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Ohio State

Growing Pains: Large-scale disease surveillance data challenges and solutions

Dillon McBride, Graduate Research Assistant & PhD Candidate Animal Influenza Ecology & Epidemiology Research Program (AIEERP) at The Ohio State University

Leading up to and through the COVID-19 pandemic, our lab group grew substantially in the scope of work and overall volume. We began to see additional complex study designs on our horizon — human cohorts, additional wildlife species for surveillance, and increased testing capacity for SARS-CoV-2 in addition to influenza made it clear we needed a new and comprehensive data-keeping solution. The flexibility among sample and source types allows us to keep all of our different projects in one place and utilize a hierarchical structure that accurately reflects the clustering and source dynamics of our sampling schemes. Since starting with Sample Manager, we have also been able to slowly utilize more functionalities including assay types and storage organization, and in the future, we have plans to begin using workflows and the integrated ELN to make our actual hands-on work in the lab run more smoothly.

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