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Based on our national outpatient sentinel surveillance, we have developed a novel approach to determine respiratory syncytial virus (RSV) epidemic seasons in Germany by using RSV positivity rate and its lower limit of 95% confidence interval. This method was evaluated retrospectively on nine RSV seasons, and it is also well-suited to describe off-season circulation of RSV in near real time as observed for seasons 2020/21 and 2021/22 during the COVID-19 pandemic. Prospective application is of crucial importance to enable timely actions for health service delivery and prevention.

Background: In 2021–22, influenza A viruses dominated in Europe. The I-MOVE primary care network conducted a multicentre test-negative study to measure influenza vaccine effectiveness (VE). Methods: Primary care practitioners collected information on patients presenting with acute respiratory infection. Cases were influenza A(H3N2) or A(H1N1)pdm09 RT-PCR positive and controls were influenza virus negative. We calculated VE using logistic regression, adjusting for study site, age, sex, onset date, and presence of chronic conditions. Results: Between week 40 2021 and week 20 2022, we included over 11,000 patients of whom 253 and 1595 were positive for influenza A(H1N1)pdm09 and A(H3N2), respectively. Overall VE against influenza A(H1N1)pdm09 was 75% (95%CI: 43–89) and 81% (95%CI: 44–93) among those aged 15–64 years. Overall VE against influenza A(H3N2) was 29% (95%CI: 12–42) and 25% (95%CI: -41–61), 33% (95%CI: 14–49) and 26% (95% CI: -22 to 55) among those aged 0–14, 15–64 and over 65 years, respectively. The A(H3N2) VE among the influenza vaccination target group was 20% (95%CI: -6–39). All 53 sequenced A(H1N1)pdm09 viruses belonged to clade 6B.1A.5a.1. Among 410 sequenced influenza A(H3N2) viruses, all but 8 belonged to clade 3C.2a1b.2a.2. Discussion: Despite antigenic mismatch between vaccine and circulating strains for influenza A(H3N2) and A(H1N1)pdm09, 2021–22 VE estimates against circulating influenza A(H1N1)pdm09 were the highest within the I-MOVE network since the 2009 influenza pandemic. VE against A(H3N2) was lower than A(H1N1)pdm09, but at least one in five individuals vaccinated against influenza were protected against presentation to primary care with laboratory-confirmed influenza.

Background The COVID-19 pandemic expanded the need for timely information on acute respiratory illness at population level. Aim We explored the potential of routine emergency department data for syndromic surveillance of acute respiratory illness in Germany. Methods We used routine attendance data from emergency departments, which continuously transferred data between week 10 2017 and 10 2021, with ICD-10 codes available for > 75% of attendances. Case definitions for acute respiratory infection (ARI), severe acute respiratory infection (SARI), influenza-like illness (ILI), respiratory syncytial virus infection (RSV) and COVID-19 were based on a combination of ICD-10 codes, and/or chief complaints, sometimes combined with information on hospitalisation and age. Results We included 1,372,958 attendances from eight emergency departments. The number of attendances dropped in March 2020 during the first COVID-19 pandemic wave, increased during summer, and declined again during the resurge of COVID-19 cases in autumn and winter of 2020/21. A pattern of seasonality of respiratory infections could be observed. By using different case definitions (i.e. for ARI, SARI, ILI, RSV) both the annual influenza seasons in the years 2017–2020 and the dynamics of the COVID-19 pandemic in 2020/21 were apparent. The absence of the 2020/21 influenza season was visible, parallel to the resurge of COVID-19 cases. SARI among ARI cases peaked in April–May 2020 (17%) and November 2020–January 2021 (14%). Conclusion Syndromic surveillance using routine emergency department data can potentially be used to monitor the trends, timing, duration, magnitude and severity of illness caused by respiratory viruses, including both influenza viruses and SARS-CoV-2.

