Changes in emergency department utilisation in Germany before and during different phases of the COVID-19 pandemic, using data from a national surveillance system up to June 2021.

BACKGROUND: During the COVID-19 pandemic and associated public health and social measures, decreasing patient numbers have been described in various healthcare settings in Germany, including emergency care. This could be explained by changes in disease burden, e.g. due to contact restrictions, but could also be a result of changes in utilisation behaviour of the population. To better understand those dynamics, we analysed routine data from emergency departments to quantify changes in consultation numbers, age distribution, disease acuity and day and hour of the day during different phases of the COVID-19 pandemic. METHODS: We used interrupted time series analyses to estimate relative changes for consultation numbers of 20 emergency departments spread throughout Germany. For the pandemic period (16-03-2020 - 13-06-2021) four different phases of the COVID-19 pandemic were defined as interruption points, the pre-pandemic period (06-03-2017 - 09-03-2020) was used as the reference. RESULTS: The most pronounced decreases were visible in the first and second wave of the pandemic, with changes of - 30.0% (95%CI: - 32.2%; - 27.7%) and - 25.7% (95%CI: - 27.4%; - 23.9%) for overall consultations, respectively. The decrease was even stronger for the age group of 0-19 years, with - 39.4% in the first and - 35.0% in the second wave. Regarding acuity levels, consultations assessed as urgent, standard, and non-urgent showed the largest decrease, while the most severe cases showed the smallest decrease. CONCLUSIONS: The number of emergency department consultations decreased rapidly during the COVID-19 pandemic, without extensive variation in the distribution of patient characteristics. Smallest changes were observed for the most severe consultations and older age groups, which is especially reassuring regarding concerns of possible long-term complications due to patients avoiding urgent emergency care during the pandemic.

Disease severity in hospitalized COVID-19 patients: comparing routine surveillance with cohort data from the LEOSS study in 2020 in Germany.

INTRODUCTION: Studies investigating risk factors for severe COVID-19 often lack information on the representativeness of the study population. Here, we investigate factors associated with severe COVID-19 and compare the representativeness of the dataset to the general population. METHODS: We used data from the Lean European Open Survey on SARS-CoV-2 infected patients (LEOSS) of hospitalized COVID-19 patients diagnosed in 2020 in Germany to identify associated factors for severe COVID-19, defined as progressing to a critical disease stage or death. To assess the representativeness, we compared the LEOSS cohort to cases of hospitalized patients in the German statutory notification data of the same time period. Descriptive methods and Poisson regression models were used. RESULTS: Overall, 6672 hospitalized patients from LEOSS and 132,943 hospitalized cases from the German statutory notification data were included. In LEOSS, patients above 76 years were less likely represented (34.3% vs. 44.1%). Moreover, mortality was lower (14.3% vs. 21.5%) especially among age groups above 66 years. Factors associated with a severe COVID-19 disease course in LEOSS included increasing age, male sex (adjusted risk ratio (aRR) 1.69, 95% confidence interval (CI) 1.53-1.86), prior stem cell transplantation (aRR 2.27, 95% CI 1.53-3.38), and an elevated C-reactive protein at day of diagnosis (aRR 2.30, 95% CI 2.03-2.62). CONCLUSION: We identified a broad range of factors associated with severe COVID-19 progression. However, the results may be less applicable for persons above 66 years since they experienced lower mortality in the LEOSS dataset compared to the statutory notification data.

Using routine emergency department data for syndromic surveillance of acute respiratory illness, Germany, week 10 2017 until week 10 2021.

BackgroundThe COVID-19 pandemic expanded the need for timely information on acute respiratory illness at population level.AimWe explored the potential of routine emergency department data for syndromic surveillance of acute respiratory illness in Germany.MethodsWe 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.ResultsWe 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%).ConclusionSyndromic 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.

SARS-CoV-2 Omicron variants BA.1 and BA.2 both show similarly reduced disease severity of COVID-19 compared to Delta, Germany, 2021 to 2022.

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.

Disease severity of the first COVID-19 wave in Germany using reporting data from the national notification system.

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.

Socioeconomic inequalities and COVID-19 - A review of the current international literature.

Social epidemiological research describes correlations between socioeconomic status and the population's risk to become diseased or die. Little research of such correlations for SARS-CoV-2 and COVID-19 has so far been conducted. This scoping review provides an overview of the international research literature. Out of the 138 publications found, 46 were later included in the analysis. For the US and the UK, the reported findings indicate the presence of socioeconomic inequalities in infection risks as well as the severity of the course of the disease, with socioeconomically less privileged populations being hit harder. There are far fewer findings for Germany to date, as is the case for most other European countries. However, the scant evidence available so far already indicates that social inequalities are a factor in COVID-19. Most of these analyses have been ecological studies with only few studies considering socioeconomic inequalities at the individual level. Such studies at the individual level are particularly desirable as they could help to increase our understanding of the underlying pathways that lead to the development of inequalities in infection risks and the severity of disease and thereby could provide a basis to counteract the further exacerbation of health inequalities.

