While it is estimated that 15% of couples worldwide are infertile, this figure hinges critically on the quality, inclusiveness and availability of infertility data sources. Current infertility data and statistics fail to account for the infertility experiences of some social groups. We identify these people as the invisible infertile, and refer to their omission from infertility data and statistics-whether intentional or unintentional-as the process of invisibilization. We identify two processes through which invisibilization in survey data is produced: sampling, with focus on exclusionary definitions of the population at-risk, and survey instrument design, with focus on skip patterns and question wording. Illustrative examples of these processes are drawn from the Integrated Fertility Survey Series and the Demographic and Health Surveys. Empirical research is not designed in an objective vacuum. Rather, survey instruments and sampling techniques are shaped and influenced by the sociocultural norms and geopolitical context of the time and place in which they are created and conducted, reflecting broader social beliefs about family building and reproduction. Furthermore, population policy singularly aimed at curbing overpopulation in high fertility parts of the world limits the type of reproduction data collected, effectively rendering the infertility of some groups epidemiologically unfathomable. In light of these sociocultural and geopolitical forces, many marginalized groups are missing from reproductive health (RH) statistics. The omission of entire groups from the scientific discourse casts doubt on the quality of research questions, validity of the analytic tools, and accuracy of scientific findings. Invisibility may also misguide evidence-based RH and family planning policies and deter equitable access to reproductive healthcare for some social groups, perpetuating social inequalities.
