@article{Ryan:2026:gigascience/giag020,
author = {Ryan, SJ and Huxley, PJ and Lippi, CA and Pawar, S and Cator, L and Rund, SSC and Johnson, LR},
doi = {gigascience/giag020},
journal = {Gigascience},
title = {MIReVTD, a Minimum Information Standard for Reporting Vector Trait Data.},
url = {http://dx.doi.org/10.1093/gigascience/giag020},
year = {2026}
}

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TY  - JOUR
AB  - 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 for assessing risk and predicting 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 prohibit analytical comprehensiveness. Here, we present MIReVTD, a Minimum Information standard for Reporting Vector Trait Data. Our reporting checklist balances completeness and labor intensity to make 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 an Aedes aegypti mosquito study.
AU  - Ryan,SJ
AU  - Huxley,PJ
AU  - Lippi,CA
AU  - Pawar,S
AU  - Cator,L
AU  - Rund,SSC
AU  - Johnson,LR
DO  - gigascience/giag020
PY  - 2026///
TI  - MIReVTD, a Minimum Information Standard for Reporting Vector Trait Data.
T2  - Gigascience
UR  - http://dx.doi.org/10.1093/gigascience/giag020
UR  - https://www.ncbi.nlm.nih.gov/pubmed/41762157
ER  - 

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