Data Sharing in a Decentralized Public Health System: Lessons From COVID-19 Syndromic Surveillance

Abstract

The COVID-19 pandemic revealed that data sharing challenges persist across public health information systems. We examine the specific challenges in sharing syndromic surveillance data between state, local, and federal partners. These challenges are complicated by US federalism, which decentralizes public health response and creates friction between different government units. The current policies restrict federal access to state and local syndromic surveillance data without each jurisdiction's consent. These policies frustrate legitimate federal governmental interests and are contrary to ethical guidelines for public health data sharing. Nevertheless, state and local public health agencies must continue to play a central role as there are important risks in interpreting syndromic surveillance data without understanding local contexts. Policies establishing a collaborative framework will be needed to support data sharing between federal, state, and local partners. A collaborative framework would be enhanced by a governance group with robust state and local involvement and policy guardrails to ensure the use of data is appropriate. These policy and relational challenges must be addressed to actualize a truly national public health information system.

Keywords: COVID-19; COVID-19 pandemic; SARS-CoV-2; United States; collaborative framework; data sharing; decentralized; digital health; digital technology; ethical guidelines; federalism; health data; health information; health policy; infodemiology; information system; innovation; public health; risk score; surveillance; syndromic surveillance; technology.