ABSTRACT
PURPOSE OF REVIEW: To examine the impacts of gun violence on early childhood development including early childhood mental health, cognitive development, and the assessment and treatment of survivors. RECENT FINDINGS: The literature reflects that gun violence exposure is often associated with significant mental health outcomes including anxiety, post-traumatic stress, and depression in older youth. Historically, studies have focused on adolescents and their exposures to gun violence through proximity to gun violence within their communities, neighborhoods, and schools. However, the impacts of gun violence on young children are less known. Gun violence has significant impacts on mental health outcomes of youth aged 0-18. Few studies focus specifically on how gun violence impacts early childhood development. In light of the increase in youth gun violence over the past three decades with a significant uptick since the onset of the COVID-19 pandemic, continued efforts are needed to better understand how gun violence impacts early childhood development.
Subject(s)
COVID-19 , Exposure to Violence , Firearms , Gun Violence , Child , Adolescent , Humans , Child, Preschool , Aged , Gun Violence/prevention & control , Pandemics , Exposure to Violence/psychology , Mental HealthABSTRACT
BACKGROUND: Like most of the world, the United States' public health and economy are impacted by the COVID19 pandemic. However, discrete pandemic effects may not be fully realized on the macro-scale. With this perspective, our goal is to visualize spread of the pandemic and measure county-level features which may portend vulnerability. METHODS: We accessed the New York Times GitHub repository COVID19 data and 2018 United States Census data for all United States Counties. The disparate datasets were merged and filtered to allow for visualization and assessments about case fatality rate (CFR%) and associated demographic, ethnic and economic features. RESULTS: Our results suggest that county-level COVID19 fatality rates are related to advanced population age (P < .001) and less diversity as evidenced by higher proportion of Caucasians in High CFR% counties (P < .001). Also, lower CFR% counties had a greater proportion of the population reporting has having 2 or more races (P < .001). We noted no significant differences between High and Low CFR% counties with respect to mean income or poverty rate. CONCLUSIONS: Unique COVID19 impacts are realized at the county level. Use of public datasets, data science skills and information visualization can yield helpful insights to drive understanding about community-level vulnerability.