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1.
Health Educ Behav ; 49(1): 11-16, 2022 02.
Article in English | MEDLINE | ID: mdl-34730051

ABSTRACT

Social and health inequities among communities of color are deeply embedded in the United States and were exacerbated by the COVID-19 pandemic. Community-based participatory research (CBPR) is a powerful approach to advance health equity. However, emergencies both as global as a pandemic or as local as a forest fire have the power to interrupt research programs and weaken community relationships. Drawing from Public Health Critical Race Praxis (PHCRP), as well as our research experience during the pandemic, this article proposes an expansion of prior CBPR principles with an emphasis on advocacy and storytelling, community investment, and flexibility. The article summarizes key principles of CBPR and PHCRP, contextualizes their relevance in COVID-19, and outlines a practical vision for crisis-resilient research through deeper engagement with antiracism scholarship. Structural barriers remain an issue, so policy changes to funding and research institutions are recommended, as well, to truly advance health equity.


Subject(s)
COVID-19 , Health Equity , Community-Based Participatory Research , Humans , Pandemics , SARS-CoV-2 , United States/epidemiology
2.
J Healthc Inform Res ; 5(2): 218-229, 2021.
Article in English | MEDLINE | ID: mdl-33969258

ABSTRACT

Anticipating the number of hospital beds needed for patients with COVID-19 remains a challenge. Early efforts to predict hospital bed needs focused on deriving predictions from SIR models, largely at the level of countries, provinces, or states. In the USA, these models rely on data reported by state health agencies. However, predicting disease and hospitalization dynamics at the state level is complicated by geographic variation in disease parameters. In addition, it is difficult to make forecasts early in a pandemic due to minimal data. Bayesian approaches that allow models to be specified with informed prior information from areas that have already completed a disease curve can serve as prior estimates for areas that are beginning their curve. Here, a Bayesian non-linear regression (Weibull function) was used to forecast cumulative and active COVID-19 hospitalizations for SD, USA, based on data available up to 2020-07-22. As expected, early forecasts were dominated by prior information, which was derived from New York City. Importantly, hospitalization trends differed within South Dakota due to early peaks in an urban area, followed by later peaks in rural areas of the state. Combining these trends led to altered forecasts with relevant policy implications. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s41666-021-00094-8.

3.
J Infect Dis ; 222(Suppl 5): S312-S321, 2020 09 02.
Article in English | MEDLINE | ID: mdl-32877549

ABSTRACT

BACKGROUND: Key indicators of vulnerability for the syndemic of opioid overdose, human immunodeficiency virus (HIV), and hepatitis C virus (HCV) due to injection drug use (IDU) in rural reservation and frontier counties are unknown. We examined county-level vulnerability for this syndemic in South Dakota. METHODS: Informed by prior methodology from the Centers for Disease Control and Prevention, we used acute and chronic HCV infections among persons aged ≤40 years as a proxy measure of IDU. Twenty-nine county-level indicators potentially associated with HCV infection rates were identified. Using these indicators, we examined relationships through bivariate and multivariate analysis and calculated a composite index score to identify the most vulnerable counties (top 20%) to this syndemic. RESULTS: Of the most vulnerable counties, 69% are reservation counties and 62% are rural. The county-level HCV infection rate is 4 times higher in minority counties than nonminority counties, and almost all significant indicators of opioid-related vulnerability in our analysis are structural and potentially modifiable through public health interventions and policies. CONCLUSIONS: Our assessment gives context to the magnitude of this syndemic in rural reservation and frontier counties and should inform the strategic allocation of prevention and intervention services.


Subject(s)
HIV Infections/epidemiology , Hepatitis C/epidemiology , Opiate Overdose/epidemiology , Substance Abuse, Intravenous/complications , Adolescent , Adult , Aged , Drug Users/statistics & numerical data , Geography , HIV Infections/prevention & control , HIV Infections/transmission , Health Services Accessibility/statistics & numerical data , Hepatitis C/prevention & control , Hepatitis C/transmission , Humans , Middle Aged , Models, Statistical , Opiate Overdose/prevention & control , Risk Factors , Rural Population/statistics & numerical data , Socioeconomic Factors , South Dakota/epidemiology , Substance Abuse, Intravenous/epidemiology , Young Adult
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