# Smart Statistics Software Helps Health Departments Make Everyday Decisions

BMBF Project Ester – Decision Support for Public Health Authorities Using Risk Modeling to Combat Pandemics

Health departments continue to face significant challenges in containing the SARS-CoV-2 pandemic. Among other things, decisions on quarantine orders have to be made on a daily basis, not infrequently affecting entire school classes or other groups. Therefore, together with our partners in the EsteR – Decision Support for Public Health Departments project, we are looking at how we can support these decisions using statistical modeling. In collaboration with the associated health departments, we have identified various issues that are useful for their daily work. We provide statistical analyses to support these questions in the form of an app.

The project is funded for one year by the Federal Ministry of Education and Research (BMBF) within the framework of the announcement »Prevention and Care of Epidemically Occurring Infections with Innovative Medical Technology«. It is a follow-up project to CorASiv and we as Fraunhofer ITWM are project coordinator.

#### Innovation and Application: What Is Innovative About Our Solution?

Many software applications have been developed during the pandemic, but they rarely provide support for individual contact events. Existing software mostly aims only at the registration and administration of contact persons, further statistical evaluations increasingly serve strategic analyses. The goal of our project is to implement complex statistical-epidemiological facts about concrete infection situations in an easy-to-use and understandable software environment. In doing so, we directly address the everyday work of the employees in the public health department.

#### Example: How Can We Use Negative Test Results to Perform a Risk Assessment for Group Quarantine Requirements?

A common decision-making situation in health departments is as follows: An infected person was part of a group event – for example, a sick child attends class. Quarantine is ordered for the whole group. However, no infections become known, i.e., no child in the school class shows symptoms and all those tested show a negative test. What is the probability that the group did become infected?

A statistical model was developed for the probability of infection when only negative tests are given in a group. For this purpose, after specifying group size, contact date and test date, it is determined how high the probability is that despite contact with an infected person, only negative tests have been performed so far. Including further modeling of the a priori probability that an infection occurred at all during the contact event, this is used to determine an a posteriori probability that no one other than the index person in the group is actually infected. The probability calculated in this way can be used as a supporting argument in shortening quarantine periods.

#### Example: Has an Infection Occurred in the Group?

Here, the software determines whether the distribution of symptoms within the group statistically matches an infection at the time of the meeting. Only the group data are entered, such as

• Group size
• Time of the meeting
• Person information
• Onset of symptoms

The answer is then displayed in the app, while calculations of a statistical test (more precisely chi-square test) ran in the background. In addition, the software visually illustrates what a worst-case scenario might look like for the expected further contagions.

#### Provision of the Research Results

The developed methods are currently available in the form of a Demonstrator App. At the end of the project, a release of the statistical computing kernel in the form of an open source R package is planned.

#### Project Duration

The project is scheduled for one year and runs from 01.07.2021 to 30.06.2022.

#### Fraunhofer ITWM versus Corona

The project is funded by the German Federal Ministry of Education and Research (BMBF) on the Federal Gazette of 03.08.2020 »Prevention and Care of Epidemically Occurring Infections With Innovative Medical Technology«.