Fig 1.
PRISMA-ScR flow diagram of study selection for the global scoping review of Brucella exposure and infection in wild canids (1962–2025).
Table 1.
Study-level brucellosis prevalence in wild canids worldwide (1962–2025).
Fig 2.
Global true seroprevalence and model calibration.
(a) Posterior distribution of the misclassification-adjusted hierarchical Bayesian model for global Brucella seroprevalence in wild canids; the vertical line marks the posterior median. (b) Study-level calibration (observed vs. predicted) aligns with the 1:1 line, indicating good model fit. Chains converged (R̂ ≈ 1.00; no divergences), and posterior predictive checks reproduced the empirical distribution. (c) Sensitivity of pooled true seroprevalence to modeling choices (baseline, Trim-K, robust priors, robust + Trim-K). Influence trimming lowers estimates, while robust priors raise them; the combined model yields a stable mid-range (~22%). (d) Forest plot showing observed (×) versus misclassification-adjusted (●) prevalence with 95% confidence intervals (CIs) by diagnostic test. Marked heterogeneity is evident, with older, lower-specificity assays producing higher apparent prevalence, while PCR/culture arms remain low.
Fig 3.
True seroprevalence of brucellosis in Asian wild canids.
(a) Posterior distribution from the misclassification-adjusted hierarchical Bayesian model; the dashed line marks the posterior median (≈4.6%, 95% CrI 4.0–5.5%). (b) Posterior predictive check comparing replicated (blue) and observed (black) prevalence distributions. The model reproduces the central mass of the empirical data but slightly under-captures the tails, indicating an overall adequate though imperfect fit. Sparse data—driven mainly by one golden-jackal series—limit precision and highlight the need for additional wild sampling in Asia.
Fig 4.
Very low pooled prevalence with localized outliers in Europe.
(a) Posterior of true seroprevalence in Europe, with a median of ≈1.6% (95% CrI 1.3–1.9%). (b) Observed (×) versus misclassification-adjusted (●) prevalence by study. Most species are near zero; a few red-fox datasets drive the right-tail, reflecting local outliers rather than widespread exposure.
Fig 5.
Pooled true seroprevalence and study-level estimates in North America.
(a) Posterior distribution from the misclassification-adjusted hierarchical model; median true seroprevalence ≈10.0% (95% CrI 7.0–13.0%). The unimodal and moderately narrow posterior indicates intermediate exposure relative to other continents and good model pooling across studies. (b) Study-level apparent (×) and adjusted (●) prevalence with 95% CIs, labeled by diagnostic test. Coyote and red-fox series contribute most of the signal; older SAT/RBT assays tend to report higher apparent values, while adjusted estimates cluster lower, reflecting diagnostic-driven heterogeneity.
Fig 6.
Elevated true seroprevalence and diagnostic variability in South America.
(a) Posterior distribution from the misclassification-adjusted hierarchical model; median ≈21.5% (95% CrI ~ 18–26.5%). The unimodal, moderately tight posterior indicates consistently higher exposure than in North America or Europe. (b) Study-level apparent (×) and adjusted (●) prevalence with 95% CIs, labeled by diagnostic test. Crab-eating fox and culpeo series dominate the signal; SAT/RBT assays tend to overestimate compared to confirmatory tests. (c) Posterior predictive check for observed positives across study arms. Simulated (blue) distributions closely envelop empirical counts (black), and the posterior predictive mean (dashed) tracks the data, indicating good model fit.
Fig 7.
Geographic clustering of seropositivity and assay-driven differences.
(a) For identical populations, bars show apparent seroprevalence (95% CIs); asterisks (*) denote significant differences. Screening assays (RBT, CARD, BPAT) consistently yield higher positivity than confirmatory tests (CFT, ELISA), underscoring diagnostic misclassification and the need for confirmatory validation. (B) Choropleth map of the total number of animals tested, aggregated by country across included studies (blue = lower totals; red = higher totals; grey = no data). (C) Choropleth map of apparent seroprevalence by country from serological studies (seropositive/total tested; blue = lower; red = higher; grey = no data). (D) Choropleth map of confirmed infection by country based on PCR and/or culture (blue = lower; red = higher; grey = no data). Maps were created in R using public-domain basemap shapefiles from Natural Earth (https://www.naturalearthdata.com).