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