ZusammenfassungIm Rahmen der nationalen Influenzapandemieplanung wurden in Deutschland neben dem Meldewesen gemäß Infektionsschutzgesetz (IfSG) weitere Überwachungssysteme etabliert. Ziel dieser Systeme sind die Beschreibung, Analyse und Bewertung der Situation bei akuten respiratorischen Erkrankungen (ARE), die Identifikation der hauptsächlich zirkulierenden Atemwegserreger und die Beschreibung des zeitlichen Verlaufs. Seit Beginn der COVID-19-Pandemie wurden die Systeme erweitert, um auch Infektionen mit SARS-CoV‑2 erfassen zu können.In diesem Beitrag werden drei verschiedene Surveillance-Systeme für ARE vorgestellt: GrippeWeb, die Arbeitsgemeinschaft Influenza mit dem SEEDARE-Modul (Sentinel zur elektronischen Erfassung von Diagnosecodes) und das Krankenhaus-Sentinel ICOSARI (ICD-10-code-basierte Krankenhaus-Surveillance schwerer akuter respiratorischer Infektionen). Mit diesen Systemen können ARE auf Bevölkerungsebene, im ambulanten und im stationären Bereich überwacht werden. Zusammen mit dem Monitoring der Mortalität liefern sie wichtige Hinweise zur Häufigkeit verschieden schwerer Krankheitsverläufe in der Bevölkerung. Um die Systeme für SARS-CoV‑2 zu erweitern, waren nur wenige Anpassungen notwendig.Da die Falldefinitionen für ARE nicht geändert wurden, können in den beschriebenen Systemen historische Zeitreihen zum Vergleich herangezogen werden. Alle Systeme sind so aufgebaut, dass stabile und etablierte Bezugsgrößen für die Berechnung von wöchentlichen Anteilen und Raten zur Verfügung stehen. Dies ist eine wichtige Ergänzung zum Meldewesen gemäß IfSG, welches stark von Testkapazitäten und -strategien sowie veränderten Falldefinitionen abhängt. Die Surveillance-Systeme haben sich in der COVID-19-Pandemie auch im internationalen Vergleich als praktikabel und effizient erwiesen.

German national surveillance data analysis shows that hospitalisation odds associated with Omicron lineage BA.1 or BA.2 infections are up to 80% lower than with Delta infection, primarily in ≥ 35-year-olds. Hospitalised vaccinated Omicron cases’ proportions (2.3% for both lineages) seemed lower than those of the unvaccinated (4.4% for both lineages). Independent of vaccination status, the hospitalisation frequency among cases with Delta seemed nearly threefold higher (8.3%) than with Omicron (3.0% for both lineages), suggesting that Omicron inherently causes less severe disease.

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

BackgroundThe Coronavirus disease 2019 (COVID-19) pandemic expanded the need for timely information on acute respiratory illness on the population level.AimWe explored the potential of routine emergency department data for syndromic surveillance of acute respiratory illness in Germany.MethodsWe included routine attendance data from emergency departments who continuously transferred data between week 10-2017 and 10-2021, with ICD-10 codes available for >75% of the attendances. Case definitions for acute respiratory illness (ARI), severe ARI (SARI), influenza-like illness (ILI), respiratory syncytial virus disease (RSV) and COVID-19 were based on a combination of ICD-10 codes, and/or chief complaints, sometimes combined with information on hospitalisation and age.ResultsWe included 1,372,958 attendances from eight emergency departments. The number of attendances dropped in March 2020, increased during summer, and declined again during the resurge of COVID-19 cases in autumn and winter of 2020/2021. A pattern of seasonality of acute respiratory infections could be observed. By using different case definitions (i.e. for ARI, SARI, ILI, RSV) both the annual influenza seasons in the years 2017-2020 and the dynamics of the COVID-19 pandemic in 2020-2021 were apparent. The absence of the 2020/2021 flu season was visible, parallel to the resurge of COVID-19 cases. The percentage SARI among ARI cases peaked in April-May 2020 (17%) and November 2020-January 2021 (14%).ConclusionSyndromic surveillance using routine emergency department data has the potential to monitor the trends, timing, duration, magnitude and severity of illness caused by respiratory viruses, including both influenza and SARS-CoV-2.

Background Influenza A(H1N1)pdm09 virus entered the human population in 2009 and evolved within this population for more than ten years. Despite genetic evolution no remarkable changes in the antigenic reactive pattern of these viruses were observed so far. Methods Primary respiratory samples of the German influenza virological sentinel were investigated by qPCR. Influenza virus-positive samples were characterized genetically and antigenetically. Results In December 2019, a antigenic drift variant characterized by an N156K substitution in the hemagglutinin of influenza A(H1N1)pdm09 virus emerged in Germany, which exhibited a reactivity to ferret antiserum that was an average 6 log2 lower than the vaccine virus A/Brisbane/02/2018 and the other A(H1N1)pdm09 viruses circulating in the influenza season 2019-2020. These viruses accounted for 20% of all A(H1N1)pdm09 viruses characterized in the German influenza sentinel. Patients infected with these viruses had a shorter median time period of medical consultation after onset of symptoms and were more frequently treated with neuraminidase inhibitors in comparison to patients infected with other A(H1N1)pdm09 viruses. Conclusions This parallel circulation of two antigenic variants of A(H1N1)pdm09 viruses which differ remarkably in their antigenic reactive pattern contributes to a greater variability in circulating influenza viruses and challenges vaccination.

