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Research Project: Predicting and Mitigating Vesicular Stomatitis Virus (VSV) Outbreaks in North America

Location: Foreign Arthropod Borne Animal Disease Research

Project Number: 3022-32000-062-000-D
Project Type: In-House Appropriated

Start Date: Oct 25, 2021
End Date: Oct 24, 2026

Objective 1: Ascertain the viral ecology and factors mediating the introduction and expansion of VSV in the U.S. Objective 1A. Identify viral genetic determinants mediating emergence of epidemic VSV in the U.S. as well as adaptation to insect and animal hosts. Objective 1B. Characterize epidemiological, biotic and abiotic factors associated with vectorial capacity, emergence, incursion, and expansion of VSV from endemic areas into the U.S. Objective 2. Develop intervention strategies to minimize the impact of VSV disease outbreaks. Objective 2A. Retrospectively integrate and harmonize environmental, vector, host, and viral variables with disease occurrence data to support the development of predictive multi-scale big data models for VSV. Objective 2B. Develop model-based early warning systems to predict future incursions of VSV from Mexico to the U.S. Objective 2C. Identify vector transmission control strategies based on our understanding of virus-vector-host interactions.

Objective 1A:The effect of genetic changes on virulence and transmissibility will be investigated with three approaches: 1) investigating virulence in pigs and vector transmissibility in relevant vectors (e.g., midges and black flies); 2) characterizing genomes of the 2019-2020 VSIV U.S. epidemic strains using comparative genomics to identify genetic differences between epidemic and endemic VSIV in Mexico. 3) if different endemic vs. epidemic lineages are identified, then characterize the virulence of these strains. Objective 1B. We will quantify the occurrence of VS cases across space and time in the endemic region in Mexico. Together these data will enable us to quantify the occurrence of VS cases across space and time in the endemic region. If successful, we expect to identify associations between VS cases and environmental/ecological factors. We will employ the big data model integration (BDMI) approach used previously by our VSV-GC collaborators. Objective 2A: Temporal relationships between VS occurrences and variables representing environmental factors relevant to VS transmission will be evaluated. First, municipality level VS occurrence data from 1981 – 2020 provided by SENASICA will be temporally binned based on incursion years into the U.S.: 1985, 1995, 2004, 2012, or 2019. Next, collated datasets representing environmental, ecological and/or biological factors relevant VS occurrences across Mexico for each year identified from Goal 1B.1 will be synchronized with the SENASICA dataset. Initially, time-series analysis of VS occurrence within temporal bins across geographic space will be performed. This analysis will help determine whether VS occurrence and spread outside of the endemic region occurs randomly or non-randomly in space and time prior to incursion in the U.S. We will then test whether identified factors reliably predict incursions to the U.S. using multivariate analyses and, if appropriate, machine learning as previously described. Analyses may reveal genomic markers of virulence to inform surveillance in Mexico and early warning programs. If successful, we expect to identify a reliable set of environmental/ecological/biological variables that can be used to inform early warning metrics in predictive modeling of VSV incursion. Objective 2B: We hypothesize that VSV infection will alter photosensory perception, altering the effectiveness of current phototaxis-dependent surveillance traps and management strategies. If successful, we will determine the effects of VSV infection on midge photoattraction behavior and on the expression of vision or other neurosensory genes.