A minimum data standard for wildlife disease studies

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 

Thousands of scientists and practitioners conduct research on infectious diseases of wildlife. Rapid and comprehensive data sharing is vital to the transparency and actionability of their work, but unfortunately, most efforts designed to publically share these data are focused on pathogen determination and genetic sequence data. Other facets of existing surveillance data – particularly negative results – are often withheld or, at best, summarized in a descriptive table with limited metadata. As a result, very few datasets on wildlife disease dynamics over space and time are publicly available for synthesis research or applied uses in conservation or public health. Here, we propose a minimum data and metadata reporting standard for wildlife disease studies. Our checklist identifies a minimum set of 30 fields required 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.