Background During the initial COVID-19 response, Germany's Federal Government implemented several nonpharmaceutical interventions (NPIs) that were instrumental in suppressing early exponential spread of SARS-CoV-2. NPI effect on the transmission of other respiratory viruses has not been examined at the national level thus far. Methods Upper respiratory tract specimens from 3580 patients with acute respiratory infection (ARI), collected within the nationwide German ARI Sentinel, underwent RT-PCR diagnostics for multiple respiratory viruses. The observation period (weeks 1-38 of 2020) included the time before, during and after a far-reaching contact ban. Detection rates for different viruses were compared to 2017-2019 sentinel data (15350 samples; week 1-38, 11823 samples). Findings The March 2020 contact ban, which was followed by a mask mandate, was associated with an unprecedented and sustained decline of multiple respiratory viruses. Among these, rhinovirus was the single agent that resurged to levels equalling those of previous years. Rhinovirus rebound was first observed in children, after schools and daycares had reopened. By contrast, other nonenveloped viruses (i.e. gastroenteritis viruses reported at the national level) suppressed after the shutdown did not rebound. Interpretation Contact restrictions with a subsequent mask mandate in spring may substantially reduce respiratory virus circulation. This reduction appears sustained for most viruses, indicating that the activity of influenza and other respiratory viruses during the subsequent winter season might be low,whereas rhinovirus resurgence, potentially driven by transmission in educational institutions in a setting of waning population immunity, might signal predominance of rhinovirus-related ARIs. Funding Robert Koch-Institute and German Ministry of Health.

Background Internet‐based participatory surveillance systems, such as the German GrippeWeb, monitor the frequency of acute respiratory illnesses on population level. In order to interpret syndromic information better, we devised a microbiological feasibility study (GrippeWeb‐Plus) to test whether self‐collection of anterior nasal swabs is operationally possible, acceptable for participants and can yield valid data. Methods We recruited 103 GrippeWeb participants (73 adults and 30 children) and provided them with a kit, instructions and a questionnaire for each sample. In the first half of 2016, participants took an anterior nasal swab and sent it to the Robert Koch Institute whenever an acute respiratory illness occurred. Reporting of illnesses through the GrippeWeb platform continued as usual. We analysed swabs for the presence of human c‐myc‐DNA and 22 viral and bacterial pathogens. After the study, we sent participants an evaluation questionnaire. We analysed timeliness, completeness, acceptability and validity. Results One hundred and two participants submitted 225 analysable swabs. Ninety per cent of swabs were taken within 3 days of symptom onset. Eighty‐nine per cent of swabs had a corresponding reported illness in the GrippeWeb system. Ninety‐nine per cent of adults and 96% of children would be willing to participate in a self‐swabbing scheme for a longer period. All swabs contained c‐myc‐DNA. In 119 swabs, we identified any of 14 viruses but no bacteria. The positivity rate of influenza was similar to that in the German physician sentinel. Conclusion Self‐collection of anterior nasal swabs proofed to be feasible, was well accepted by participants, gave valid results and was an informative adjunct to syndromic data.

Im Rahmen der nationalen Influenzapandemieplanung wurden in Deutschland neben dem Meldewesen gemäß Infektionsschutzgesetz (IfSG) weitere Überwachungssysteme etabliert. Ziel dieser Systeme sind die Beschreibung, Analyse und Bewertung der Situation bei akuten respiratorischen Erkrankungen (ARE), die Identifikation der hauptsächlich zirkulierenden Atemwegserreger und die Beschreibung des zeitlichen Verlaufs. Seit Beginn der COVID-19-Pandemie wurden die Systeme erweitert, um auch Infektionen mit SARS-CoV‑2 erfassen zu können. In diesem Beitrag werden drei verschiedene Surveillance-Systeme für ARE vorgestellt: GrippeWeb, die Arbeitsgemeinschaft Influenza mit dem SEEDARE-Modul (Sentinel zur elektronischen Erfassung von Diagnosecodes) und das Krankenhaus-Sentinel ICOSARI (ICD-10-code-basierte Krankenhaus-Surveillance schwerer akuter respiratorischer Infektionen). Mit diesen Systemen können ARE auf Bevölkerungsebene, im ambulanten und im stationären Bereich überwacht werden. Zusammen mit dem Monitoring der Mortalität liefern sie wichtige Hinweise zur Häufigkeit verschieden schwerer Krankheitsverläufe in der Bevölkerung. Um die Systeme für SARS-CoV‑2 zu erweitern, waren nur wenige Anpassungen notwendig. Da die Falldefinitionen für ARE nicht geändert wurden, können in den beschriebenen Systemen historische Zeitreihen zum Vergleich herangezogen werden. Alle Systeme sind so aufgebaut, dass stabile und etablierte Bezugsgrößen für die Berechnung von wöchentlichen Anteilen und Raten zur Verfügung stehen. Dies ist eine wichtige Ergänzung zum Meldewesen gemäß IfSG, welches stark von Testkapazitäten und -strategien sowie veränderten Falldefinitionen abhängt. Die Surveillance-Systeme haben sich in der COVID-19-Pandemie auch im internationalen Vergleich als praktikabel und effizient erwiesen.

