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As Peru is subject to large seismic movements owing to its geographic condition, determining seismic risk levels is a priority task for designing appropriate management plans. These actions become especially relevant when analyzing Pisco, a Peruvian city which has been heavily affected by various seismic events through the years. Hence, this project aims at estimating the associated seismic risk level and its previous requirements, such as hazard and vulnerability. To this end, a hybrid approach of machine learning (i.e., Random Forest) and hierarchical analysis (i.e., the Saaty matrix) was used. Risk levels were calculated through a double-entry table that establishes the relation between hazard and vulnerability levels. Results suggest that the city of Pisco exhibits both medium (lower city areas) and high (higher city areas) hazard levels in similar proportion. In addition, the coast area is considered a very-high hazard zone. Regarding vulnerability, the central area of the city exhibits a medium vulnerability level, whereas the periphery denotes high and very-high vulnerability levels. The interrelation of these components results in overall high-risk levels, with very-high levels in some central areas of the city. Finally, the results from this research study are expected to be useful for the authorities in charge of fostering specific activities in each sector and, simultaneously, as a motivator for future studies within this field.

OBJECTIVES/GOALS: In the United States, oropharyngeal cancer (OPC) is the leading human papilloma-virus (HPV) related malignancy, and OPC rates are increasing among the US veteran population. The purpose of this study is to identify demographic and regional factors that may be associated with low HPV-vaccination rates among the US veteran population. METHODS/STUDY POPULATION: This study will use Veterans Health Administration (VHA) administrative data to create a national cross-sectional cohort of veterans ages 18-45 with a VHA primary care visit from 2018-2020. HPV-vaccination status of each subject (initiation of vaccination series, completion of vaccination regimen, and age vaccinated) will be determined. Differences in the prevalence of HPV-vaccination by smoking status, geographic location, socioeconomic status, race/ethnicity, and rural-urban context will be examined in the unadjusted analysis. Factors associated with low HPV-vaccination rates in the VHA will be identified using multivariable logistic regression to model no (vs any) HPV-vaccination, no completion (vs completion) of HPV-vaccination recommendations, and non-routine (vs routine) HPV-vaccination: RESULTS/ANTICIPATED RESULTS: In 2019, HPV-vaccination guidelines were expanded to include some adults between the ages of 26-45, making many young veterans in the VHA eligible for vaccination. From this study’s recently generated dataset, more than 1.2 million subjects (n=1,219,896) met the study inclusion criteria. Extrapolating from trends in the civilian population, it is anticipated that HPV-vaccination rates will be lower among African Americans compared to non-Hispanic Caucasian Americans, within the South Central and Southeastern regions of the US, and in rural communities. This study will define a veteran’s geographic location by their associated Veteran Affairs Integrated Service Network (or VISN), which are groups responsible for healthcare planning and resource allocation in particular regions of the US: DISCUSSION/SIGNIFICANCE: Identifying factors associated with low HPV-vaccination rates within the VHA will be the first step to reducing future incidence of HPV-related cancer burden among US veterans. Assessing geographic variability in vaccination rates by VISNs will create the potential to generate targeted interventions within an existing VHA framework.