ICD-10 based syndromic surveillance enables robust estimation of burden of severe COVID-19 requiring hospitalization and intensive care treatment

  1. Kristin Tolksdorf
  2. Walter Haas
  3. Ekkehard Schuler
  4. Lothar H. Wieler
  5. Julia Schilling
  6. Osamah Hamouda
  7. Michaela Diercke
  8. Silke Buda

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Abstract

Objective

The emergence of coronavirus disease 2019 (COVID-19) required countries to establish COVID-19 surveillance by adapting existing systems, such as mandatory notification and syndromic surveillance systems. We estimated age-specific COVID-19 hospitalization and intensive care unit (ICU) burden from existing severe acute respiratory infections (SARI) surveillance and compared the results to COVID-19 notification data.

Methods

Using data on SARI cases with ICD-10 diagnosis codes for COVID-19 (COVID-SARI) from the ICD-10 based SARI sentinel, we estimated age-specific incidences for COVID-SARI hospitalization and ICU for the first five COVID-19 waves in Germany and compared these to incidences from notification data on COVID-19 cases using relative change Δ r at the peak of each wave.

Findings

The COVID-SARI incidence from sentinel data matched the notified COVID-19 hospitalization incidence in the first wave with Δ r =6% but was higher during second to fourth wave (Δ r =20% to 39%). In the fifth wave, the COVID-SARI incidence was lower than the notified COVID-19 hospitalization incidence (Δ r =-39%). For all waves and all age groups, the ICU incidence estimated from COVID-SARI was more than twice the estimation from notification data.

Conclusion

The use of validated SARI sentinel data adds robust and important information for assessing the true disease burden of severe COVID-19. Mandatory notifications of COVID-19 for hospital and ICU admission may underestimate (work overload in local health authorities) or overestimate (hospital admission for other reasons than the laboratory-confirmed SARS-CoV-2 infection) disease burden. Syndromic ICD-10 based SARI surveillance enables sustainable cross-pathogen surveillance for seasonal epidemics and pandemic preparedness of respiratory viral diseases.

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    SciScore for 10.1101/2022.02.11.22269594: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Cell Line AuthenticationAuthentication: The system has been validated and was described in detail in 2017 (10).

    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:
    However, our findings are subject to some limitations. The estimation of regional catchment population with the given data is difficult, therefore larger regions based on federal states were used (19). Yet, regional estimations are a strength of notification data. For the years 2020 and 2021, we saw a notable decrease of patient admissions in the hospital sentinel. This effect was observed world-wide and was probably due to a combination of aspects such as the cancelling of elective operations and an increased hesitancy to use the health service in general and especially hospitals (38-45). As we had stable catchment population estimations in the preceding years, using a fixed catchment population derived from the median of previous years was justified. The number of COVID-19-cases detected in hospitals is dependent on testing, and is likely underestimated. However, routine screening upon admission in sentinel hospitals was in place since July 2020. Furthermore, cases with laboratory confirmed SARS-CoV-2 infection hospitalized due to symptoms other than severe acute respiratory infections are not reported within the SARI sentinel. Thus, the focus on COVID-19 cases with SARI is more robust and less biased by the testing strategy as seen in notification data, as pneumonia was known to be the main syndrome of severe COVID-19 since the first case reports from China (46). We also note that weekly estimation of age-specific rates can lack accuracy due to low case numbers, especially...

    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.

    Results from scite Reference Check: We found no unreliable references.

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  2. Version published to 10.1101/2022.02.11.22269594 on medRxiv