An important goal of surveillance is to inform public health interventions that aim to reduce the burden of disease in the population. Ensuring accuracy of results is paramount to achieving this goal. However, science is currently facing a reproducibility crisis where researchers have found it difficult or impossible to reproduce study results. Organized and well-documented statistical source code that is publicly available could increase research reproducibility, especially for research relying on publicly available surveillance data like the BRFSS, NHANES, GSS, SEER, and others. As part of our overall goal to improve training around reproducible research practices, we surveyed public health data analysts to determine current practices and barriers to code sharing.
Objective: Our presentation will explain current use, and barriers to use, of reproducible research practices in public health. We will also introduce a set of modules for researchers wishing to increase their use of reproducible research practices.