ORIGINAL RESEARCH article
Front. Vet. Sci.
Sec. Veterinary Epidemiology and Economics
Bayesian Spatiotemporal Evaluation of Bovine Anaplasmosis Seroprevalence in Missouri (2010-2021)
Provisionally accepted
- 1University of Missouri, Columbia, United States
- 2University of Twente, Enschede, Netherlands
Select one of your emails
You have multiple emails registered with Frontiers:
Notify me on publication
Please enter your email address:
If you already have an account, please login
You don't have a Frontiers account ? You can register here
Bovine anaplasmosis, caused by the rickettsia Anaplasma marginale, is an economically important and globally distributed tick-and blood-borne disease of cattle. Although cases are known to be widespread in Missouri, current spatiotemporal trends, presence of high-risk areas, and any potential drivers for disease trends in Missouri are poorly documentednot readily evident. To address these knowledge gaps, this study analyzed spatiotemporal patterns of annual, county-level anaplasmosis case counts using a Bayesian hierarchical framework. Seropositive cCases of anaplasmosis detected at the University of Missouri Veterinary Medical Diagnostic Laboratory (n = 1,944) between the years 2010-2021 were used to construct data-driven Bayesian hierarchical models. All the models consisted of imputation sub-models to alleviate issues related to missing observations from spatiotemporal units (114 counties and 1 independent city, 12 years). Three progressively complex models with different assumptions for capturing the spatial, temporal, and spatiotemporal interactions that explained the variability in case counts were prepared. Model-1 included linear predictors decomposed into structured and unstructured terms for the temporal and spatial processes. Model-2 included separate temporal terms for smoothing each spatial entity and spatial smoothing terms for each temporal entity. This model was extended in Model-3, which included space-time interaction effect using first-order conditional autoregressive (CAR) priors. Based on the Deviance Information Criterion (DIC), Models 3 was superior at explaining space/time variability in the detected seropositive cases of bovine anaplasmosis. These findings indicate that distribution and risk of bovine anaplasmosis seroprevalence in Missouri are non-uniform, and potentially driven by environmental and/or management factors, operating at local and regional scales, that when identified could inform mitigation strategies.
Keywords: Anaplasma marginale, Bayesian spatiotemporal analysis, Bovine anaplasmosis, Imputation model, Missingness
Received: 02 Jul 2025; Accepted: 15 Dec 2025.
Copyright: © 2025 Raghavan, Ierardi, Osei and Zhang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Ram Raghavan
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.