A zoonotic A/sw/H1avN1 1C.2.2 influenza virus infection was detected in a German child that presented with influenza-like illness, including high fever. There was a history of close contact with pigs 3 days before symptom onset. The child recovered within 3 days. No other transmissions were observed. Serological investigations of the virus isolate revealed cross-reactions with ferret antisera against influenza A(H1N1)pdm09 virus, indicating a closer antigenic relationship with A(H1N1)pdm09 than with the former seasonal H1N1 viruses.

As of December 31, 2019, initial reports circulated internationally of an unusual cluster of pneumonia of unknown cause in China. By the end of January 2020, the virus affected Germany with the first case confirmed on January 27, 2020. Intensive contact tracing and infection control measures contained the first two clusters in the country. However, the dynamic of the first wave gained momentum as of March, and by mid-June 2020 over 190,000 laboratory-confirmed cases had been reported to the Robert Koch Institute. This article examines these cases as part of a retrospective descriptive analysis focused on disease severity. Most cases (80%) were mild and two thirds of the cases were younger than 60 years (median age: 50 years). Severe cases were primarily reported among men aged 60 or over who had at least one risk factor (particularly cardiovascular disease, diabetes, neurological disorders and/or lung diseases). Cases between the ages of 40 and 59 years had the longest interval between symptom onset and hospitalisation (median: six days) and - if admitted to an intensive care unit (ICU) - also the longest ICU stay (median: eleven days). This analysis provides valuable information about disease severity of COVID-19 and particularly affected groups.

Mitigation of the coronavirus disease (COVID-19) pandemic in Germany included school closures in early March 2020. After reopening in April, preventive measures were taken in schools. We analysed national surveillance system data on COVID-19 school outbreaks during different time periods. After reopening, smaller outbreaks (average: 2.2/week) occurred despite low incidence in the general population. School closures might have a detrimental effect on children and should be applied only cautiously and in combination with other measures.

Information on severity of coronavirus disease (COVID-19) (transmissibility, disease seriousness, impact) is crucial for preparation of healthcare sectors. We present a simple approach to assess disease seriousness, creating a reference cohort of pneumonia patients from sentinel hospitals. First comparisons exposed a higher rate of COVID-19 patients requiring ventilation. There were more case fatalities among COVID-19 patients without comorbidities than in the reference cohort. Hospitals should prepare for high utilisation of ventilation and intensive care resources.

In the WHO European Region, COVID-19 surveillance was implemented 27 January 2020. We detail the first European cases. As at 21 February, nine European countries reported 47 cases. Among 38 cases studied, 21 were linked to two clusters in Germany and France, 14 were infected in China. Median case age was 42 years; 25 were male. Late detection of the clusters' index cases delayed isolation of further local cases. As at 5 March, there were 4,250 cases., info:eu-repo/semantics/published

Introduction Respiratory syncytial virus (RSV) is a major cause of hospital admission for acute lower respiratory tract infection in young children. Objectives We aimed to identify risk factors for hospitalized RSV disease and its severe outcomes. Methods We conducted a retrospective cohort study analyzing data of a ICD‐10‐code‐based hospital surveillance for severe acute respiratory infections (SARI). Using univariable and multivariable logistic regression analysis, we assessed age‐group, gender, season, and underlying medical conditions as possible risk factors for RSV and its severe outcomes including ICU admission, application of ventilator support, and death, respectively. Results Of the 413 552 patients hospitalized with SARI in the database, 8761 were diagnosed with RSV from week 01/2009 to 20/2018 with 97% (8521) aged

