  During an epidemic, the information available to individuals in the society
deeply influences their belief of the epidemic spread, and consequently the
preventive measures they take to stay safe from the infection. In this paper,
we develop a scalable framework for ascertaining the optimal information
disclosure a government must make to individuals in a networked society for the
purpose of epidemic containment. This problem of information design problem is
complicated by the heterogeneous nature of the society, the positive
externalities faced by individuals, and the variety in the public response to
such disclosures. We use a networked public goods model to capture the
underlying societal structure. Our first main result is a structural
decomposition of the government's objectives into two independent components --
a component dependent on the utility function of individuals, and another
dependent on properties of the underlying network. Since the network dependent
term in this decomposition is unaffected by the signals sent by the government,
this characterization simplifies the problem of finding the optimal information
disclosure policies. We find explicit conditions, in terms of the risk aversion
and prudence, under which no disclosure, full disclosure, exaggeration and
downplay are the optimal policies. The structural decomposition results are
also helpful in studying other forms of interventions like incentive design and
network design.
