Sauermann, S., Kanjala, C., Templ, M., Austin, C. C., & RDA COVID-19 WG. (2020). Preservation of individuals’ privacy in shared COVID-19 related data. Social Science Research Network (SSRN). https://doi.org/10.2139/ssrn.3648430
Statistical Disclosure Control; Anonymization; Pharmacology (medical); Covid19 data
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Abstract:
This paper gives insight into the pseudo-anonymization and anonymization of COVID-19 data sets. First, methods for the pseudo-anonymization of direct identification variables are discussed. We also discuss different pseudo-IDs of the same person for multi-domain and multi-organization. Essentially, pseudo- anonymization and its encrypted IDs are used to successfully match data later if required and permitted, as well as to restore the true ID (and authenticity) in individual cases of a patient's clarification.
To make the re-identification of individual persons of COVID-19 (that are often enriched with other covariates like age, gender, nationality, etc.) impossible, the successful re-identification by a combination of attribute values must be prevented. This is done with methods of statistical disclosure control for anonymization of data.
