Projects Infectious Disease Epidemiology

Projects Infectious Disease Epidemiology

Developing differential serology as adaptive diagnostic tools to provide relevant epidemiological indicators in epidemiological studies

Adaptive diagnostic and serological assays are important to allow reliable large-scale population-based research for the effective management of infectious diseases. As a platform technology, multiplex-based immunoassays allow profiling of polyclonal antibody responses towards different antigens, the analysis of humoral cross-reactivity between related pathogen species as a potential source of pre-existing cross-protection, to monitor pathogen variants or to differentiate vaccine from infection-induced antibodies to define vaccine efficiency or to define the role of antibody responses in disease progression. The joint development of MULTICOV-AB and RBDCoV-2 to analyze antibody binding and surrogate neutralization after SARS-CoV-2 infection and vaccination has well demonstrated how multiplex-based immunoassays can serve as platform technology. To date, both assays have been used to screen more than 100.000 samples collected in a wide variety of scientific contexts ranging from work that examines antibody responses in household transmission studies [1], characterizes humoral immunity after infections with emerging variants of concern [2, 3] or to define vaccination responses both within the general population and in immunocompromised at risk populations for severe COVID-19 [4-7].

Analysing burden of disease and infection sequelae in longterm population and clinical cohorts with digital tools

The CRC study centre run by the Department of Epidemiology at the HZI provides a perfect infrastructure to conduct large epidemiological studies. This is one study site of the largest population-based cohorts in Germany, NAKO,  and MuSPAD. Also, here we conduct further clinical and population-based studies, such as the RESIST senior cohort  [8] . We also provide capacity for data management, quality and analysis of large epidemiological studies, such as the largest clinical transplant cohort in Europe, the DZIF transplant cohort. [9]
These studies provide us with a perfect infrastructure as well as data and biosample resource to conduct detailed epidemiological analyses, including on OMICs data, to better understand infectious disease burden in the population and improve clinical management of infectious diseases. For example as part of a DFG-funded initiative we will assess organ cross talk of human microbiota and its role for health and disease using NAKO data. We are also using these data to understand changed dynamics of different infectious diseases due to the climate crisis. [10]
With the project ZIFCO, since 2019, we have developed and implemented a digital study infrastructure called PIA that successfully collects provides data on transient infections. We are now expanding this in the European project PCR4All for further cohort studies and pathogens  to understand the use of mass testing strategies in epidemics and methodologically develop our epidemiological cohorts further. 

Assessing and predicting infection dynamics in adaptive epidemics panels and modelling platforms

To be fast and adaptable to any emerging pathogen we set up a large adaptive panel that is able to quickly start surveys, including the build-up of flexible study centres and continuously provide relevant results - MuSPAD. Here we use the diagnostic tools developed above and where their fast deployment and potential large scale-up are highly relevant.[4, 11] Eg, in 2022 with this epidemic panel we sampled for four pathogens, with a preparation time of 2 months in collaboration with other large population-based studies [12, 13] .
We are leading a modelling consortium (RESPINOW), where we assess non-pharmaceutical interventions on their effect on dynamics and burden of respiratory infections like RSV, influenza and pneumococci and we build integrated multi-pathogen models, using data of our adaptive panel. We further take part as partner in the BMBF-funded consortium OPTIM-Agent in building a framework for pandemic-related decision makers, work on models for different scenarios regarding critical infrastructures in Europe with SUNRISE, are engaged in developing an early warning system for epidemics in Germany with LOKI-pandemics, and work on agent-based models to enhance the planning of the architecture of intensive care units for an infectious disease control perspective.[4, 11, 14, 15]

 

Publications

  1. Renk, H., et al., Robust and durable serological response following pediatric SARS-CoV-2 infection. Nat Commun, 2022. 13(1): p. 128.
  2. Becker, M., et al., Immune response to SARS-CoV-2 variants of concern in vaccinated individuals. Nat Commun, 2021. 12(1): p. 3109.
  3. Junker, D., et al., Antibody Binding and Angiotensin-Converting Enzyme 2 Binding Inhibition Is Significant Reduced for Both the BA.1 and BA.2 Omicron Variants. Clin Infect Dis, 2023. 76(3): p. e240-e249.
  4. Dulovic, A., et al., Comparative Magnitude and Persistence of Humoral SARS-CoV-2 Vaccination Responses in the Adult Population in Germany. Front Immunol, 2022. 13: p. 828053.
  5. Strengert, M., et al., Cellular and humoral immunogenicity of a SARS-CoV-2 mRNA vaccine in patients on haemodialysis. EBioMedicine, 2021. 70: p. 103524.
  6. Becker, M., et al., Longitudinal cellular and humoral immune responses after triple BNT162b2 and fourth full-dose mRNA-1273 vaccination in haemodialysis patients. Front Immunol, 2022. 13: p. 1004045.
  7. Dulovic, A., et al., Diminishing Immune Responses against Variants of Concern in Dialysis Patients 4 Months after SARS-CoV-2 mRNA Vaccination. Zeitschrift Emerging Infectious Disease, 2022. 28(4).
  8. Peters, A., et al., Framework and baseline examination of the German National Cohort (NAKO). Eur J Epidemiol, 2022. 37(10): p. 1107-1124.
  9. Karch, A., et al., The transplant cohort of the German center for infection research (DZIF Tx-Cohort): study design and baseline characteristics. Eur J Epidemiol, 2021. 36(2): p. 233-241.
  10. Lotto, M., et al., TOWARDS A LEPTOSPIROSIS EARLY WARNING SYSTEM IN NORTH- EASTERN ARGENTINA. International Journal of Infectious Diseases, 2023. 130: p. S155.
  11. Gornyk, D., et al., SARS-CoV-2 Seroprevalence in Germany. Dtsch Arztebl Int, 2021. 118(48): p. 824-831.
  12. Harries, M., et al., Bridging the gap - estimation of 2022/2023 SARS-CoV-2 healthcare burden in Germany based on multidimensional data from a rapid epidemic panel. medRxiv, 2022: p. 2022.12.30.22284061.
  13. Lange, B., et al., A case series of severe breakthrough infections observed in nine patients with COVID-19 in a southwestern German university hospital. Infection, 2022. 50(3): p. 775-782.
  14. Heinsohn, T., et al., Infektions- und Übertragungsrisiken von COVID-19 in Schulen und ihr Beitrag zu Infektionen der Bevölkerung in Deutschland: Eine retrospektive Beobachtungsstudie unter Verwendung von bundesweiten und regionalen Meldedaten der Gesundheits- und Bildungsbehörden. PLoS Med, 2022. 19(12): p. e1003913.
  15. Rodiah, I., et al., Age-specific contribution of contacts to transmission of SARS-CoV-2 in Germany. Eur J Epidemiol, 2023. 38(1): p. 39-58.