The RECODID project will develop an quitable, acessible, and sustainable model for the storage, curation, and analyses of clinical-epidemiological and high-dimensional sample data collected by infectious disease cohorts in low-and-midle-income countries (LMIC). To ensure that data generators in LMIC participate in and benefit from personalized medicine-based approached to ID research and response, the RECODID team complete the following objectives:
Identify and address the political, ethical, administrative, regulatory, and legal (PEARL) barriers and solutions related to combining, analyzing and sharing a range of datatypes and specimens across infectious disease cohorts.
Develop and implement a roadmap, tools and analytic methods to reconcile, analyse and link "high density laboratory" data with synthesized clinical-epidemiological metadata from objective 2.
Develop and implement a roadmap, tools and analytical methods to reconcile, analyze and link human clinical, epidemiological, and diagnostic laboratory data within and across infectious disease cohorts.
Develop a local governance model and searchable portal for decentralized cataloguing of data repositories and biobanks.