Scientific Computing Core

High-Performance Computing (HPC)

Where2Test

Where2Test online platform on COVID19 pandemic analysis.  During the COVID19 pandemic CASUS developed and ran the Where2Test platform. It combined data collection about COVID infections with demographics as well as prediction and simulation of hypothetical scenarios. For this purpose it employed High-Performance Computing (HPC), epidemiological modelling, control theory, and numeric optimization. In addition to traditional scientific papers, the CASUS effort has produced several web applications that made the HPC forecasts available to general public, and provided useful tools for dealing with the practical aspects of life under pandemic such as workplace risk calculator, optimizer for office occupancy, or testing strategy optimizer for medical care facilities.

Optimisation of the local and temporal distribution of tests for SARS-CoV-2 based on “what-if” scenarios for different test strategies (Where2Test).

Funding:
Saxon Ministry for Research, Culture and Tourism, Corona Fund of the Free State of Saxony

Period: 01.08.2020 to 31.12.2022

The overall objective of the project is to develop a software for the spatial, temporal and strategic optimisation of the use of tests from Coronavirus SARS-CoV-2. Extensive testing, in addition to the development of therapies or a vaccine and intensive contact tracing, is an important basis for the control and, if necessary, containment of infections and thus a viable way out of the so-called lockdown.

The project aims to determine an optimal spatial and temporal distribution of these test capacities on the basis of an existing test strategy and assuming limited test capacities. The optimisation will be based on different test strategies such as the combination of tests with close contact tracking, the use of test pooling or the use of new, fast test procedures. The aim of optimisation will be to achieve the most comprehensive possible recording of infection figures. The openness of the planned solution will allow for adaptation to the further course of the pandemic as well as its spread to future pandemics. A link to space- and time-dependent epidemiological models will also allow the modelling of “what-if” scenarios.

Partner:
Integrated SARS-CoV-2 waste water monitoring project – Prof. Teutsch, Helmholtz Centre for Environmental Research (UFZ)

Prof. Dr Justin Calabrese

Dr Jiří Vyskočil

Dr Weronika Schlechte-Wełnicz

This project is financed by the Saxon State government out of the State budget approved by the Saxon State Parliament.

Software