Osamah Hamouda’s research while affiliated with Robert Koch Institut and other places

Background The first Corona Monitoring Nationwide (RKI-SOEP) study (October 2020−February 2021) found a low pre-vaccine SARS-CoV-2 antibody seroprevalence (2.1%) in the German adult population (≥ 18 years). Aim The objective of this second RKI-SOEP (RKI-SOEP-2) study in November 2021−March 2022 was to estimate the prevalence of SARS-CoV-2-specific anti-spike and/or anti-nucleocapsid (anti-N) IgG antibodies (combined seroprevalence), past infection based on infection-induced seroprevalence (anti-N), and basic immunisation (at least two antigen contacts through vaccination or infection) in individuals aged ≥ 14 years. We also aimed to estimate under-reporting of infections. Methods Dried blood-spot specimens from a population-based sample embedded in a dynamic cohort, the Socio-Economic Panel (SOEP), were serologically analysed. Resulting serological data and self-reports via a questionnaire from the same individuals were used to estimate prevalences. Results Combined seroprevalence was 90.7% (95% CI: 89.7%–91.6%) without correction and 94.6% (95% CI: 93.6%–95.7%) with correction for sensitivity/specificity and antibody waning. While one in nine individuals had been infected (11.3%; 95% CI: 9.1%–13.5%), nine in 10 had a basic immunisation (90%; 95% CI: 88.9–90.9%), primarily due to vaccination. Population-weighted estimates differed by age, region, and socioeconomic deprivation. The under-reporting factor was estimated as 1.55 (95% CI: 1.3–1.8). Conclusions When the SARS-CoV-2-Omicron wave was beginning, most people had been vaccinated, infected, or both. Large-scale vaccination, but not a high infection rate, was able to fill the immunity gap, especially in ≥ 65 year-olds who are known to be at higher risk of severe COVID-19. Our data point towards the need for targeted socioeconomically, demographically and regionally stratified mitigation strategies, including measures to enhance vaccine uptake.

Background: The first wave of the Corona Monitoring Nationwide (RKI-SOEP) Study drawn from the German Socio-Economic Panel proved a low pre-vaccine SARS-CoV-2 seroprevalence in the German adult population of 2.1%. Methods: In this second wave of the study (RKI-SOEP-2, November 2021-March 2022), we used combined serological and self-reported data on infection and vaccination to estimate the prevalence of SARS-CoV-2-specific anti-spike and/or anti-nucleocapsid IgG antibodies (combined seroprevalence), past infection, and basic immunization in individuals aged 14+. Findings: Combined seroprevalence was 90.7% (95% CI 89.7% - 91.6%) without correction for antibody waning and 94.6% (95% CI 93.6% - 95.7%) with correction. While 1 in 10 individuals had been infected (9.9%, 95% CI 9.0% - 10.9%), 9 in 10 had at least a basic immunization (90%, 95% CI 88.9%-90.9%). Population-weighted estimates differed by age, region, and socioeconomic deprivation. Infection-induced seroprevalence with correction for antibody waning was 1.55 (95% CI 1.3 - 1.8) times higher than the cumulative proportion based on national surveillance data. Interpretation: At the beginning of the SARS-CoV-2-Omicron wave, the vast majority of the population had been vaccinated, infected, or both. Our results show how large-scale vaccination, but not a high infection rate, was able to fill the immunity gap, especially in older individuals (aged 65+) who are known to be at higher risk of severe COVID-19. Our data point towards a targeted demographically and regionally stratified mitigation strategy, to optimize future pandemic mitigation efforts.

