Wyoming Department of Agriculture

Abstract Background Hepatitis C virus (HCV) infection in the Philippines has a prevalence of < 1% and is much less common than Hepatitis B, which has a nationwide prevalence of 10-17%. HCV genotyping is only done sporadically, usually during outbreak investigations, and there is limited surveillance data in literature. Most local HCV infection has been reported among people who inject drugs (PWID), with a co-infection rate of up to 70% among those PWID with HIV. Our central laboratory at the University of the Philippines National Institutes of Health (UP-NIH) is one of a few facilities nationwide that routinely performs HCV genotyping. We report our experience since we started HCV genotyping in 2017 until 2025 to better understand the evolving local molecular epidemiology of HCV.Figure 1.Phylogenetic analysis of HCV genotypes from UP-NIH from 2017 to 2025. Methods De-identified HCV-positive clinical plasma samples collected from 2017-2025 and banked at the UP-NIH Central Laboratory were included in the study. This study was exempted from ethical review by the University of the Philippines Manila - Research Ethics Board since no identifying data was collected. The core region (360 bp) was amplified using nested PCR and amplicons underwent capillary sequencing. Sequence quality control and multiple sequence alignment of all sample consensus sequences with representative sequences of major HCV genotypes from the GenBank database were performed using MEGA 7.0. The maximum likelihood tree was constructed with GTR+F+I+G4 model and 1000 bootstrap replicates using IQ-TREE. Results A total of 82 samples were analyzed during the study period. Table 1 shows the overall genotype distribution and breakdown across different years. Figure 1 shows the phylogenetic analysis among representative genotypes.Table 1.HCV genotype distribution from 2017 to 2025 at the UP-NIH Central Laboratory.YearHCV GenotypeTotal per year1a1b2a2b3a4a620178102011132018144441002720191200101115202020000002202150000005202231000004202390000009202430000003202540000004Total (%)60647122N=82 Conclusion Genotype 1a remains the most prevalent HCV genotype in the Philippines, with no other HCV genotypes other than 1b reported since 2020. This may reflect the increasing uptake of curative treatment globally with the resultant loss in diversity. Disclosures All Authors: No reported disclosures

Infectious diseases pose a significant threat to global health and biodiversity. Yet, predicting the spatiotemporal dynamics of wildlife epizootics remains challenging. Disease outbreaks result from complex nonlinear interactions among a large collection of variables that rarely adhere to the assumptions of parametric regression modeling. We adopted a nonparametric machine learning approach to model wildlife epizootics and population recovery, using the disease system of colonial black-tailed prairie dogs (BTPD, Cynomys ludovicianus) and sylvatic plague as an example. We synthesized colony data between 2001 and 2020 from eight USDA Forest Service National Grasslands across the range of BTPDs in central North America. We then modeled extinctions due to plague and colony recovery of BTPDs in relation to complex interactions among climate, topoedaphic variables, colony characteristics, and disease history. Extinctions due to plague occurred more frequently when BTPD colonies were spatially clustered, in closer proximity to colonies decimated by plague during the previous year, following cooler than average temperatures the previous summer, and when wetter winter/springs were preceded by drier summers/falls. Rigorous cross-validations and spatial predictions indicated that our final models predicted plague outbreaks and colony recovery in BTPD with high accuracy (e.g., AUC generally >0.80). Thus, these spatially explicit models can reliably predict the spatial and temporal dynamics of wildlife epizootics and subsequent population recovery in a highly complex host-pathogen system. Our models can be used to support strategic management planning (e.g., plague mitigation) to optimize benefits of this keystone species to associated wildlife communities and ecosystem functioning. This optimization can reduce conflicts among different landowners and resource managers, as well as economic losses to the ranching industry. More broadly, our big data-model integration approach provides a general framework for spatially explicit forecasting of disease-induced population fluctuations for use in natural resource management decision-making.