Die Revision der Internationalen statistischen Klassifikation der Krankheiten und verwandter Gesundheitsprobleme (International Classification of Diseases – ICD) geht mit grundlegenden Anderungen der Morbiditats- und Mortalitatsstatistik einher, die auch den Bereich der Infektionskrankheiten betreffen. Die Zuordnung der einzelnen Infektionskrankheiten zu den Kapiteln in der aktuellen ICD-10 erfolgt aufgrund unterschiedlicher Konzepte, teilweise nach auslosendem Agens, nach betroffenem Organsystem oder nach Lebensperiode. Besondere Herausforderungen der Klassifizierung der Infektionskrankheiten bestehen u. a. darin, dass regelmasig ein Anpassungsbedarf durch neu auftretende Erreger entstehen kann. Auserdem reichen die Angaben hinsichtlich Umfang und Tiefe in der ICD-10 teilweise nicht aus, um epidemiologische Auswertungen der Daten durchzufuhren. Die ICD ermoglicht den weltweiten Vergleich von Statistiken zu Infektionskrankheiten. Zunehmend wird die ICD jedoch auch fur die Erhebung von Surveillance- und Forschungsdaten eingesetzt, z. B. im Rahmen des Meldewesens (Identifizierung von Meldetatbestanden), aber auch in der syndromischen Surveillance akuter Atemwegsinfektionen und fur den Aufbau neuer Surveillance-Systeme sowie der Evaluation der Datenqualitat durch Abgleich mit Sekundardaten. Die Chancen der ICD-11 liegen vor allem darin, dass Infektionskrankheiten eindeutiger codiert werden konnen und ihre Codierung mehr relevante Informationen fur die epidemiologische Bewertung enthalt. Durch die hohe Komplexitat konnen jedoch Verzerrungen in den Daten entstehen, die die Fortschreibung der Morbiditats- und Mortalitatsstatistiken erschweren.

Background The burden of influenza in primary care is difficult to assess, since most patients with symptoms of a respiratory infection are not tested. The case definition of “medically attended acute respiratory infection” (MAARI) in the German physician sentinel is sensitive; however, it requires modelling techniques to derive estimates of disease attributable to influenza and respiratory syncytial virus (RSV). Objectives The objective of this paper was to review and extend our previously published model in order to estimate the burden of RSV and the differential burden of the two influenza B lineages (Victoria, Yamagata) as well as both influenza A subtypes on primary care visits. Methods Data on MAARI and virological results of respiratory samples (virological sentinel) were available from 2010/11 until 2017/18. We updated the previously published generalized additive regression model to include RSV. Results We found that the proportion of MAARI due to RSV is substantial only in the 0‐1‐ and 2‐4‐year‐old age groups (0‐1 years old: median 7.5%, range 4.0%‐14.8%; 2‐4 years old: median 6.5%, range 4.0%‐10.3%); in the 0‐1 years old age group, RSV leads in almost all seasons to a higher burden than any influenza type or subtype, but this is reversed in the age group 2‐4 years old. Conclusions We succeeded in rearranging our previously published model on MAARI to incorporate RSV as well as the two influenza B lineages (Victoria, Yamagata) in the time period 2010 to 2018.

Influenza und andere akute respiratorische Erkrankungen (ARE) treten jahrlich mit einer stark variablen Krankheitslast in epidemischen Wellen in der Bevolkerung auf. Dies erfordert eine zeitnahe syndromische Surveillance zur Beurteilung der Situation und Anpassung von Praventionsmasnahmen. Wir haben ein ICD-10-basiertes elektronisches System zur zeitnahen Erfassung und Ubermittlung von ARE in Deutschland in Sentinelpraxen etabliert (SEEDARE). In der vorliegenden Arbeit evaluieren wir dieses neue System anhand von Ergebnissen der syndromischen und virologischen Surveillance der Arbeitsgemeinschaft Influenza (AGI). Praxiskontakte und ubermittelte ICD-10-Diagnosecodes (J00–J22, J44.0 und B34.9) zwischen der 16. Kalenderwoche (KW) 2009 und der 15. KW 2013 wurden fur den Vergleich mit den Daten der AGI genutzt. Hierzu wurden der zeitliche Verlauf, die Korrelation der wochentlich geschatzten Konsultationsinzidenz und die Anzahl ARE/100-Praxiskontakte aus den verschiedenen Systemen untersucht. Die Anzahl der teilnehmenden Arztpraxen an SEEDARE konnte von 2009 (n = 65) bis 2013 (n = 111) fast verdoppelt werden. Insgesamt wurden fast 6,8 Mio. Praxiskontakte und 465.006 ARE ubermittelt. Der Vergleich der wochentlich geschatzten Konsultationsinzidenzen zeigte eine hohe statistische Korrelation (Spearman-Korrelationskoeffizient rs = 0,924; n = 209; p < 0,001). Die Anteile von Influenzapatienten (J09–J11) und der wochentlichen Positivenraten der virologischen Surveillance wahrend der Influenzawellen waren ebenfalls hoch korreliert. Das SEEDARE-System stellt damit ein valides Instrument zur syndromischen Influenzasurveillance dar. Der fallbasierte Ansatz mittels ICD-10 erlaubt eine detaillierte Analyse der aktuellen Situation, der sich auch fur populationsbasierte Studien eignet.

