Masking is a statistical issue by which true signals of disproportionate reporting are hidden by the presence of other products in the database. It is a phenomenon often observed when external factors, such as solicited schemes of reporting of adverse drug reactions or media attention, affect the reporting dynamics leading to a relative increase in the reporting rate for a specific medicinal product. As the change in reporting dynamics can be restricted in time and location, masking is not fully understood, but can be highly impactful if the reporting dynamics change dramatically over a long period and across multiple countries, such as seen in the COVID-19 world-wide vaccination campaigns.
Publications have described methods assessing the extent and impact of the masking effect of measures of disproportionality. They include A conceptual approach to the masking effect of measures of disproportionality (Pharmacoepidemiol Drug Saf. 2014;23(2):208-17), with an application described in Assessing the extent and impact of the masking effect of disproportionality analyses on two spontaneous reporting systems databases (Pharmacoepidemiol Drug Saf. 2014;23(2):195-207), Outlier removal to uncover patterns in adverse drug reaction surveillance - a simple unmasking strategy (Pharmacoepidemiol Drug Saf. 2013;22(10):1119-29) and A potential event-competition bias in safety signal detection: results from a spontaneous reporting research database in France (Drug Saf. 2013;36(7):565-72). The value of these methods in practice needs to be further investigated.