Excess mortality during the SARS-CoV-2 pandemic in the City of Frankfurt/Main, Germany, in 2020 and 2021, adjusted for age trends and pandemic phases.

Aims: Excess mortality during the SARS-CoV-2 pandemic has been studied in many countries. Accounting for population aging has important implications for excess mortality estimates. We show the importance of adjustment for age trends in a small-scale mortality analysis as well as the importance of analysing different pandemic phases for mortality in an urban population. Methods: Population data for Frankfurt/Main for 2016-2021 were obtained from the Municipal Office of Statistics, City of Frankfurt/Main. Mortality data from 2016 to 2021 were provided by the Hessian State Authority. For standardized mortality ratios (SMR=observed number of deaths divided by the expected number of deaths), the expected number of deaths was calculated in two ways: For SMRcrude, the mean mortality rate from the years 2016-2019 was multiplied by the total number of residents in 2020 and 2021 separately. For SMRadjusted, this procedure was performed separately for five age groups, and the numbers of expected deaths per age group were added. Results: SMRcrude was 1.006 (95% CI: 0.980-1.031) in 2020, and 1.047 (95% CI: 1.021-1.073) in 2021. SMRadjusted was 0.976 (95% CI: 0.951-1.001) in 2020 and 0.998 (95% CI: 0.973-1.023) in 2021. Excess mortality was observed during pandemic wave 2, but not during pandemic waves 1 and 3. Conclusion: Taking the aging of the population into account, no excess mortality was observed in Frankfurt/Main in 2020 and 2021. Without adjusting for population aging trends in Frankfurt /Main, mortality would have been greatly overestimated.

Real-time monitoring shows substantial excess all-cause mortality during second wave of COVID-19 in Europe, October to December 2020.

The European monitoring of excess mortality for public health action (EuroMOMO) network monitors weekly excess all-cause mortality in 27 European countries or subnational areas. During the first wave of the coronavirus disease (COVID-19) pandemic in Europe in spring 2020, several countries experienced extraordinarily high levels of excess mortality. Europe is currently seeing another upsurge in COVID-19 cases, and EuroMOMO is again witnessing a substantial excess all-cause mortality attributable to COVID-19.

Excess all-cause mortality during the COVID-19 pandemic in Europe - preliminary pooled estimates from the EuroMOMO network, March to April 2020.

A remarkable excess mortality has coincided with the COVID-19 pandemic in Europe. We present preliminary pooled estimates of all-cause mortality for 24 European countries/federal states participating in the European monitoring of excess mortality for public health action (EuroMOMO) network, for the period March-April 2020. Excess mortality particularly affected ≥ 65 year olds (91% of all excess deaths), but also 45-64 (8%) and 15-44 year olds (1%). No excess mortality was observed in 0-14 year olds.

[Monitoring heat-related mortality in Hesse]. / Monitoring hitzebedingter Sterblichkeit in Hessen.

BACKGROUND: Continuous monitoring of the mortality phenomenon is given high priority in the current recommendations for the preparation of heat action plans in Germany with respect to problem detection and evaluation of interventions. International monitoring systems are heterogeneous concerning the procedures used. In Germany, such monitoring systems are rarely established. OBJECTIVES: Under what circumstances can a mortality monitoring system be operated on a regional basis using routine data? MATERIALS AND METHODS: Summer mortality data from Hesse from 2000 to 2018 and their associations with climate variables were analyzed. Different approaches regarding spatial analyses, definition of excess criteria, and adjusting procedures were explored. RESULTS: In Hesse, daily mean temperatures averaged over all operating weather stations proved appropriate as a climate parameter. The expected daily number of deaths was estimated by a moving average based on 25 daily mortality datasets from reference periods of five years adjusted for mortality peaks using data from three previous years. Mortality excess was defined as twice the value of the standard deviation of the expected values including an empirically determined temperature threshold. This threshold was derived from analyzing relative frequencies of observed excess number of deaths per 1 ℃ temperature interval. Based on this approach, 49 mortality excesses with a total of 889 excess deaths were estimated in Hesse during days with a daily mean temperature of more than 23.0 ℃ during summer from 2005 to 2018. CONCLUSIONS: The system described in this article turned out to be practicable for systematically monitoring mortality during summer. Timely availability of mortality and climate data is crucial.