Objective With the emergence of coronavirus disease 2019 (COVID-19) countries had to establish COVID-19 surveillance by adapting existing systems, such as the mandatory notification system and syndromic surveillance systems. We estimated COVID-19 hospitalization and ICU burden from existing severe acute respiratory infections (SARI) surveillance and compared it to COVID-19 notification data. Methods Using data from the ICD-10 based hospital sentinel, we estimated SARI incidence and validated our estimations retrospectively using full population data. We estimated age-specific incidences for COVID-19 hospitalization and ICU for the first three COVID-19 waves in Germany, based on information of SARI cases (COVID-SARI). We compared these estimations to hospitalization and ICU burden of COVID-19 from notification data and described potential underreporting of hospitalizations in notification data. Findings The estimation of SARI incidence from sentinel data corresponded very well to full population data. The estimated COVID-SARI incidence matched the notified COVID-19 hospitalization incidence in the first wave, but was much higher during the second and the third wave. The proportion of unknown hospitalization status among notified COVID-19 cases was much higher in the later waves compared to the first wave. For all waves, the ICU incidence estimated from COVID-SARI was considerably higher than the results from notification data. Conclusion The use of SARI sentinel data adds valid and important information for assessing COVID-19 hospitalization and ICU burden, especially in times with high case numbers where notification data may be more incomplete.

Zusammenfassung Daten zu Severe Acute Respiratory Syndrome Coronavirus 2-(SARS-CoV-2-)bedingten Ausbrü- chen in Kindertageseinrichtungen (Kitas) können wichtige Hinweise zur Einschätzung des Infektions- geschehens im Kita-Setting liefern und sind ein wichtiger Bestandteil in der Gesamtbewertung des SARS-CoV-2-Infektionsgeschehens. Im vorliegen- den Beitrag untersuchten wir daher SARS-CoV-2- Ausbrüche in Kitas für den Zeitraum von Septem- ber 2020 bis Anfang Juni 2021 und vergleichen da- bei Daten aus zwei verschiedenen Systemen. Wir betrachteten zum einen die Meldedaten zu den ge- mäß Infektionsschutzgesetz (IfSG) an das Robert Koch-Institut (RKI) übermittelten Kita-Ausbrüchen und zum anderen das Infektionsgeschehen in Kitas, welches von etwa 14 % der bundesweit registrierten Einrichtungen an das Deutsche Jugendinstitut (DJI) in dem dort etablierten KiTa-Register berichtet wird. Während von den Gesundheitsämtern Kita-Ausbrü- che als solche an das RKI übermittelt werden kön- nen, melden die Einrichtungen an das KiTa-Register lediglich die Zahl an bestätigten SARS-CoV-2-Infek- tionsfällen unter Kita-Personal und Kita-Kindern pro Kalenderwoche (KW). Wir werteten daher min- destens zwei innerhalb von zwei KW über das KiTa- Register berichtete SARS-CoV-2-Infektionsfälle in einer Kita als „potenziellen“ Ausbruch. Die Gesamt- zahl der potenziellen Ausbrüche wurde unter Kennt- nis des Anteils an registrierten Kitas hochgerechnet. Es zeigte sich, dass der ungefähre Verlauf der Kita- Ausbrüche während der zweiten und dritten Welle der Coronavirus Disease 19-(COVID-19-)Pandemie von beiden Systemen ähnlich beschrieben wird, die Zahl der potenziellen Ausbrüche (über das KiTa- Register) aber deutlich höher ist als die Zahl der über das Meldesystem übermittelten Ausbrüche. Der Anteil der Ausbrüche, in denen nur Kinder be- troffen waren, stieg seit Beginn der COVID-19-Impf- kampagne Anfang 2021 an und wurde von beiden Systemen angezeigt. Die Unterschiede in der Zahl der übermittelten bzw. potenziellen Ausbrüche könnte darauf zurückzuführen sein, dass Gesund- heitsämter auftretende Fälle und ihre Zusammen- hänge epidemiologisch bewerten, diese Bewertung aber in den KiTa-Register-Daten nicht möglich ist. Dafür spiegeln die Daten aus dem KiTa-Register möglicherweise den Infektionsdruck, d. h. das Risi- ko, dass es zu Infektionsfällen kommt, besser wider, unter dem Kitas ihre Arbeit bewältigen müssen.