Abstract Vesicular stomatitis (VS) is an arthropod‐borne viral disease that negatively impacts domestic livestock and wildlife hosts, and economically impacts both private animal owners and the commercial livestock industry. Previous phylogenetic studies, based on partial P gene sequences, suggested that outbreak cycles of the virus (VSV) exhibit a two‐phase dynamic (i.e., incursion and expansion). A single viral lineage from endemic areas of Mexico introduced into the southern United States during an incursion year (2004), can overwinter, and then expand throughout the western United States during the subsequent spring and summer seasons (2005). Our objective was to build on this past research using full‐length viral genomic sequences from Mexico and the United States from the same outbreak, and a large suite of geospatial data to identify the environmental factors that influence VSV evolution in the United States and potentially drive the incursion–expansion dynamics. Our phylogeographic analysis confirmed that a single VS New Jersey virus (VSNJV) lineage initiated the 2004 incursion year outbreak was subject to decreasing genetic divergence during the 2004–2006 outbreak cycle, and likely overwintered between the 2004–2006 outbreak seasons. However, rather than a simple geographic relationship, viral genetic sublineages or patristic groups identified as part of our study, were found to be associated with seasonally varying evaporative demand, soil moisture, and precipitation. Our results suggest a functional role for these environmental factors in shaping the evolution and ecology of VSNJV. We speculate a nexus to insect‐vector switching and possible adaptation to local environmental conditions to help explain the observed incursion–expansion dynamic in the United States in the 2004–2006 outbreak. Our approach of linking the phylogeography of a virus with the ecology of insect vectors can be applied to other vector‐borne diseases.

Abstract Productivity throughout the North American Great Plains grasslands is generally considered to be water limited, with the strength of this limitation increasing as precipitation decreases. We hypothesize that cumulative actual evapotranspiration water loss (AET) from April to July is the precipitation‐related variable most correlated to aboveground net primary production (ANPP) in the U.S. Great Plains (GP). We tested this by evaluating the relationship ofANPPtoAET, precipitation, and plant transpiration (Tr). We used multi‐yearANPPdata from five sites ranging from semiarid grasslands in Colorado and Wyoming to mesic grasslands in Nebraska and Kansas, mean annualNRCS ANPP, and satellite‐derived normalized difference vegetation index (NDVI) data. Results from the five sites showed that cumulative April‐to‐JulyAET, precipitation, and Tr were well correlated (R2: 0.54–0.70) to annual changes inANPPfor all but the wettest site.AETand Tr were better correlated to annual changes inANPPcompared to precipitation for the drier sites, and precipitation in August and September had little impact on productivity in drier sites. April‐to‐July cumulative precipitation was best correlated (R2 = 0.63) with interannual variability inANPPin the most mesic site, whileAETand Tr were poorly correlated withANPPat this site. Cumulative growing season (May‐to‐September)NDVI(iNDVI) was strongly correlated with annualANPPat the five sites (R2 = 0.90). UsingiNDVIas a surrogate forANPP, we found that county‐level cumulative April–JulyAETwas more strongly correlated toANPPthan precipitation for more than 80% of theGPcounties, with precipitation tending to perform better in the eastern more mesic portion of theGP. Including the ratio ofAETto potential evapotranspiration (PET) improved the correlation ofAETto bothiNDVIand mean county‐levelNRCS ANPP. Accounting for how different precipitation‐related variables controlANPP(AETin drier portion, precipitation in wetter portion) provides opportunity to develop spatially explicit forecasting ofANPPacross theGPfor enhancing decision‐making by land managers and use of grasslandANPPfor biofuels.

Salix sectionCordatae subsectionLuteae includes 10 taxa and occurs in most of North America. The taxa are here treated as four species, one with six varieties and another with two varieties. Six new combinations are proposed underSalix eriocephala.

Sociocultural factors effect the learning of deaf and hard-of-hearing (deaf/hh) children. Knowledge and sensitivity to children's home culture can assist the teacher in planning effective lessons. A three year project funded by the U.S. Department of Education is described which prepared 15 teachers of deaf/hh children in southeastern Kentucky. It is suggested that teacher-preparation programs include information on the sociocultural context of the communities where its graduates will work. The needs of preservice teachers for southeast Kentucky are conceptualized into four components: (a) Appalachian history, culture, and language; (b) deafness and learning strategies; (c) deaf culture and American Sign Language; and d) main-streaming competencies. Self-reports by the 15 trainees on their progress in the program are presented along with evaluations of teaching performance by their school supervisors.