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Abstract Vector-borne diseases pose a persistent and increasing challenge to human, animal, and agricultural systems globally. Mathematical modeling frameworks incorporating vector trait responses are powerful tools to assess risk and predict vector-borne disease impacts. Developing these frameworks and the reliability of their predictions hinge on the availability of experimentally derived vector trait data for model parameterization and inference of the biological mechanisms underpinning transmission. Trait experiments have generated data for many known and potential vector species, but the terminology used across studies is inconsistent, and accompanying publications may share data with insufficient detail for reuse or synthesis. The lack of data standardization can lead to information loss and prohibits analytical comprehensiveness. Here, we present MIReVTD, a Minimum Information standard for Reporting Vector Trait Data. Our reporting checklist balances completeness and labor- intensiveness with the goal of making these important experimental data easier to find and reuse, without onerous effort for scientists generating the data. To illustrate the standard, we provide an example reproducing results from anAedes aegyptimosquito study. 

VecTraits is a searchable database of hundreds of datasets on the traits of vectors (or potential vectors) of human, plant, and animal diseases. It includes a user-friendly GUI interface that provides simple visualizations of datasets to facilitate exploration of the data as well as an API to enable direct downloading of user selected datasets. VecTraits is hosted by the University of Notre Dame Center for Research Computing, and is being developed and maintained as part of the NSF funded VectorByte Initiative (www.vectorbyte.org).