Socioeconomic inequalities in the risk of SARS-CoV-2 infection - First results from an analysis of surveillance data from Germany.

Experiences with acute respiratory diseases which caused virus epidemics in the past and initial findings in the research literature on the current COVID-19 pandemic suggest a higher SARS-CoV-2 infection risk for socioeconomically disadvantaged populations. Nevertheless, further research on such a potential association between socioeconomic status and SARS-CoV-2 incidence in Germany is required. This article reports on the results of a first Germany-wide analysis of COVID-19 surveillance data to which an area-level index of socioeconomic deprivation was linked. The analysis included 186,839 laboratory-confirmed COVID-19 cases, the data of which was transferred to the Robert Koch Institute by 16 June 2020, 00:00. During the early stage of the epidemic up to mid-April, the data show a socioeconomic gradient with higher incidence in less deprived regions of Germany. Over the course of the epidemic, however, this gradient becomes less measurable and finally reverses in south Germany, the region hardest hit by the epidemic, to the greater detriment of the more deprived regions. These results highlight the need to continue monitoring social epidemiological patterns in COVID-19 and analysing the underlying causes to detect dynamics and trends early on and countering a potential exacerbation of health inequalities.

Emerging socio-economic disparities in COVID-19-related deaths during the second pandemic wave in Germany.

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.

[The different periods of COVID-19 in Germany: a descriptive analysis from January 2020 to February 2021]. / Die verschiedenen Phasen der COVID-19-Pandemie in Deutschland: Eine deskriptive Analyse von Januar 2020 bis Februar 2021.

The first case of coronavirus SARS-CoV­2 infection in Germany was diagnosed on 27 January 2020. To describe the pandemic course in 2020, we regarded four epidemiologically different periods and used data on COVID-19 cases from the mandatory reporting system as well as hospitalized COVID-19 cases with severe acute respiratory infection from the syndromic hospital surveillance.Period 0 covers weeks 5 to 9 of 2020, where mainly sporadic cases of younger age were observed and few regional outbreaks emerged. In total, 167 cases with mostly mild outcomes were reported. Subsequently, the first COVID-19 wave occurred in period 1 (weeks 10 to 20 of 2020) with a total of 175,013 cases throughout Germany. Increasingly, outbreaks in hospitals and nursing homes were registered. Moreover, elderly cases and severe outcomes were observed more frequently. Period 2 (weeks 21 to 39 of 2020) was an interim period with more mild cases, where many cases were younger and often travel-associated. Additionally, larger trans-regional outbreaks in business settings were reported. Among the 111,790 cases, severe outcomes were less frequent than in period 1. In period 3 (week 40 of 2020 to week 8 of 2021), the second COVID-19 wave started and peaked at the end of 2020. With 2,158,013 reported cases and considerably more severe outcomes in all age groups, the second wave was substantially stronger than the first wave.Irrespective of the different periods, more elderly persons and more men were affected by severe outcomes.

[Social inequalities in the regional spread of SARS-CoV-2 infections]. / Soziale Ungleichheit in der regionalen Ausbreitung von SARS-CoV-2.

BACKGROUND AND OBJECTIVE: It has not been adequately answered whether the spread of SARS-CoV­2 is influenced by social and economic factors. Earlier studies generally looked at cumulative incidences up to the analysis date and did not take into account the development of the spread over time. This study therefore focuses on the regional dynamic of new infections and their relationship to socioeconomic factors. Based on the literature we describe the state of knowledge and present our own analyses of administrative data from Germany. METHODS: For this study, we examined regional progress data of reported COVID-19 cases for 401 cities and counties in Germany and associated them with socioeconomic characteristics of the areas. Age-standardized weekly incidence rates were calculated for the period from 3 February 2020 to 28 March 2021. Macroindicators were added from the INKAR database (e.g., income, employment rate, and crowding). RESULTS: While areas with higher incomes and lower poverty had higher incidences in the first and at the beginning of the second wave of the pandemic, they increased significantly in low-income regions from December 2020 on. Regions with a high proportion of gainfully employed people in general and especially those in the manufacturing sector had high incidences, especially in the second wave and at the beginning of the third wave. A low mean living space per inhabitant was related to higher incidence rates since November 2020. CONCLUSION: The regional temporal course of the pandemic correlates with social and economic indicators. A differentiated consideration of these differences could provide information on target group-specific protection and test strategies and help to identify social factors that generally favor infections. An English full-text version of this article is available at SpringerLink as Supplementary Information.

