Use of proxy indicators for automated surveillance of severe acute respiratory infection, the Netherlands, 2017 to 2023: a proof-of-concept study

Swets, M.C.; Niessen, A.; Buddingh, E.P.; Vossen, A.C.T.M.; Veldkamp, K.E.; Veldhuijzen, I.K.; Boer, M.G. de; Groeneveld, G.H.

doi:doi:10.2807/1560-7917.ES.2024.29.27.2300657

Background: Effective pandemic preparedness requires robust severe acute respiratory infection (SARI) surveillance. However, identifying SARI patients based on symptoms is time-consuming. Using the number of reverse transcription (RT)-PCR tests or contact and droplet precaution labels as a proxy for SARI could accurately reflect the epidemiology of patients presenting with SARI. Aim: We aimed to compare the number of RT-PCR tests, contact and droplet precaution labels and SARI-related International Classification of Disease (ICD)-10 codes and evaluate their use as surveillance indicators. Methods: Patients from all age groups hospitalised at Leiden University Medical Center between 1 January 2017 up to and including 30 April 2023 were eligible for inclusion. We used a clinical data collection tool to extract data from electronic medical records. For each surveillance indicator, we plotted the absolute count for each week, the incidence proportion per week and the correlation...Show moreBackground: Effective pandemic preparedness requires robust severe acute respiratory infection (SARI) surveillance. However, identifying SARI patients based on symptoms is time-consuming. Using the number of reverse transcription (RT)-PCR tests or contact and droplet precaution labels as a proxy for SARI could accurately reflect the epidemiology of patients presenting with SARI. Aim: We aimed to compare the number of RT-PCR tests, contact and droplet precaution labels and SARI-related International Classification of Disease (ICD)-10 codes and evaluate their use as surveillance indicators. Methods: Patients from all age groups hospitalised at Leiden University Medical Center between 1 January 2017 up to and including 30 April 2023 were eligible for inclusion. We used a clinical data collection tool to extract data from electronic medical records. For each surveillance indicator, we plotted the absolute count for each week, the incidence proportion per week and the correlation between the three surveillance indicators. Results: We included 117,404 hospital admissions. The three surveillance indicators generally followed a similar pattern before and during the COVID-19 pandemic. The correlation was highest between contact and droplet precaution labels and ICD-10 diagnostic codes (Pearson correlation coefficient: 0.84). There was a strong increase in the number of RT-PCR tests after the start of the COVID-19 pandemic. Discussion: All three surveillance indicators have advantages and disadvantages. ICD-10 diagnostic codes are suitable but are subject to reporting delays. Contact and droplet precaution labels are a feasible option for automated SARI surveillance, since these reflect trends in SARI incidence and may be available real-time.
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Use of proxy indicators for automated surveillance of severe acute respiratory infection, the Netherlands, 2017 to 2023: a proof-of-concept study