I study the economic effects of testing during the outbreak of a novel disease. I propose a model where testing permits isolation of the infected and provides agents with information about the prevalence and lethality of the disease. Additional testing reduces the perceived lethality of the disease, but might increase the perceived risk of infection. As a result, more testing could increase the perceived risk of dying from the disease - i.e. "stoke fear" - and cause a fall in economic activity, despite improving health outcomes. Two main insights emerge. First, increased testing is beneficial to the economy and pays for itself if performed at a sufficiently large scale, but not necessarily otherwise. Second, heterogeneous risk perceptions across age-groups can have important aggregate consequences. For a SARS-CoV-2 calibration of the model, heterogeneous risk perceptions across young and old individuals mitigate GDP losses by 50% and reduce the death toll by 30% relative to a scenario in which all individuals have the same perceptions of risk.