Nonresponse is a challenge in many fields, including demography, economics, public health, sociology, and business. This chapter explores nonpolitical manifestations of nonignorable nonresponse by focusing on population health. For many conditions, the decision to get tested or the willingness to allow a test is deeply wrapped up in the likelihood of having the condition. During Covid, for example, people who thought they might have been exposed to the virus were almost certainly more likely to get tested meaning that nonignorable nonresponse complicated our ability to understand the Covid outbreak. Section 13.1 discusses the challenge of estimating public health variables in terms of a nonignorable missing data problem. Section 13.2 explores how first-stage instruments can improve the efficiency and accuracy of efforts to assess prevalence. Section 13.3 presents a framework for comparing Covid positivity rates across regions even when testing rates differ.