Schatzungen der Anzahl der Verstorbenen infolge der Influenzapandemien des 20. und 21. Jahrhunderts (1918/1919, 1957/1958, 1968–1970 und 2009) sind weltweit und auch fur Deutschland eine Herausforderung. Die aufgrund einer systematischen Literaturrecherche erhobenen Ergebnisse sollen zusammengetragen, durch eigene Berechnungen erganzt und bewertet werden. Es wurde eine systematische Literaturrecherche unter Verwendung u. a. der Begriffe death, mortality, pandemic, epidemic, Germany, 1918, 1957, 1968, 2009 durchgefuhrt. Treffer wurden nach Titel bzw. Zusammenfassung gesichtet und bezuglich moglicher Relevanz selektiert. Eigene Schatzungen wurden, basierend auf Exzess-Mortalitats-Berechnungen, durchgefuhrt. Die verschiedenen Werte aus der Literatur und den gegebenenfalls eigenen Berechnungen wurden bezuglich Methodik und Qualitat der Datengrundlage bewertet, um den jeweils vertrauenswurdigsten zu identifizieren. Aus den Todesfallzahlen wurde fur jede Pandemie eine Letalitat berechnet und mit globalen Werten der Weltgesundheitsorganisation (WHO) verglichen. Fur die Pandemie 1918/1919 identifizierten wir 5, fur die Pandemien 1957/1958 und/oder 1968–1970 3 und fur die Pandemie 2009 ebenfalls 3 relevante Publikationen. Fur alle 4 Pandemien waren die plausibelsten Schatzungen diejenigen, welche mittels einer Zeitreihenanalyse (aus der Literatur entnommen oder aufgrund eigener Schatzungen) monatlicher oder wochentlicher Gesamttodesfallstatistiken ermittelt wurden. Diese waren fur die 4 Pandemien in chronologischer Reihenfolge 426.600 (1918/1919), 29.100 (1957/1958), 46.900 (1968–1970) bzw. 350 (2009) und entsprachen einer bevolkerungsbezogenen Exzess-Mortalitat zwischen 691/100.000 (0,69 %) infolge der Pandemie 1918/1919 und 0,43/100.000 (0,00043 %) fur 2009. Die resultierenden Letalitaten stimmten gut mit globalen, von der WHO angegebenen Werten uberein. Fur die letzten 4 Pandemien (1918 bis 2009) konnten plausible Schatzungen der Exzess-Todesfallzahlen identifiziert werden. Die Heterogenitat der entsprechenden Exzess-Mortalitat zwischen den Pandemien ist bei einem Faktor von mehr als 1000 enorm. Diese kann durch Eigenschaften des Virus oder des Wirts (Immunitat), die jeweiligen gesellschaftlichen Bedingungen, die Gesundheitsversorgung oder die medizinische Entwicklung bedingt sein.

Global human mobility and intercontinental connectivity, expansion of livestock production and encroachment of wildlife habitats by invasive agricultural land use contribute to shape the complexity of influenza epidemiology. The OneHealth approach integrates these and further elements into considerations to improve disease control and prevention. Food of animal origin for human consumption is another integral aspect; if produced from infected livestock such items may act as vehicles of spread of animal pathogens, and, in case of zoonotic agents, as a potential human health hazard. Notifiable zoonotic avian influenza viruses (AIV) have become entrenched in poultry populations in several Asian and northern African countries since 2003. Highly pathogenic (HP) AIV (e.g. H5N1) cause extensive poultry mortality and severe economic losses. HPAIV and low pathogenic AIV (e.g. H7N9) with zoonotic propensities pose risks for human health. More than 1500 human cases of AIV infection have been reported, mainly from regions with endemically infected poultry. Intense human exposure to AIV-infected poultry, e.g. during rearing, slaughtering or processing of poultry, is a major risk factor for acquiring AIV infection. In contrast, human infections through consumption of AIV-contaminated food have not been substantiated. Heating poultry products according to kitchen standards (core temperatures ≥70°C, ≥10 s) rapidly inactivates AIV infectivity and renders fully cooked products safe. Nevertheless, concerted efforts must ensure that poultry products potentially contaminated with zoonotic AIV do not reach the food chain. Stringent and sustained OneHealth measures are required to better control and eventually eradicate, HPAIV from endemic regions.

