This study was done in accordance with existing statutory and ethical approvals from the Clinical Research Ethics Committee of the IDIAPJGol (project code: 20/172-PCV).
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.

    Results from OddPub: Thank you for sharing your code and data.

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Our research has several limitations. Firstly, the design of our study does not allow us to ensure a causal link between COVID-19 epidemic and the excess of pneumonia, but only a temporal coincidence. Moreover, as we lacked tests we were not able to differentiate the etiology of each pneumonia. However, our method offers a low-cost surveillance system that could help to detect unusual trends, supporting public health responses. Secondly, as our study uses data from several years, changes in population structure could limit the use of this method. Nonetheless, population structure in terms of age and gender has remained stable in the study period [23]. Thirdly, using data from the primary care EHR could introduce some bias as we lacked information about emergency departments or hospital admission. The strengths of this study include population-based data automatically obtained from primary care EHR. Several studies have used the Catalan EHR to do useful research in real-world conditions and for the surveillance of different diseases [9, 24]. Our database covers over 75% of the population of Catalonia, allowing us to detect general and local excesses and lack of pneumonia. It’s also a quick and low cost method to integrate in the current information systems of any region using EHR. In addition, we have tested our method in a non-COVID-19 affected season (2018-2019) and we didn’t find any unusual pattern, strengthening our subsequent findings. Finally, this study presents for th...

    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.

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  3. Version published to 10.1101/2020.12.31.20249076v1 on medRxiv