[Influenza pandemic deaths in Germany from 1918 to 2009. Estimates based on literature and own calculations]. / Todesfälle durch Influenzapandemien in Deutschland 1918 bis 2009. Schätzwerte auf Basis der Literatur und ergänzende eigene Berechnungen.

BACKGROUND AND OBJECTIVE: 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. METHOD: 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. RESULTS: 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. CONCLUSION: 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.

Extended-spectrum beta-lactamase-producing Shiga toxin gene (stx1)-positive Escherichia coli O91:H14 carrying blaCTX-M-15 on an IncI1-ST31 plasmid isolated from a human patient in Germany.

In 2011, the Shiga toxin- and extended-spectrum ß-lactamase (ESBL)-producing Escherichia coli O104:H4 caused a serious outbreak of gastroenteritis in Germany. This strain carried bla(CTX-M-15) and bla(TEM-1) on an IncI1-ST31 plasmid. During screening of individuals at risk for acquisition of the epidemic E. coli O104:H4, we isolated another ESBL-producing and Shiga toxin-positive E. coli belonging to serotype O91:H14 from feces of a human patient. Interestingly, the patient also carried a further ESBL-producing but Shiga toxin-negative E. coli. Both strains harbored bla(CTX-M-15) and bla(TEM-1) on an IncI1-ST31 plasmid, which was indistinguishable regarding size and plasmid restriction pattern from the plasmid of the epidemic E. coli O104:H4 strain. The patient had traveled to India 6 months prior to the isolation of the E. coli strains. This is the first report of an ESBL-producing, Shiga toxin-positive E. coli of serogroup O91. Our data suggest a high propensity of the IncI1-ST31 plasmid to spread in the human and/or animal population.

4Flu - an individual based simulation tool to study the effects of quadrivalent vaccination on seasonal influenza in Germany.

BACKGROUND: Influenza vaccines contain Influenza A and B antigens and are adjusted annually to match the characteristics of circulating viruses. In Germany, Influenza B viruses belonged to the B/Yamagata lineage, but since 2001, the antigenically distinct B/Victoria lineage has been co-circulating. Trivalent influenza vaccines (TIV) contain antigens of the two A subtypes A(H3N2) and A(H1N1), yet of only one B lineage, resulting in frequent vaccine mismatches. Since 2012, the WHO has been recommending vaccine strains from both B lineages, paving the way for quadrivalent influenza vaccines (QIV). METHODS: Using an individual-based simulation tool, we simulate the concomitant transmission of four influenza strains, and compare the effects of TIV and QIV on the infection incidence. Individuals are connected in a dynamically evolving age-dependent contact network based on the POLYMOD matrix; their age-distribution reproduces German demographic data and predictions. The model considers maternal protection, boosting of existing immunity, loss of immunity, and cross-immunizing events between the B lineages. Calibration to the observed annual infection incidence of 10.6% among young adults yielded a basic reproduction number of 1.575. Vaccinations are performed annually in October and November, whereby coverage depends on the vaccinees' age, their risk status and previous vaccination status. New drift variants are introduced at random time points, leading to a sudden loss of protective immunity for part of the population and occasionally to reduced vaccine efficacy. Simulations run for 50 years, the first 30 of which are used for initialization. During the final 20 years, individuals receive TIV or QIV, using a mirrored simulation approach. RESULTS: Using QIV, the mean annual infection incidence can be reduced from 8,943,000 to 8,548,000, i.e. by 395,000 infections, preventing 11.2% of all Influenza B infections which still occur with TIV (95% CI: 10.7-11.8%). Using a lower B lineage cross protection than the baseline 60%, the number of Influenza B infections increases and the number additionally prevented by QIV can be 5.5 times as high. CONCLUSIONS: Vaccination with TIV substantially reduces the Influenza incidence compared to no vaccination. Depending on the assumed degree of B lineage cross protection, QIV further reduces Influenza B incidence by 11-33%.

Effectiveness of the AS03-adjuvanted vaccine against pandemic influenza virus A/(H1N1) 2009--a comparison of two methods; Germany, 2009/10.

