Requirements and design of the PROSPER protocol for implementation of information infrastructures supporting pandemic response: a Nominal Group study

Background

Advanced technical systems and analytic methods promise to provide policymakers with information to help them recognize the consequences ofalternative courses of action during pandemics. Evaluations still show thatresponse programs are insufficiently supported by information systems. Thispaper sets out to derive a protocol for implementation of integratedinformation infrastructures supporting regional and local pandemic responseprograms at the stage(s) when the outbreak no longer can be contained at itssource.

Methods

Nominal group methods for reaching consensus on complex problems were used totransform requirements data obtained from international experts into animplementation protocol. The analysis was performed in a cyclical process inwhich the experts first individually provided input to working documents andthen discussed them in conferences calls. Argument-based representation indesign patterns was used to define the protocol at technical, system, andpandemic evidence levels.

Results

The Protocol for a Standardized information infrastructure for Pandemic andEmerging infectious disease Response (PROSPER) outlines the implementationof information infrastructure aligned with pandemic response programs. Theprotocol covers analyses of the community at risk, the response processes,and response impacts. For each of these, the protocol outlines theimplementation of a supporting information infrastructure in hierarchicalpatterns ranging from technical components and system functions to pandemicevidence production.

Conclusions

The PROSPER protocol provides guidelines for implementation of an informationinfrastructure for pandemic response programs both in settings wheresophisticated health information systems already are used and in developingcommunities where there is limited access to financial and technicalresources. The protocol is based on a generic health service model and itsfunctions are adjusted for community-level analyses of outbreak detectionand progress, and response program effectiveness. Scientifically groundedreporting principles need to be established for interpretation ofinformation derived from outbreak detection algorithms and predictivemodeling.