when are rational expectations a threat to causal inference? Consider the impact government policy has had on deaths from COVID19.  I think the potential relationships are 

If the relationships are as given in the above diagram, and I regress covid deaths at t+1 on policy at t-1, is the ONLY threat to causal inference that policy maker's rational expectations of covid deaths at t+1 is affecting policy choice at t-1?  Specifically, do I not need to worry about the bi-direction of the relationship between policy and the epidemic because the relationship between the epidemic and covid deaths is one directional and government policy affects covid deaths only indirectly via the epidemic? 
I think it is fairly safe to assume that: 
1) policy does not affect covid deaths directly, but only through its impact on the epidemic.
2) the epidemic causes covid deaths, but not vice versa.
3) the relationship between policy and epidemic runs both ways.
4) nations choose their own policies and experience their own epidemic. 
nb: I am investigating 5 measures of government policy aggregated to the national level, but for clarity referred to them as "policy"  
 A: I think I would add another node for policy at $t+1,$ so as not to violate the fundamental law of cause and effect (causes must precede effects). Let $E(t)$ be the epidemic at $t,$ $D(t)$ be COVID deaths at $t,$ and $G(t)$ be government policy at $t.$ The real question is whether we will allow modeling (accurate or not) to affect government policy. I think we should, since that's obviously happening. So I would propose this alteration to your model:

So this is saying that government policy at $t+1$ has inertia (arrow $G(t-1)\to G(t+1)$), and that modeling of the epidemic (as well as actual data) and the deaths affect government policy at $t+1.$ COVID deaths are only immediately affected by the epidemic, as you said.
I would caution you that the effect of government policy on the epidemic is hotly contested, and is (inherently) a highly political topic. 
But I'm very excited that you're thinking to apply causal diagrams to this incredibly important question! I've been wanting someone to do this, because we need clarity of thought!
