COVID-19 isolation and quarantine orders in Berlin-Reinickendorf (Germany): How many, how long and to whom?

Isolating COVID-19 cases and quarantining their close contacts can prevent COVID-19 transmissions but also inflict harm. We analysed isolation and quarantine orders by the local public health agency in Berlin-Reinickendorf (Germany) and their dependence on the recommendations by the Robert Koch Institute, the national public health institute. Between 3 March 2020 and 18 December 2021 the local public health agency ordered 24 603 isolations (9.2 per 100 inhabitants) and 45 014 quarantines (17 per 100 inhabitants) in a population of 266 123. The mean contacts per case was 1.9. More days of quarantine per 100 inhabitants were ordered for children than for adults: 4.1 for children aged 0-6, 5.2 for children aged 7-17, 0.9 for adults aged 18-64 and 0.3 for senior citizens aged 65-110. The mean duration for isolation orders was 10.2 and for quarantine orders 8.2 days. We calculated a delay of 4 days between contact and quarantine order. 3484 contact persons were in quarantine when they developed an infection. This represents 8% of all individuals in quarantine and 14% of those in isolation. Our study quantifies isolation and quarantine orders, shows that children had been ordered to quarantine more than adults and that there were fewer school days lost to isolation or quarantine as compared to school closures. Our results indicate that the recommendations of the Robert Koch Institute had an influence on isolation and quarantine duration as well as contact identification and that the local public health agency was not able to provide rigorous contact tracing, as the mean number of contacts was lower than the mean number of contacts per person known from literature. Additionally, a considerable portion of the population underwent isolation or quarantine, with a notable number of cases emerging during the quarantine period.

EsteR - A Digital Toolkit for COVID-19 Decision Support in Local Health Authorities.

In Germany, the current COVID-19 cases are managed and reported by the local health authorities. The workload of their employees during the pandemic is high, especially in periods of high infection numbers. In this work a decision support toolkit for local health authorities is introduced. A demonstrator web application was developed with the R Shiny framework and is publicly accessible online. It contains five separate tools based on statistical models for specific use cases and corresponding questions of COVID-19 cases and their contacts. The underlying statistical methods have been implemented in a new open-source R package. The toolkit has the potential to support local health authorities' employees in their daily work. A simulated-based validation of the statistical models and a usability evaluation of the demonstrator application in a user study will be carried out in the future.

[Quantifying the Developments of Shortages in Public Health Specialists in the Public Health Service and its Effects]. / Quantifizierung der Entwicklungen des Mangels an Fachärzten/innen für Öffentliches Gesundheitswesen im Öffentlichen Gesundheitsdienst und seine Auswirkungen.

The institutions of the Public Health Service at the level of the federal government, the states and the local authorities play a central role in public health in Germany. To manage the many practical tasks of health protection, disease prevention and health promotion in accordance with legal requirements, employees with different skills work together and contribute to social coherence. There are no empirical data on nationwide staffing levels. For years, different actors have been reporting a decreasing number of public health consultants and associated quality of public health work. The aim of this study was to quantify the public health consultant decline and to present regional trends. Regularly collected and freely available data on medical consultants registered in Germany from 1998 to 2018 were descriptively analysed with regard to developments in the number of consultants in Germany, in the regions of the Medical Associations, by specialty and age. While the total number of medical consultants in Germany has continuously increased (52%), the number of those working in administrative positions, public corporate bodies, etc. has remained relatively constant at 2%. In contrast, the number of public health consultants working in administrative offices, public corporate bodies, etc. over the last 20 years has decreased by almost 30%. Similar developments can be seen in all regions, with some even larger decreases in some regions. Bavaria is the only region with a contrasting development. There is almost no new generation of public health consultants and the number of older consultants in this field is increasing. Against this background, the availability of a sufficient number of qualified professionals to manage administrative and other tasks relevant to population medicine must be questioned. These developments threaten public health in general, public concern for vulnerable population groups in particular, and ultimately the functioning of the democratic welfare state.

A Statistical Model to Assess Risk for Supporting COVID-19 Quarantine Decisions.

In Germany, local health departments are responsible for surveillance of the current pandemic situation. One of their major tasks is to monitor infected persons. For instance, the direct contacts of infectious persons at group meetings have to be traced and potentially quarantined. Such quarantine requirements may be revoked, when all contact persons obtain a negative polymerase chain reaction (PCR) test result. However, contact tracing and testing is time-consuming, costly and not always feasible. In this work, we present a statistical model for the probability that no transmission of COVID-19 occurred given an arbitrary number of negative test results among contact persons. Hereby, the time-dependent sensitivity and specificity of the PCR test are taken into account. We employ a parametric Bayesian model which combines an adaptable Beta-Binomial prior and two likelihood components in a novel fashion. This is illustrated for group events in German school classes. The first evaluation on a real-world dataset showed that our approach can support important quarantine decisions with the goal to achieve a better balance between necessary containment of the pandemic and preservation of social and economic life. Future work will focus on further refinement and evaluation of quarantine decisions based on our statistical model.

Hepatitis A outbreak among MSM in Berlin due to low vaccination coverage: Epidemiology, management, and successful interventions.

