Continually arriving information is communicated through a network of $n$
agents, with the value of information to the $j$'th recipient being a
decreasing function of $j/n$, and communication costs paid by recipient.
Regardless of details of network and communication costs, the social optimum
policy is to communicate arbitrarily slowly. But selfish agent behavior leads
to Nash equilibria which (in the $n \to \infty$ limit) may be efficient (Nash
payoff $=$ social optimum payoff) or wasteful ($0 < $ Nash payoff $<$ social
optimum payoff) or totally wasteful (Nash payoff $=0$). We study the cases of
the complete network (constant communication costs between all agents), the
grid with only nearest-neighbor communication, and the grid with communication
cost a function of distance. The main technical tool is analysis of the
associated first passage percolation process or SI epidemic (representing
spread of one item of information) and in particular its "window width", the
time interval during which most agents learn the item. Many arguments are just
outlined, not intended as complete rigorous proofs.