The evolution of a disease in a large population is a function of the top-down policy measures from a centralized planner and the self-interested decisions (to be socially active) of individual agents in a large heterogeneous population. This paper is concerned with understanding the latter based on a mean-field type optimal control model. Specifically, the model is used to investigate the role of partial information on an agent's decision-making and study the impact of such decisions by a large number of agents on the spread of the virus in the population. The motivation comes from the presymptomatic and asymptomatic spread of the COVID-19 virus, where an agent unwittingly spreads the virus. We show that even in a setting with fully rational agents, limited information on the viral state can result in epidemic growth.