9 Appendix/ Supplementary material for the paper: Causal analysis of Covid-19 spread in Germany 9.1 Results of causal analysis on federal level for all four combinations of thresholds for SyPI

Figure 5: Detected causal paths of the spread of Covid-19 among the federal German states, including causes among the restriction measures taken by each federal state. Each colour (in arrows and policies) indicates causes of one state (see top legend). The four subfigures correspond to the four combinations of threshold 1 and 2 that we tested. A distribution P is faithful to a directed acyclic graph (DAG) G if no conditional independence relations other than the ones entailed by the Markov property are present. Let G be a causal graph with vertex set V and P be a probability distribution over the vertices in V generated by the causal structure represented by G. G and P satisfy the Causal Markov Condition if and only if for every W in V, W is independent of V \ (Descendants(W) Parents(W)) given Parents(W).