Epidemiology conducts research on health and disease at the population level – infection epidemiology is concerned with contagious diseases. Their tools and methods are systematic queries, clinical examinations and laboratory diagnostic documentation for both healthy and afflicted individuals, as well as statistical analysis of the compiled data. Causes and risk factors for infections can thus be identified. Infectious diseases epidemiology contributes to the development of preventive measures, early detection and therapy for diseases. Moreover, it examines the efficacy of such measures. Thus epidemiology ties in with scientific findings in basic research as well as medicine, and examines these processes at the population level.
Team Clinical Epidemiology
Teamleader: Dr Berit Lange
Deputy: Dr Carolina Klett-Tammen
Other team members, see EPID Members
In the Clinical Epidemiology research team, we conduct clinical and population-based epidemiological studies (e.g. https://hzi-c19-antikoerperstudie.de/en/), do evidence synthesis and meta-analyses (www.serohub.net) and investigate the dynamics of respiratory infectious diseases within large modelling networks (e.g. www.respinow.de). For this purpose, we use and evaluate digital tools and build platforms for data exchange and In the German Centre for Infection Research (https://www.dzif.de/en), we are co-coordinator of the unit of "Translational Infrastructure Bioresources, Biodata and Digital Health" (https://www.dzif.de/en/infrastructure/bioresources-biodata-and-digital-health). We are part of the Modelling Network for Serious Infectious Diseases (MONID, website to come) with two modelling consortia.
By building and sustaining infrastructures such as rapid epidemic panels, modelling platforms and rapid evidence synthesis, we conduct epidemiological studies to better understand the dynamics, transmission and burden of respiratory infections in particular. We also evaluate pharmaceutical and non-pharmaceutical interventions and diagnostics. Study sites are both national and international in Europe, Africa and Asia.
Our work is divided into the following areas with corresponding projects:
Modelling platforms to improve the effective response to epidemics and improved understanding of infection
Consortium coordinator, BMBF:
In this modelling consortium, which we lead, the medium- and long-term effects of non-pharmaceutical interventions (NPIs) used during the COVID-19 pandemic on respiratory infections such as respiratory syncytial virus, influenza and pneumococcal disease are being researched. Our aim here is to develop an integrated model to simulate the transmission of different respiratory infections and the collateral effects of NPIs on their medium- and long-term disease burden. We are working with 10 partners from Germany and Poland to use evidence synthesis and population-based surveys to better understand the dynamics of respiratory infections during and after the pandemic, create integrated modelling and a platform for short-term predictions.
This modelling consortium, led by the University of Halle, will develop a standardised framework for decision-making during a pandemic based on a specific agent-based mathematical model tailored to the German population. Particular attention will be paid to conceptualising the model incorporating expertise from different disciplines and a realistic design that takes into account heterogeneities in population structure, intra- and inter-individual contacts, mobility, individual sociological and psychological characteristics, and links epidemiological results to a framework for public health decision-making. This includes health economic analyses of direct outcomes and the impact of non-pharmaceutical interventions (NPIs) on society as a whole. The Clinical Epidemiology Unit of the HZI is particularly responsible for evidence synthesis and meta-analysis on collateral effects of non-pharmaceutical interventions to parameterise the emerging model.
This is an EU project to evaluate existing critical infrastructures within the EU and their interdependencies in the context of pandemics. Our task is the modelling of different pandemic scenarios and the compilation of literature on the likely effect of these scenarios on critical infrastructures.
Under the leadership of SIMM, HZI, this modelling consortium is establishing a local early warning system for epidemiologically relevant outbreaks of infection. The Jülich Research Centre (FZJ), the German Aerospace Centre (DLR) and the Helmholtz Centre for Environmental Research (UFZ) are involved. Clinical Epidemiology at the HZI is leading the first work package, which is concerned with providing current and retrospective data for the parameterisation of the model.
This project uses agent-based modelling to investigate structural optimisation of intensive care units. The project is led by the TU Braunschweig, and the WWU Münster, the University of Halle and the University Medical Centre Göttingen are also involved.
Establishment of rapid epidemic panels and clinical cohorts for a better understanding of the infection dynamics of respiratory infections
Lead, Helmholtz Association:
MuSPAD is a population-based epidemic panel led by us with >33,000 participants across Germany. It was set up during the pandemic to track seroprevalence against SARS-CoV-2 throughout the pandemic. In the meantime, we have converted this study into an epidemic panel, so that rapid surveys for different infectious diseases, including sample collection at study centres, are possible.
To be better prepared for future pandemics originating from a yet unknown pandemic-causing agent X, more advanced measures need to be developed that can be immediately deployed as soon as a potential PX is detected, while balancing economic activity with public safety. The PCR-4-ALL team aims to achieve this in a holistic manner by bringing together expertise in (1) epidemiology, disease modelling and e-health platforms, (2) disease econometrics and (3) high-throughput screening, diagnostic technologies and clinical testing of infectious diseases. Clinical Epidemiology is responsible for conducting investigations in the MuSPAD cohort and infection modelling - in the Epidemiology Department this is done jointly with the PIA, Cohorts and Climate team.
