Subprojects

The basis for the development of LOKI and its underlying models and forecasts is data. Subproject 1 (SP1) is concerned with the collection and preparation of data from a variety of sources for use in the subsequent subprojects. The aim is to integrate multiple data sources into a data pool for models and forecasts in a structured and readily usable manner. This includes data collection, structuring and primary analysis. Furthermore, SP1 will analyze the potential to integrate new data sources, either publicly available or through collaborations, and assess and address issues of data protection.

A major constraint in assessment and prediction of epidemic dynamics are data availability, quality, and provenance. Integrating a variety of independent data sources, their standardization, and the automation of their processing, are essential for downstream statistical analyses and more precise forecasting. Quality control mechanisms to ensure high accuracy of data and metadata with minimal manual curation will be established. At the same time, data will be aggregated, combined, and converted to standardized formats to secure a reliable and predictable data source for automated workflows.

For forecasting, epidemiological models have to be calibrated. However, reliable estimation of model parameters from insufficient data is often impossible. With increasing levels of model detail, this issue becomes more severe. Data-derived model parameters provide valuable detail and constraints, and their incorporation improves the reliability of the predictions.

Primary data sources include aggregated public surveillance data, case-based data from health authorities, data on clinical and hospitalization-related parameters (in collaboration with the Lean European Open Survey on SARS-CoV-2 [LEOSS] project, a prospective European multi-center cohort study), population-based studies and seroprevalence surveys (https://serohub.net/en/, https://hzi-c19-antikoerperstudie.de/).

Furthermore, SP1 aims to integrate existing data on vaccinations, wastewater samples, contact networks, mobility, and aerosol dynamics.

Lastly, SP1 will conduct evidence synthesis on existing literature to integrate previous estimates of parameters. Evidence synthesis will be focused on SARS-CoV-2 in the first stage and will later integrate ongoing work (https://respinow.de/) on other respiratory pathogens.

This data and synthesized evidence on model parameters will be provided in a structured manner to downstream work packages and is directly used in pattern recognition approaches, mechanistic models and enters model calibration and uncertainty analysis. To promote synergies with existing efforts internationally, SP1 will aim to include and compare the current platform in an umbrella review of similar global efforts in building up modelling and forecasting platforms for public health agency use.

Several aspects of the study deal with sensitive data. For the collected data, SP1 will analyze their potential to breach privacy and investigate inference threats. Equally, SP1 will ensure that the products of data analysis or machine learning algorithms will not leak private data and are also not susceptible to inference attacks. Where necessary, SP1 will employ and develop local mechanisms that aggregate data and coarsen the analysis to improve privacy protection for individuals.

The aggregation of a variety of data sources will provide a detailed picture of the pandemic and its parameter and will allow for previously unseen precision of forecasting in a thought-out, part-automated manner accessible to public health workers and other relevant professionals.

The aim is to integrate multiple data sources into a data pool for models and forecasts in a structured and readily usable manner (for use in subsequent subprojects).

Dr. Berit Lange - Helmholtz Centre for Infection Research

Subproject 2 (SP2) "Models and Analysis" deals with the development of models that are intended to represent the real spread of infectious diseases and provides methods for parameter estimation, uncertainty quantification and optimization. Parameter estimation attempts to draw conclusions about the true values of various parameters (e.g., the number of daily contacts). Uncertainty quantification can be used to calculate how likely certain results are if certain aspects of the model are not fully known or are fuzzy or subject to variation. The optimization tool calculates the optimal combination for a predefined goal as well as the optimal timing of non-pharmaceutical measures from a given set. 

Overall, different types of models are used. The first class of models ranges from classical SIR-type models based on ordinary differential equations to models involving integro-differential equations and coupled regional or metapopulation models. In addition, LOKI-Pandemics will provide agent-based models as well as models based on classical statistics and machine learning. To explore infection dynamics, these models will be used either independently or with methods for parameter estimation and optimization. To ensure that the models can be used for future epidemiologically relevant outbreaks, the scientists in SP2 will also establish a workflow for calibrating and integrating real-time data into the models. All models will be developed under a permissive open source license and published within our simulation backend MEmilio (https://github.com/DLR-SC/memilio).

SP2 will provide retrospective analyses of the Sars-CoV-2 pandemic to draw conclusions from past outbreak developments. These inferences will help increase the depth of infectious disease spread models or, if needed, develop new models for potential future respiratory viral disease outbreaks. In addition, retrospective analyses will help to evaluate the impact of regionally adopted non-pharmaceutical measures, such as those implemented in Germany, in order to use these findings for future outbreak containment.

