Karla Köpke1, Kerstin Prahm1, Silke Buda1, Walter Haas2. 1. Fachgebiet für respiratorisch übertragbare Erkrankungen, Abteilung für Infektionsepidemiologie, Robert Koch-Institut, Seestraße 10, 13353, Berlin, Deutschland. 2. Fachgebiet für respiratorisch übertragbare Erkrankungen, Abteilung für Infektionsepidemiologie, Robert Koch-Institut, Seestraße 10, 13353, Berlin, Deutschland. haasw@rki.de.
Abstract
BACKGROUND: Every year epidemic waves of influenza and other acute respiratory infections (ARIs) cause a highly variable burden of disease in the population. Thus, assessment of the situation and adaptation of prevention strategies have to rely on real time syndromic surveillance. OBJECTIVE: We have established an ICD-10-based electronic system allowing rapid capture and transmission of information on ARI (SEEDARI), in Germany. Here we report the evaluation of this new system based on results of the syndromic and virologic surveillance carried out by the working group on influenza in Germany (AGI). METHODS: Consultations and ICD10-codes (J00-J22, J44.0 and B34.9) between week 16 in 2009, and week 15 in 2013, were used for comparison with AGI data. The time course and the correlation of weekly estimates of the incidence of medically attended ARI (MAARI) and ARI/100 consultations were analyzed for the different surveillance systems. RESULTS: The number of participating medical practices in SEEDARI almost doubled from 2009 (n = 65) to 2013 (n = 111). A total of almost 6.8 million consultations and 465,006 diagnosed ARIs were transmitted. The comparison of weekly estimated incidence of MAARI per 100,000 capita derived from SEEDARI and the results of the AGI showed high statistical correlation (Spearman correlation coefficient rs = 0,924; n = 209; p < 0,001). The proportion of diagnosed influenza (J09-J11) and the weekly positivity rate from virological surveillance during epidemic waves also showed high correlations. DISCUSSION: We conclude that SEEDARI represents a valid system for syndromic influenza surveillance. The case-based ICD-10 approach allows a detailed analysis of the actual situation and also seems suitable for population-based studies.
BACKGROUND: Every year epidemic waves of influenza and other acute respiratory infections (ARIs) cause a highly variable burden of disease in the population. Thus, assessment of the situation and adaptation of prevention strategies have to rely on real time syndromic surveillance. OBJECTIVE: We have established an ICD-10-based electronic system allowing rapid capture and transmission of information on ARI (SEEDARI), in Germany. Here we report the evaluation of this new system based on results of the syndromic and virologic surveillance carried out by the working group on influenza in Germany (AGI). METHODS: Consultations and ICD10-codes (J00-J22, J44.0 and B34.9) between week 16 in 2009, and week 15 in 2013, were used for comparison with AGI data. The time course and the correlation of weekly estimates of the incidence of medically attended ARI (MAARI) and ARI/100 consultations were analyzed for the different surveillance systems. RESULTS: The number of participating medical practices in SEEDARI almost doubled from 2009 (n = 65) to 2013 (n = 111). A total of almost 6.8 million consultations and 465,006 diagnosed ARIs were transmitted. The comparison of weekly estimated incidence of MAARI per 100,000 capita derived from SEEDARI and the results of the AGI showed high statistical correlation (Spearman correlation coefficient rs = 0,924; n = 209; p < 0,001). The proportion of diagnosed influenza (J09-J11) and the weekly positivity rate from virological surveillance during epidemic waves also showed high correlations. DISCUSSION: We conclude that SEEDARI represents a valid system for syndromic influenza surveillance. The case-based ICD-10 approach allows a detailed analysis of the actual situation and also seems suitable for population-based studies.
Entities:
Keywords:
Data collection; Electronic health record; Epidemiologic surveillance; ICD-10; Influenza
Authors: Norman Rose; Josephine Storch; Anna Mikolajetz; Thomas Lehmann; Konrad Reinhart; Mathias W Pletz; Christina Forstner; Horst Christian Vollmar; Antje Freytag; Carolin Fleischmann-Struzek Journal: Hum Vaccin Immunother Date: 2021-01-07 Impact factor: 3.452