Within the ad hoc NUM-IMMUNEBRIDGE project, we merged data from eight studies on protection against infection and severe course of SARS-CoV-2 and made them available to the Modelling Network for Severe Infectious Diseases (MONID). Here, the Serohub was used as a tool for data pooling.
DZIF Transplant cohort
With the help of the DZIF Transplant Cohort, medical data and biological samples from transplanted patients throughout Germany can be collected and managed. These data and samples form the basis of scientific studies. In the process, correlations between the numerous factors that can have an influence on susceptibility to infection and the function of the organs are investigated.
TBNet is a network of more than 300 researchers and over 50 clinical tuberculosis centres in Europe, in which multicentre studies are carried out jointly. In TBNet we are responsible for the epidemiological part, help with the design of studies, with the evaluation and with the consolidation of studies that have already taken place.
Digital Health Tools, evidence synthesis and meta-analysis platforms
DZIF TI BBD
The infrastructure "Bioresources, Biodata and Digital Health" will in future enable overarching standardisation of biomedical data and interoperability of database systems as well as improved access to relevant biospecimens, (medical) analysis data or digital tools and methods at DZIF. The infrastructure provides information on biospecimens and pathogen collections, databases, analysis tools or apps, as well as templates, samples or work instructions, which are needed more than ever for translational infection research. Since 2021, the previous infrastructures "Biobanking", "Bioinformatics and Machine Learning", "Epidemiology" and the "Pathogen Repository" have been pooling their expertise in this new infrastructure. All DZIF researchers can use and benefit from the services, training and workshops.
Collaborative Coordinator, BMBF:
In this collaborative project, which we lead, we are working with the National Reference Laboratories in Kyrgyzstan and Armenia, the University of Freiburg, Synlab Gauteng. The aim is to establish an evidence base for the use of digital tools for TB control in the South Caucasus and Central Asia and to build potential capacity for context-sensitive and patient-centred controlled implementation of such tools in this region. Therefore, we would like to evaluate these digital tools for patients and from the user perspective in a collaborative project with the national TB control programme and create solutions for gaps that are already emerging and would be found in the process.
(Coordinator, BMBF and DZIF):
The serohub is a virtual research environment that enables individual participant data meta-analyses of various studies on SARS-CoV-2, but also on influenza, RSV and tuberculosis to be carried out on different questions. It was set up jointly by the HZI, UKK and RKI via the DZIF and the NUM project COVIM and collects individual participant data from population-based seroprevalence studies in Germany. The data can be made available anonymously to other academic researchers.
Within the Network for University Medicine, we are responsible as work package leaders in NUM-COVIM 1.0 and 2.0 for population immunity, in NUM-IMMUNEBRIDGE for data pooling and analysis, and contribute evidence synthesis and expertise as partners in NUM-CoverChild and NUM-Prepared.
Heinsohn, T., Lange, B., Vanella, P., Rodiah, I., Glöckner, S., Joachim, A., Becker, D., Brändle, T., Dhein, S., Ehehalt, S., Fries, M., Galante-Gottschalk, A., Jehnichen, S., Kolkmann, S., Kossow, A., Hellmich, M., Dötsch, J., & Krause, G. (2022b). Infection and transmission risks of COVID-19 in schools and their contribution to population infections in Germany: A retrospective observational study using nationwide and regional health and education agency notification data. PLoS Med, 19(12), e1003913. https://doi.org/10.1371/journal.pmed.1003913
Rodiah, I., Vanella, P., Kuhlmann, A., Jaeger, V. K., Harries, M., Krause, G., Karch, A., Bock, W., & Lange, B. (2023). Age-specific contribution of contacts to transmission of SARS-CoV-2 in Germany. Eur J Epidemiol. https://doi.org/10.1007/s10654-022-00938-6
Fricke, L. M., Glockner, S., Dreier, M., & Lange, B. (2021). Impact of non-pharmaceutical interventions targeted at COVID-19 pandemic on influenza burden - a systematic review. J Infect, 82(1), 1-35. https://doi.org/10.1016/j.jinf.2020.11.039
Gornyk, D., Harries, M., Glöckner, S., Strengert, M., T., K., Bojara, G., Castell, S., Frank, K., Gubbe, K., Heise, J.-K., Hernandez, P., Kappert, O., Kern, W., Illig, T., Klopp, N., Maaß, H., Ortmann, J., Barbora Kessel, B., Roller, G., . . . Krause, G. (2021). SARS-CoV-2 seroprevalence in Germany - A population based sequential study in seven regions. Deutsches Ärzteblatt Int, 118: 824.https://doi.org/10.3238/arztebl.m2021.0364
Rishi K. Gupta, Claire J. Calderwood, Alexei Yavlinsky, Maria Krutikov, Matteo Quartagno, Maximilian C. Aichelburg (…),Berit Lange (…) Ibrahim Abubakar; Discovery and validation of a personalised risk predictor for incident tuberculosis in settings aiming towards pre-elimination (PERISKOPE-TB), Nature Medicine, 2020 , doi.org10.1038/s41591-020-1076-0
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