A minimum data standard for wildlife disease research and surveillance

Tess Stevens, Ryan Zimmerman, Greg Albery, Daniel J Becker , Rebekah Kading, Carl N. Keiser, Shashank Khandelwal, Stephanie Kramer-Schadt, Raphael Krut-Landau, Clifton McKee, Diego Montecino-Latorre, Zoe O'Donoghue, Sarah H Olson, Timothée Poisot , Hailey Robertson, Sadie Jane Ryan, Stephanie Seifert, David Simons, Amanda Vicente-Santos, Chelsea Wood, Ellie Graeden, Colin J Carlson 

Rapid and comprehensive data sharing is vital to the transparency and actionability of wildlife infectious disease research and surveillance. Unfortunately, most best practices for publicly sharing these data are focused on pathogen determination and genetic sequence data. Other facets of wildlife disease data – particularly negative results – are often withheld or, at best, summarized in a descriptive table with limited metadata. Here, we propose a minimum data and metadata reporting standard for wildlife disease studies. Our data standard identifies a set of 40 data fields (9 required) and 24 metadata fields (7 required) sufficient to standardize and document a dataset consisting of records disaggregated to the finest possible spatial, temporal, and taxonomic scale. We illustrate how this standard is applied to an example study, which documented a novel alphacoronavirus found in bats in Belize. Finally, we outline best practices for how data should be formatted for optimal re-use, and how researchers can navigate potential safety concerns around data sharing.