North American AIDS Cohorts Collaboration on Research and Design (NAACCORD) Renewal

The North American - AIDS Cohort Collaboration on Research and Design (NA-ACCORD) is a collaboration of >20 academic and community-based prospective HIV research cohorts from the United States and Canada. It is the largest collaboration of HIV cohorts in North America and has been shown to be representative of the US HIV epidemic (according to CDC HIV Surveillance reports). Urgent COVID-19 questions can be answered by NA-ACCORD co-investigators using: 1) existing data in large-scale cohorts of people with (PWH) and without HIV (PWOH); and 2) newly established cohorts of people who have been tested for SARS-Cov-2 (regardless of the test result), which are enrolling participants every day. NA-ACCORD investigators will work collaboratively to share data collection instruments, algorithms for identifying COVID-19 disease, and analytic approaches to expedite answers to urgent questions in multiple data sources and understand the heterogeneity in findings. To answer urgent COVID-19 questions, this supplement will support: 1) assembling a team of experienced infectious disease epidemiologists and clinicians versed in longitudinal study design who are focused on answering urgent COVID-19 and understand heterogeneity in findings resulting from the same question being answered in different cohorts 2) the foundational steps to establishing 3 longitudinal COVID-19 clinical cohorts using EHR data 3) data management and analytic expertise specific to the profound health impacts of infectious disease using data from clinical (i.e. primarily EHR data) and interval cohort studies 4) establishing a library of COVID-19 surveys, person under investigation (PUI) forms, and other documentation forms from existing cohort studies, and providing a RedCap-based survey to NAACCORD cohorts in anticipation of future collaborative research 5) the development and sharing of EHR-based algorithms for COVID-19 and facilitating engagement with other groups working on common data models for COVID-19