OBJECTIVES: To describe the characteristics of a large hepatitis A virus (HAV) outbreak among men who have sex with men (MSM) in Berlin and to assess the impact of measures implemented. METHODS: Cases of laboratory-confirmed, symptomatic HAV infection notified in Berlin, Germany between August 2016 and February 2018 were analysed using routine and enhanced surveillance data including genotyping results. Several studies involving different groups of participants were conducted to further investigate the outbreak, including surveys on knowledge and practices of HAV vaccination among physicians and vaccination coverage and determinants of vaccination status among MSM. The measures implemented were categorized by target group in a Gantt chart. To assess their impact, health insurance data on HAV vaccination uptake were analysed, comparing Berlin and other federal states. RESULTS: During the outbreak period, a total of 222 cases were reported (of which 91 were sequence-confirmed), with a peak in case numbers in January 2017. Physicians were aware of the existing vaccination recommendations, but vaccination coverage among 756 MSM was low, with 32.7% being completely vaccinated and 17.3% being incompletely vaccinated before 2017. HAV vaccination before 2017 was associated with being born in Germany (odds ratio 2.36) and HIV-positive (odds ratio 1.80). HAV monovalent vaccination uptake increased by 164% from 2016 to 2017 among males in Berlin, compared to 7% in other federal states. CONCLUSIONS: Multiple measures targeting the MSM community, physicians, and public health to increase HAV vaccination uptake were successfully implemented. To prevent future HAV outbreaks, we recommend monitoring vaccination coverage among MSM, promoting awareness of existing recommendations among physicians, and ensuring access for foreign-born and young MSM.

Source attribution of community-acquired cases of Legionnaires' disease-results from the German LeTriWa study; Berlin, 2016-2019.

INTRODUCTION: Sources of infection of most cases of community-acquired Legionnaires' disease (CALD) are unknown. OBJECTIVE: Identification of sources of infection of CALD. SETTING: Berlin; December 2016-May 2019. PARTICIPANTS: Adult cases of CALD reported to district health authorities and consenting to the study; age and hospital matched controls. MAIN OUTCOME MEASURE: Percentage of cases of CALD with attributed source of infection. METHODS: Analysis of secondary patient samples for monoclonal antibody (MAb) type (and sequence type); questionnaire-based interviews, analysis of standard household water samples for Legionella concentration followed by MAb (and sequence) typing of Legionella pneumophila serogroup 1 (Lp1) isolates; among cases taking of additional water samples to identify the infectious source as appropriate; recruitment of control persons for comparison of exposure history and Legionella in standard household water samples. For each case an appraisal matrix was filled in to attribute any of three source types (external (non-residence) source, residential non-drinking water (RnDW) source (not directly from drinking water outlet), residential drinking water (RDW) as source) using three evidence types (microbiological results, cluster evidence, analytical-comparative evidence (using added information from controls)). RESULTS: Inclusion of 111 study cases and 202 controls. Median age of cases was 67 years (range 25-93 years), 74 (67%) were male. Among 65 patients with urine typable for MAb type we found a MAb 3/1-positive strain in all of them. Compared to controls being a case was not associated with a higher Legionella concentration in standard household water samples, however, the presence of a MAb 3/1-positive strain was significantly associated (odds ratio (OR) = 4.9, 95% confidence interval (CI) 1.7 to 11). Thus, a source was attributed by microbiological evidence if it contained a MAb 3/1-positive strain. A source was attributed by cluster evidence if at least two cases were exposed to the same source. Statistically significant general source types were attributed by calculating the population attributable risk (analytical-comparative evidence). We identified an external source in 16 (14%) cases, and RDW as source in 28 (25%). Wearing inadequately disinfected dentures was the only RnDW source significantly associated with cases (OR = 3.2, 95% CI 1.3 to 7.8) and led to an additional 8% of cases with source attribution, for a total of 48% of cases attributed. CONCLUSION: Using the appraisal matrix we attributed almost half of all cases of CALD to an infectious source, predominantly RDW. Risk for LD seems to be conferred primarily by the type of Legionella rather than the amount. Dentures as a new infectious source needs further, in particular, integrated microbiological, molecular and epidemiological confirmation.

Epidemic curves made easy using the R package incidence.

The epidemiological curve (epicurve) is one of the simplest yet most useful tools used by field epidemiologists, modellers, and decision makers for assessing the dynamics of infectious disease epidemics. Here, we present the free, open-source package incidence for the R programming language, which allows users to easily compute, handle, and visualise epicurves from unaggregated linelist data. This package was built in accordance with the development guidelines of the R Epidemics Consortium (RECON), which aim to ensure robustness and reliability through extensive automated testing, documentation, and good coding practices. As such, it fills an important gap in the toolbox for outbreak analytics using the R software, and provides a solid building block for further developments in infectious disease modelling. incidence is available from https://www.repidemicsconsortium.org/incidence.

Timeliness in the German surveillance system for infectious diseases: Amendment of the infection protection act in 2013 decreased local reporting time to 1 day.

Time needed to report surveillance data within the public health service delays public health actions. The amendment to the infection protection act (IfSG) from 29 March 2013 requires local and state public health agencies to report surveillance data within one working day instead of one week. We analysed factors associated with reporting time and evaluated the IfSG amendment. Local reporting time is the time between date of notification and date of export to the state public health agency and state reporting time is time between date of arrival at the state public health agency and the date of export. We selected cases reported between 28 March 2012 and 28 March 2014. We calculated the median local and state reporting time, stratified by potentially influential factors, computed a negative binominal regression model and assessed quality and workload parameters. Before the IfSG amendment the median local reporting time was 4 days and 1 day afterwards. The state reporting time was 0 days before and after. Influential factors are the individual local public health agency, the notified disease, the notification software and the day of the week. Data quality and workload parameters did not change. The IfSG amendment has decreased local reporting time, no relevant loss of data quality or identifiable workload-increase could be detected. State reporting time is negligible. We recommend efforts to harmonise practices of local public health agencies including the exclusive use of software with fully compatible interfaces.