Health Informatics to Model the Scott County HIV Outbreak

摘要

ABSTRACT COVID-19 cases and deaths are surging in rural areas of the United States. In the last two weeks of April 2020, the average number of COVID-19 cases per 100,000 persons rose 125% in rural U.S. counties but only 68% in urban counties. During this same time period, COVID-19 related deaths rose 169% in rural areas compared to 113% in urban areas. As of May 4 2020, Georgia had 28,945 confirmed cases of COVID-19 and 1,186 COVID-19-related deaths. Georgia is a predominantly rural state. Rural people living with HIV (PLHIV) are at-risk for COVID-19 due, in part, to compromised immune systems and high rates of comorbid health conditions. Rural PLHIV with comorbid substance use disorders (SUDs) are at particularly high risk for COVID- 19 infection. Many rural PLHIV + SUDs lack access to medical and psychological care, must travel vast distances to receive HIV and SUD treatments, experience high rates of mood disorders, and experience discrimination, prejudice, and stigma related to their HIV-status, sexual-identity, and SUD. Georgia is an opportune state in which to study risk for COVID-19 in rural PLHIV + SUDs. In 2017, Georgia had the highest HIV prevalence rate per 100,000 residents of any state. Currently, Georgia ranks 12th in number of COVID-19 cases, 5th in hospitalizations due to COVID-19, but has the nation's 7th slowest COVID-19 testing rate. This study's scientific premise is that, to date, most COVID-19 research has been conducted in urban centers; little is known about (i) rates of COVID-19 in rural PLHIV + SUDs, (ii) factors predictive of COVID-19 infection in this group, and (iii) types of preventive behaviors in which rural PLHIV + SUDs engage to avoid infection. This study will assemble a prospective longitudinal cohort of 100 rural PLHIV in northeast Georgia, 50% of whom have an active SUD (most likely opioid use disorders). The study will be conducted in Georgia's Health District 10, in which all ten counties are classified as “rural,” 9 are mental health professional shortage areas, and 8 are primary care professional shortage areas. To maximize participant safety, all data will be collected using innovative remote assessment methodologies. Guided by Wilson and Cleary's model of life quality, participants will complete assessments at baseline and 3-, 6- and 9-month follow-up that collect: (1) biologic data: CD4 count, HIV viral load, viral hepatitis status; (2) behavioral/psychosocial data: tobacco and marijuana use, vaping practices, depressive symptoms, ways of coping with COVID-19-related stress, and coping self-efficacy; and (3) environmental data: housing status and correctional systems involvement. Surveys will also assess COVID-19 prevention behavior data (e.g., washing hands with soap and water; social distancing). Analyses will compare rural PLHIV + SUDs to rural PLHIV without SUDs on rates of engaging in COVID-19 preventive behaviors. Logistic regression analyses will identify factors predictive of COVID-19 infection in this group. Study findings can inform the development of COVID-19 prevention interventions for rural PLHIV and possibly contextualize interventions for the unique needs of rural PLHIV + SUDs.