With the ongoing corona pandemic, it is important to convey information about the spread of the disease in a simple and accessible way. A common way to do this is through visualizations. This work makes an attempt to shed light on how visualizations on maps can be improved by creating a prototype that takes into account established design principles and also suggests a way to display data from different prediction models for future development of the disease spread.

Relevant research shows that there are many articles that present new models for predicting the development of covid-19, however, visualizations that present these are often very simple and difficult to compare with each other. Therefore, this work creates a prototype that could take in and present data from different prediction models on an interactive map.

During the work, the Design Science Research Method has been used as a basis for the research process. The process is based on a number of different research methods and is well proven for this type of work. The method also provides enough flexibility so that the problem formulation could change during the process, which has been necessary for this work.

The prototype that the work resulted in is a web application written with the Javascript library React. The prototype uses a number of different external libraries for, for example, rendering of data storage and the map itself. The data presented in the prototype comes from the public health authority and is pre-processed in a Python script to be used by the web application.

The prototype was first intended to be able to take in and present various actual prediction models as part of the visualization. However, this has not been possible due to limitations in the amount of data used and the technical complexity of implementing an epidemiological model in a short time.Instead, the work provides a suggestion on how these models could be integrated into applications such as the one proposed here.