Table 2.

Current challenges in pandemic and epidemic intelligence

Challenge	Potential solution(s)
Data fragmentation	New taxonomies and ontologies are needed to enable diverse data to be connected directly or through federated data models
Difficulty accessing sources	New digital technologies can facilitate the analysis of data remotely, in whatever form they reside, while data custodians retain full control of their data
Licensing, ownership	Novel licensing and access models could make data insights available from copyrighted information when used for public-health and global-good purposes
Cyber security risks	Cyber security measures need to be strengthened for all public health surveillance systems and need to be incorporated into designs for interconnected data systems
Analysis challenges	Automation and artificial intelligence approaches can improve capacities to analyze large volumes of different data types
Increased computing requirements	Analyzing large quantities of highly complex data will require access to distributed computing services for public health institutions
Risk assessments will include more determining factors	Tools will be needed to assist human analysts in considering many determinants of risk, both quantitative and qualitative
Organizational challenges	Public health institutions will need to be organized to facilitate institution-wide inclusion in intelligence functions and the creation of intelligence teams
Requirement for a highly trained team with diverse specialties	An intelligence workforce will require topic-specific experts in human and animal health, social and behavioral sciences, environmental sciences and data science, among others