During the autumn wave of the pandemic influenza virus A/(H1N1) 2009 (pIV) the German population was offered an AS03-adjuvanted vaccine. The authors compared results of two methods calculating the effectiveness of the vaccine (VE). The test-negative case-control method used data from virologic surveillance including influenza-positive and negative patients. An innovative case-series methodology explored data from all nationally reported laboratory-confirmed influenza cases. The proportion of reported cases occurring in vaccinees during an assumed unprotected phase after vaccination was compared with that occurring in vaccinees during their assumed protected phase. The test-negative case-control method included 1,749 pIV cases and 2,087 influenza test-negative individuals of whom 6 (0.3%) and 36 (1.7%), respectively, were vaccinated. The case series method included data from 73,280 cases. VE in the two methods was 79% (95% confidence interval (CI) = 35-93%; P = 0.007) and 87% (95% CI = 78-92%; P<0.001) for individuals less than 14 years of age and 70% (95% CI = -45%-94%, P = 0.13) and 74% (95% CI = 64-82%; P<0.001) for individuals above the age of 14. Both methods yielded similar VE in both age groups; and VE for the younger age group seemed to be higher.

Electronic outbreak surveillance in Germany: a first evaluation for nosocomial norovirus outbreaks.

BACKGROUND: In Germany, surveillance for infectious disease outbreaks is integrated into an electronic surveillance system. For 2007, the national surveillance database contains case-based information on 201,224 norovirus cases, three-quarters of which are linked to outbreaks. We evaluated the data quality of the national database in reflecting nosocomial norovirus outbreak (NNO) data available in 19 Hessian local public health authorities (LPHAs) and the influence of differences between LPHA's follow-up procedures for laboratory notifications of Norovirus positive stool samples on outbreak underascertainment. METHODS: Data on NNO beginning in 2007 and notified to the 19 LPHAs were extracted from the national database, investigated regarding internal validity and compared to data collected from LPHAs for a study on NNO control. LPHAs were questioned whether they routinely contacted all persons for whom a laboratory diagnosis of norovirus infection was notified. The number of outbreaks per 1,000 hospital beds and the number of cases within NNOs for acute care and rehabilitation hospitals were compared between counties with and without complete follow-up. RESULTS: The national database contained information on 155 NNOs, including 3,115 cases. Cases were missed in the national database in 58 (37%) of the outbreaks. Information on hospitalisation was incorrect for an estimated 47% of NNO cases. Information on county of infection was incorrect for 24% (199/820) of cases being forwarded between LPHAs for data entry. Reported NNO incidence and number of NNO cases in acute care hospitals was higher in counties with complete follow-up (incidence-rate ratio (IRR) 2.7, 95% CI 1.4-5.7, p-value 0.002 and IRR 2.1, 95% CI 1.9-2.4, p-value 0.001, respectively). CONCLUSIONS: Many NNOs are not notified by hospitals and differences in LPHA procedures have an impact on the number of outbreaks captured in the surveillance system. Forwarding of case-by-case data on Norovirus outbreak cases from the local to the state and national level should not be required.

Risk factors for hantavirus infection in Germany, 2005.

In 2005, a marked increase in hantavirus infections was observed in Germany. Large cities and areas where hantaviruses were not known to be endemic were affected. A case-control study identified the following independent risk factors for infection: occupational exposure for construction workers, living <100 meter from forested areas, and exposure to mice.

Factors that affect influenza vaccine uptake among staff of long-term care facilities.

A survey of directors and employees of 36 long-term care facilities in Hesse, Germany, revealed that influenza vaccine uptake among staff was less than 30% in 30 and greater than 50% in 6. The study identified policies and practices associated with vaccination uptake at long-term care facilities and factors associated with the decision of staff to get vaccinated.

Influenza associated excess mortality in Germany, 1985-2001.

Influenza-associated excess mortality is widely used to assess the severity of influenza epidemics. In Germany, however, it is not yet established as a routine component of influenza surveillance. We therefore applied a simple method based on the annual distribution of monthly relative mortality (relative mortality distribution method, RMDM) to a time-series of German monthly all-cause mortality data from 1985-2001 to estimate influenza-associated excess mortality. Results were compared to those obtained by cyclical regression. Both methods distinguished stronger from milder influenza seasons, but RMDM gave the better fit (R2 = 0.80). For the years after reunification, i.e. 1990/91 through 2000/01, RMDM yielded an average of 6900 (conservative estimate) to 13,600 influenza-associated excess deaths per season (crude estimate). The most severe epidemics occurred during subtype A/H3N2 seasons. While German all-cause mortality declined over the study period, the number of excess deaths displayed an upward trend, coinciding with an increase of the proportion of the elderly population.