We used physician sentinel surveillance to identify 25 (7.7%) mild to severe infections with enterovirus D68 (EV-D68) in children and adults among 325 outpatients with acute respiratory infections in Germany during August-October 2014. Results suggested low-level circulation of enterovirus D68 in Germany. Viruses were characterized by sequencing viral protein (VP) 1 and VP4/VP2 genomic regions.

Background To reduce the burden of severe influenza, most industrialized countries target specific risk-groups with influenza vaccines, e.g. the elderly or individuals with comorbidities. Since children are the main spreaders, some countries have recently implemented childhood vaccination programs to reduce overall virus transmission and thereby influenza disease in the whole population. The introduction of childhood vaccination programs was often supported by modelling studies that predicted substantial incidence reductions. We developed a mathematical transmission model to examine the potential impact of childhood influenza vaccination in Germany, while also challenging established modelling assumptions. Methods We developed an age-stratified SEIR-type transmission model to reproduce the epidemic influenza seasons between 2003/04 and 2013/14. The model was built upon German population counts, contact patterns, and vaccination history and was fitted to seasonal data on influenza-attributable medically attended acute respiratory infections (I-MAARI) and strain distribution using Bayesian methods. As novelties we (i) implemented a stratified model structure enabling seasonal variability and (ii) deviated from the commonly assumed mass-action-principle by employing a phenomenological transmission rate. Results According to the model, by vaccinating primarily the elderly over ten seasons 4 million (95% prediction interval: 3.84 – 4.19) I-MAARI were prevented which corresponds to an 8.6% (8.3% – 8.9%) reduction compared to a no-vaccination scenario and a number-needed-to-vaccinate (NNV) to prevent one I-MAARI of 37.1 (35.5 – 38.7). Additional vaccination of 2-10 year-old children at 40% coverage would have led to an overall I-MAARI reduction of 17.8% (17.1 – 18.7%) mostly due to indirect effects with a NNV of 20.7 (19.6 – 21.6). When employing the traditional mass-action-principle, the model predicted a more than 3-fold higher I-MAARI reduction (55.6%) due to childhood vaccination. Conclusion In Germany, the introduction of routine childhood influenza vaccination could considerably reduce I-MAARI among all age-groups and improve the NNV. However, the predicted impact is much lower compared to previous studies, which is primarily caused by our phenomenological approach to modelling influenza virus transmission. Electronic supplementary material The online version of this article (doi:10.1186/s12879-017-2344-6) contains supplementary material, which is available to authorized users.

The publisher regrets that the co-authors in the “European region influenza surveillance network” were not tagged correctly. The full and complete list of authors and their affiliations for this article is given above. The publisher would like to apologise for any inconvenience caused.

Background The World Health Organization recommends early antiviral treatment for patients with severe influenza illness or those at increased risk for severe illness. Objectives The aim of this study was to determine the proportion of cases with laboratory-confirmed A(H1N1)pdm09 infection that have been treated with antivirals in Germany during the pandemic (H1N1) 2009 and to investigate factors associated with the use of antivirals. Methods We analyzed cases with laboratory-confirmed A(H1N1)pdm09 infection notified to national health authorities in Germany between week 29/2009 and week 17/2010 using multivariable logistic regression. Severity of disease was defined by pneumonia or death. Results and conclusions Of 160 804 cases with laboratory-confirmed A(H1N1)pdm09 infection, 22% were treated with antivirals. Cases with severe disease were more likely to be treated with antivirals than cases without severe disease (odds ratio = 1·66; 95% confidence interval: 1·46–1·89). In the group with at least one underlying medical condition, only children aged between 1 and 4 years had significant lower odds for receiving antiviral treatment compared with cases in the age group 15 to 49 years (odds ratio = 0·75; 95% confidence interval: 0·6–0·94). In conclusion, the implementation of international recommendations on use of antivirals differed according to the age of patients in Germany during the pandemic (H1N1) 2009. This indicates that the potential of antivirals to prevent severe influenza might not have been fully exhausted. The reasons leading to the observed differences in patient management need to be investigated.

