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Research Project: Intervention Strategies to Support the Global Control and Eradication of Foot-and-Mouth Disease Virus (FMDV)

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Title: Ecological and Anthropogenic Spatial Gradients Shape Patterns of Dispersal of Foot-and-Mouth Disease Virus

Author
item MUNSEY, ANNA - University Of Minnesota
item MWIINE, FRANK - Makerere University
item OCHWO, SYLVESTER - Makerere University
item VELAZQUEZ SALINAS, LAURO - University Of Mississippi
item AHMED, ZAHEER - Animal And Plant Health Inspection Service (APHIS)
item Rodriguez, Luis
item Rieder, Aida - Elizabeth
item PEREZ, ANDRES - University Of Minnesota
item VANDERWAALL, KIMBERLY - University Of Minnesota

Submitted to: Viruses
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/27/2022
Publication Date: 4/29/2022
Citation: Munsey, A., Mwiine, F., Ochwo, S., Velazquez Salinas, L., Ahmed, Z., Rodriguez, L.L., Rieder, A.E., Perez, A., Vanderwaall, K. 2022. Ecological and Anthropogenic Spatial Gradients Shape Patterns of Dispersal of Foot-and-Mouth Disease Virus. Viruses. https://doi.org/10.3390/pathogens11050524.
DOI: https://doi.org/10.3390/pathogens11050524

Interpretive Summary: Although foot-and-mouth disease (FMD) has been eradicated in most developed countries, the disease continues to have substantial impacts in developing countries. In this study Ugandan foot-and-mouth disease virus (FMDV) genetic information fwere examined for the development of novel tools for epidemiological purposes.

Technical Abstract: Despite its substantial impact on animal health and economics, the epidemiology of foot and mouth disease virus (FMDV) in endemic settings remains poorly understood. Concordant with the increasing availability of pathogen genetic sequence data, there is a growing need for tools to test epidemiological hypotheses. In this study we utilize novel regression tools to elucidate the epidemiology of foot and mouth disease virus in Uganda. We analyze FMDV serotype O genetic sequences and their corresponding spatiotemporal metadata from a cross-sectional study of cattle. We apply step selection function (SSF) models, traditionally used to study wildlife habitat selection, to viral phylogenies to show that FMDV is more likely to be found in areas of low rainfall. Next, we developed a novel tool, the resource gradient function (RGF) model, to elucidate characteristics of viral source and sink areas. An RGF model applied to our data reveals areas of high cattle density and areas near livestock markets may serve as sources of FMDV dissemination in Uganda, and areas of low rainfall serve as viral sinks that experience frequent reintroductions. The application of these regression tools to viral phylogenies may help researchers better understand spatiotemporal heterogeneities in risk for FMDV in other areas as well as for other diseases.