Impact of the COVID-19 pandemic and associated non-pharmaceutical interventions on other notifiable infectious diseases in Germany: An analysis of national surveillance data during week 1-2016 - week 32-2020.

BACKGROUND: The COVID-19 pandemic and associated non-pharmaceutical interventions (NPIs) affect healthcare seeking behaviour, access to healthcare, test strategies, disease notification and workload at public health authorities, but may also lead to a true change in transmission dynamics. We aimed to assess the impact of the pandemic and NPIs on other notifiable infectious diseases under surveillance in Germany. METHODS: We included 32 nationally notifiable disease categories with case numbers >100/year in 2016-2019. We used quasi-Poisson regression analysis on a weekly aggregated time-series incorporating trend and seasonality, to compute the relative change in case numbers during week 2020-10 to 2020-32 (pandemic/NPIs), in comparison to week 2016-01 to 2020-09. FINDINGS: During week 2020-10 to 2020-32, 216,825 COVID-19 cases, and 162,942 (-35%) cases of other diseases, were notified. Case numbers decreased across all ages and notification categories (all p<0•05), except for tick-borne encephalitis, which increased (+58%). The number of cases decreased most for respiratory diseases (from -86% for measles, to -12% for tuberculosis), gastro-intestinal diseases (from -83% for rotavirus gastroenteritis, to -7% for yersiniosis) and imported vector-borne diseases (-75% dengue fever, -73% malaria). The less affected infections were healthcare associated pathogens (from -43% infection/colonisation with carbapenem-non-susceptible Acinetobacter, to -28% for Methicillin-resistant Staphylococcus aureus invasive infection) and sexually transmitted and blood-borne diseases (from -28% for hepatitis B, to -12% for syphilis). INTERPRETATION: During the COVID-19 pandemic a drastic decrease of notifications for most infectious diseases and pathogens was observed. Our findings suggest effects of NPIs on overall disease transmission that require further investigation. FUNDING: The Robert Koch Institute is the National Public Health Institute of Germany, and is an institute within the portfolio of the Federal Ministry of Health.

The COVID-19 Disease Burden in Germany in 2020­Years of Life Lost to Death and Disease Over the Course of the Pandemic.

BACKGROUND: The SARS-CoV-2 pandemic presented major challenges to the health sector in 2020. The burden of disease arising from COVID-19 can be expressed as the number of years of life lost to disease or death. For example, death at age 40 involves a loss of far more years of life than death at age 80. METHODS: The disability-adjusted life years (DALY) lost to COVID-19 were calculated as the sum of the years of life lost through death (YLL) and the number of years lived with disability (YLD), on the basis of laboratory-confirmed notifiable cases of SARS-CoV-2 infection in Germany in 2020 (documented as of 18 January 2021). The methodology was based on that used in the Global Burden of Disease Study. Pre-existing diseases do not enter into the determination of YLL; rather, the residual life expectancy that is applied in this calculation corresponds to a mean age-specific level of morbidity. RESULTS: 305 641 years of life were lost to COVID-19 in Germany in 2020. The percentage of DALY lost by persons under 70 was 34.8% in men and 21.0% in women. 99.3% of the COVID-19 disease burden was accounted for by death (YLL). The daily average years of life lost due to death was lower for COVID-19 than for the major non-communicable diseases. Persons who died of COVID-19 lost a mean of 9.6 years of life; those who were under 70 when they died lost a mean of 25.2 years of life. Men lost more years of life than women (11.0 vs. 8.1 years). CONCLUSION: The effects of COVID-19 on public health can be expressed through the burden of disease indicators. This method yields additional information that should be put to use early in the course of future outbreaks.

[Adaptation of the routine surveillance system for infectious diseases in 2020 in the context of the COVID-19 pandemic]. / Anpassung des Meldesystems gemäß Infektionsschutzgesetz im Jahr 2020 aufgrund von COVID-19.

In response to the COVID-19 pandemic the routine surveillance system for infectious diseases had to be adapted. The disease was unknown before the first cases were reported under a catch-all notification requirement for new and threatening pathogens and diseases, but specific notification requirements for SARS-CoV­2 detection by laboratories as well as for suspect cases of COVID-19 diagnosed by physicians were soon integrated in the infectious diseases protection act. This article describes how the notification system for infectious diseases was adapted in 2020 to meet the requirements of the COVID-19 pandemic.In addition to the notification requirements, the list of data that is collected through the notification system was also amended. To facilitate the work of laboratories and local health authorities we have established the possibility for electronic reporting.Additionally, the software used for case and contact management within the local health authorities had to be adapted accordingly.COVID-19 notification data is important for the assessment of the current epidemiological situation and daily updated data was published by the Robert Koch Institute. To ensure timely data and good data quality, the IT infrastructure within the public health system has to be further modernized and the electronic notification system should be further strengthened.