Introduction of highly pathogenic avian influenza (HPAI) virus A(H5N8) into Europe prompted animal and human health experts to implement protective measures to prevent transmission to humans. We describe the situation in 2016 and list public health measures and recommendations in place. We summarise critical interfaces identified during the A(H5N1) and A(H5N8) outbreaks in 2014/15. Rapid exchange of information between the animal and human health sectors is critical for a timely, effective and efficient response.

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.We have established an ICD-10-based electronic system allowing rapid capture and transmission of information on ARI (SEEDConsultations 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.The number of participating medical practices in SEEDWe conclude that SEED

Background Syndromic surveillance of severe acute respiratory infections (SARI) is important to assess seriousness of disease as recommended by WHO for influenza. In 2015 the Robert Koch Institute (RKI) started to collaborate with a private hospital network to develop a SARI surveillance system using case-based data on ICD-10 codes. This first-time description of the system shows its application to the analysis of five influenza seasons. Methods Since week 40/2015, weekly updated anonymized data on discharged patients overall and on patients with respiratory illness including ICD-10 codes of primary and secondary diagnoses are transferred from the network data center to RKI. Retrospective datasets were also provided. Our descriptive analysis is based on data of 47 sentinel hospitals collected between weeks 1/2012 to 20/2016. We applied three different SARI case definitions (CD) based on ICD-10 codes for discharge diagnoses of respiratory tract infections (J09 - J22): basic CD (BCD), using only primary diagnoses; sensitive CD (SCD), using primary and secondary diagnoses; timely CD (TCD), using only primary diagnoses of patients hospitalized up to one week. We compared the CD with regard to severity, age distribution and timeliness and with results from the national primary care sentinel system. Results The 47 sentinel hospitals covered 3.6% of patients discharged from all German hospitals in 2013. The SCD comprised 2.2 times patients as the BCD, and 3.6 times as many as the TCD. Time course of SARI cases corresponded well to results from primary care surveillance and influenza virus circulation. The patients fulfilling the TCD had been completely reported after 3 weeks, which was fastest among the CD. The proportion of SARI cases among patients was highest in the youngest age group of below 5-year-olds. However, the age group 60 years and above contributed most SARI cases. This was irrespective of the CD used. Conclusions In general, available data and the implemented reporting system are appropriate to provide timely and reliable information on SARI in inpatients in Germany. Our ICD-10-based approach proved to be useful for fulfilling requirements for SARI surveillance. The exploratory approach gave valuable insights in data structure and emphasized the advantages of different CD.

Estimation of the number of deaths as a consequence of the influenza pandemics in the twentieth and twenty-first centuries (i.e. 1918-1919, 1957-1958, 1968-1970 and 2009) is a challenge worldwide and also in Germany. After conducting a systematic literature search complemented by our own calculations, values and estimates for all four pandemics were collated and evaluated.A systematic literature search including the terms death, mortality, pandemic, epidemic, Germany, 1918, 1957, 1968, 2009 was performed. Hits were reviewed by title and abstract and selected for possible relevance. We derived our own estimates using excess mortality calculations, which estimate the mortality exceeding that to be expected. All identified values were evaluated by methodology and quality of the database. Numbers of pandemic deaths were used to calculate case fatality rates and were compared with global values provided by the World Health Organization.For the pandemic 1918-1919 we identified 5 relevant publications, 3 for the pandemics 1957-1958 and 1968-1970 and 3 for 2009. For all four pandemics the most plausible estimations were based on time series analyses, taken either from the literature or from our own calculations based on monthly or weekly all cause death statistics. For the four pandemics these estimates were in chronological order 426,600 (1918-1919), 29,100 (1957-1958), 46,900 (1968-1970) and 350 (2009) excess pandemic-related deaths. This translates to an excess mortality ranging between 691 per 100,000 (0.69 % in 1918-1919) and 0.43 per 100,000 (0.00043 % in 2009). Case fatality rates showed good agreement with global estimates.We have proposed plausible estimates of pandemic-related excess number of deaths for the last four pandemics as well as excess mortality in Germany. The heterogeneity among pandemics is large with a variation factor of more than 1000. Possible explanations include characteristics of the virus or host (immunity), social conditions, status of the healthcare system and medical advances.

Improvement is needed in preventing severe disease and nosocomial transmission in children beyond pandemic situations., We conducted a nationwide hospital-based prospective study in Germany of influenza A(H1N1)pdm09 cases among children