# In this tutorial we demonstrate how one can use TKRISK to analyze vaccine response to COVID-19. We create a simple model of contamination and show how vaccine and exposition can jointly affect the probability of being infected.

We review with this example the logic and applicability of Bayesian networks. We are able to closely match the analytical solution thanks to efficient sampling methods including low discrepancy sequences. This is the first of a three parts demo.

# In this tutorial we demonstrate how one can use TKRISK to analyze vaccine response to COVID-19. We create a simple model of contamination and show how vaccine and exposition can jointly affect the probability of being infected.

We review with this example the logic and applicability of Bayesian networks. We are able to closely match the analytical solution thanks to efficient sampling methods including low discrepancy sequences. This is the first of a three parts demo.

## TKRISK EXAMPLES

TKRISK can be used in a large spectrum of applications. We demonstrate the application through a series of case studies.

###### CARBON SEQUESTRATION & STORAGE

Through this example, we demonstrate how one can build a COVID contamination model from basic assumptions. We can then use this model to explore various scenarios of vaccination and their impact on the average health care cost associated in the US.

We develop a model that characterizes the main risks associated with Carbon Sequestration in geological formations.

The injected CO2 needs pore space for storage. Is the storage site fit to store a given amount of CO2. What land area needs to be covered?

How far does the plume of CO2 travel away from the injection well? How quickly does the front move?

Injection triggers pressure increase in the reservoir. How does that pressure increase with time and how far does it reach?

Calibrated models can be used for decision support. the Inference module of TKRISK unlocks powerful capabilities such as evidence propagation and value of information