Table 2 Current challenges in pandemic and epidemic intelligence
From: How better pandemic and epidemic intelligence will prepare the world for future threats
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 |