Over the course of the second pandemic wave in late 2020, new infections with severe acute respiratory syndrome coronavirus-2 shifted from the most affluent to the most deprived regions of Germany. This study investigated how this trend in infections played out for deaths due to coronavirus disease 2019 (COVID-19) by examining area-level socio-economic disparities in COVID-19-related mortality during the second pandemic wave in Germany. The analysis was based on nationwide data on notified deaths, which were linked to an area-based index of socio-economic deprivation. In the autumn and winter of 2020/2021, COVID-19-related deaths increased faster among residents in Germany's more deprived districts. From late 2020 onwards, the mortality risks of men and women in the most deprived districts were 1.52 (95% confidence interval [CI] 1.27−1.82] and 1.44 (95% CI 1.19−1.73) times higher than among those in the most affluent districts, respectively, after adjustment for age, urbanization and population density. To promote health equity in the pandemic and beyond, deprived populations should receive increased attention in pandemic planning, infection control and disease prevention.

Objective Evidence on socioeconomic inequalities in infections with the novel coronavirus (SARS-CoV-2) is still limited as most of the available studies are ecological in nature and individual-level data is sparse. We therefore analysed individual-level data on socioeconomic differences in the prevalence and perceived dangerousness of SARS-CoV-2 infections in local populations. Data were obtained from a population-based seroepidemiological study of adult individuals in two early German SARS-CoV-2 hotspots (n = 3903). Infection was determined by IgG antibody ELISA, RT-PCR testing and self-reports on prior positive PCR tests. The perceived dangerousness of an infection and socioeconomic position (SEP) were assessed by self-reports. Logistic and linear regression were applied to examine associations of multiple SEP measures with infection status and perceptions of dangerousness. Results We found no evidence of socioeconomic inequalities in SARS-CoV-2 infections by education, occupation, income and subjective social status. Participants with lower education and lower subjective social status perceived an infection as more dangerous than their better-off counterparts. In successfully contained local outbreaks of SARS-CoV-2 in Germany, infections may have been equally distributed across the socioeconomic spectrum. But residents in disadvantaged socioeconomic groups might have experienced a higher level of mental distress due to the higher perceived dangerousness of an infection.

Zusammenfassung Das Severe Acute Respiratory Syndrome Coronavirus Type 2 (SARS-CoV-2) hat sich seit 2020 weltweit verbreitet. In Deutschland haben sich bis zum Ende Juni 2021 über 3,7 Mio. Menschen infiziert. Das Infektionsgeschehen betrifft jedoch nicht alle Bevölkerungsgruppen gleichmäßig. Einige Gruppen haben ein besonders hohes Risiko, sich zu infizieren oder nach der Infektion schwere Coronavirus-Disease-2019(COVID-19)-Verläufe zu erleiden. Der vorliegende narrative Review vermittelt eine Übersicht über die Bevölkerungsgruppen in Deutschland, welche besonders von COVID-19 betroffen sind. Außerdem werden die bisher identifizierten Risikofaktoren beschrieben, die mit Krankenhausaufenthalten oder schweren COVID-19-Verläufen assoziiert sind. SARS-CoV-2-Übertragungen finden an den verschiedensten Orten und in unterschiedlichen Situationen statt. Besonders betroffen erscheinen bestimmte berufliche Umgebungen, wie z. B. die Fleisch verarbeitende Industrie, aber auch Freizeitaktivitäten und Großveranstaltungen. Es wurden im Laufe der Pandemie Komorbiditäten identifiziert, die mit einem erhöhten Hospitalisierungsrisiko oder einem schweren COVID-19-Verlauf assoziiert sind, z. B. vorbestehende Lungen‑, Herz-Kreislauf- und Stoffwechselkrankheiten. Patientinnen und Patienten nach Organtransplantation und Personen mit Downsyndrom (Trisomie 21) haben nach einer SARS-CoV-2-Infektion das höchste Risiko für eine stationäre Behandlung. Die identifizierten Rahmenbedingungen, die eine SARS-CoV-2-Verbreitung begünstigen, und das Wissen um besonders vulnerable Bevölkerungsgruppen bilden eine wichtige Evidenzgrundlage für die Planung von Präventionsstrategien und Maßnahmen zur Pandemiebekämpfung.