All models will be implemented efficiently and in a modular fashion so that they can provide real-time results in the form of visualizations of the further evolution of an outbreak event and can be easily interchangeable in the near future as newer models are developed. Regionally resolved models can also be used to incorporate regional aspects of disease spread or control. SP2 will also allow simulation of scenarios with and without non-pharmaceutical interventions. This will allow to present the impact of these interventions on the incidence of infections or hospitalizations. Taking into account uncertainty quantification, the results will help to evaluate outbreak events and support the decision to introduce non-pharmaceutical measures and optimize them in reality. Numerical optimization methods, among others, are used to recommend adapted measures.

The workflow of SP2 will be designed to be as general as possible, so that transfer to new pathogens will help to reduce the costs of preparing for new pandemics. The lessons learned from Sars-CoV-2 in the subproject will thus enable decision-makers and the German population to be better prepared for potentially upcoming pandemics.

The objective of SP2 is to provide modular and efficiently implemented models for the spread of infectious diseases as well as methods for parameter estimation, uncertainty quantification and optimization. In addition, a workflow that is as automatic and as general as possible will be created to enable the computations of different scenarios of infectious disease spread.

Dr. Martin Joachim Kühn - German Aerospace Center

Subproject 3 (SP3) comprises the technical implementation and realization of the platform. The modular components developed in SP2 will be combined into a common platform. This plattform is based on a cloud-based infrastructure with direct connection to a supercomputer for computationally intensive operations and access to large storage capacity. In addition to the computation of user-driven simulation scenarios, visualization and visual analytics methods are an essential aspect of the LOKI-pandemics platform.

Therefore, the centre of the platform is the web application with interactive components that visualizes and provides easy access to the model results. The collected data and the results of data analyses, simulations and forecasts are communicated to the target audience in a pragmatic and understandable way.

By combining visualization with interaction and automated algorithms, the web application supports decision makers in evaluating possible policy measures. The algorithms simplify the classification of complex phenomena and the detection of new patterns in the data. Diagrams and graphs can be displayed in detail and modified interactively.

Seamless integration with existing systems is critical for a realistic, cost- and time-efficient introduction of the platform and adaptation to targeted user groups. A special interface will allow other systems to gain access to the platform's key results and aggregated and simulated data to facilitate the reuse of the algorithms and data in other systems. Furthermore, in the opposite direction, it will allow the use and technical integration of additional data sources.

Information security aspects are an integral part of the overall platform to ensure that sensitive data is analysed while maintaining privacy. Solutions will be defined primarily by technical and legal considerations, which will require collaboration with legal experts and will affect the design of the platform's security architecture. Because the platform will provide various forms of access to potentially sensitive data, it is critical to develop novel security architectures that can balance data use with privacy and security considerations.

The ambitious goal of an integrated platform for different methods of data analysis, data storage and user interaction requires modularity and flexibility in the software architecture. Only then will the generated platform serve pandemic control beyond the project lifetime and be generalizable to different respiratory infections.

The goal of SP3 is the technical implementation and realization of the platform by developing the web application for the users. From here, user-controlled simulation scenarios can be triggered and results can be visualized and analysed. Interfaces for the integration of the platform into existing systems, the coupling to external data sources and a high demand on information security make the platform open and flexible to use.

Jens Henrik Göbbert - Forschungszentrum Jülich GmbH, Jülich Supercomputing Centre

Subproject 4 (SP4) is responsible for transferring the platform into practice. This means that employees of this subproject form the interface between the developers of the platform and the cooperating health authorities. The main focus is on coordinating the communication between the development and the application of LOKI-Pandemics. For the exchange between users and developers, regular web conferences are held with employees of the cooperating pilot health authorities. These meetings will also allow for networking among participants. Individual virtual meetings, as well as telephone and written support, will be provided as needed.

By involving users in the development process of the platform, valuable experience and suggestions from the field will be used to adapt the web application to the individual needs of health authorities.

After the introduction of the platform, employees of SP4 will train and advise the responsible employees of the pilot health authorities. The trainings will be offered in different formats, e.g. face-to-face trainings, webinars or e-learning units. Furthermore, training materials will be developed and made available to the pilot health authorities.

Another task of SP4 is to evaluate the platform. The aim is to demonstrate the benefits and quality of the application for daily practice. The employees can use the user feedback to evaluate and optimize the platform.

The aforementioned tasks of the subproject are supplemented by the provision of user support to enable personal exchange with the pilot health authorities and to rapidly clarify open questions. Through telephone support, the employees of SP4 are regularly available for questions, ideas and suggestions.

The aim of SP4 is to transfer the LOKI-pandemics platform into practical use in pilot health authorities. The experiences of the users and the local needs in the health authorities will be taken into account by SP4 for the development of an application-friendly and practice-oriented platform. With the customized application, health authorities should be able to test, evaluate and effectively use measures for local control of an infection event. Regular training, individual user support and coordination of exchange forums will support health authorities in dealing with local epidemic outbreaks.

Dr. Sybille Somogyi – Academy of Public Health Services