We evaluated blood collected on Nobuto filter-paper (FP) strips for use in detecting Brucella spp. antibodies in caribou. Whole blood (for serum) and blood-saturated FP strips were obtained from 185 killed arctic caribou (Rangifer tarandus groenlandicus). Sample pairs (serum and FP eluates) were simultaneously tested in duplicate using competitive enzyme-linked immunosorbent assay (c-ELISA) and indirect ELISA (i-ELISA) for Brucella spp. Prior work based on isolation of Brucella spp. revealed sensitivity (SE) and specificity (SP) of 100% and 99%, respectively, for both these serum assays in caribou. Infection status of the animals in the current study was unknown but recent sampling had revealed clinical brucellosis and >40% Brucella antibody prevalence in the herd. To assess the performance of FP relative to serum in these assays, serum was used as the putative gold standard. On both assays, the findings for duplicate runs (A and B) were similar. For c-ELISA run A, the FP Brucella prevalence (47%) was lower than serum prevalence (52%), with SE 89% (95% confidence interval [CI]: 82–95%) and SP 99% (97–100%). For i-ELISA run A, serum and FP Brucella prevalence rates were identical (43%), and the SE and SP of FP testing were 100% and 99% (97–100%), respectively. The findings suggest better FP test performance with i-ELISA than with c-ELISA; however, i-ELISA does not distinguish cross-reacting antibodies induced by Brucella vaccination or exposure to certain other Gram-negative pathogens. Results for duplicate FP eluates (prepared using separate FP strips from each animal) were strongly correlated for both protocols (r=0.996 and 0.999 for c-ELISA and i-ELISA, respectively), indicating minimal variability among FPs from any individual caribou. Dried caribou FP blood samples stored for 2 mo at room temperature are comparable with serum for use in Brucella spp. c-ELISA and i-ELISA. Hunter-based FP sampling can facilitate detection of disease exposure in remote regions and under adverse conditions, and can expand wildlife disease surveillance across temporospatial scales.