Epidemiology of the 2020 pandemic of COVID-19 in the state of Georgia: Inadequate critical care resources and impact after 7 weeks of community spread.

Objectives: Novel coronavirus (COVID-19) is a global pandemic currently spreading rapidly across the United States. We provide a comprehensive look at COVID-19 epidemiology across the state of Georgia, which includes vast rural communities that may be disproportionately impacted by the spread of this infectious disease. Methods: All 159 Georgia counties were included in this study. We examined the geographic variation of COVID-19 in Georgia from March 3 through April 24, 2020 by extracting data on incidence and mortality from various national and state datasets. We contrasted county-level mortality rates per 100,000 population (MRs) by county-level factors. Results: Metropolitan Atlanta had the overall highest number of confirmed cases; however, the southwestern rural parts of Georgia, surrounding the city of Albany, had the highest bi-weekly increases in incidence rate. Among counties with >10 cases, MRs were highest in the rural counties of Randolph (233.2), Terrell (182.5), Early (136.3), and Dougherty (114.2). Counties with the highest MRs (22.5-2332 per 100,000) had a higher proportion of: non-Hispanic Blacks residents, adults aged 60+, adults earning <$20,000 annually, and residents living in rural communities when compared with counties with lower MRs. These counties also had a lower proportion of the population with a college education, lower number of ICU beds per 100,000 population, and lower number of primary care physicians per 10,000 population. Conclusions: While urban centers in Georgia account for the bulk of COVID-19 cases, high mortality rates and low critical care capacity in rural Georgia are also of critical concern.

An analytical model of population level chronic conditions and COVID-19 related hospitalization in the United States.

BACKGROUND: The surge in the COVID-19 related hospitalization has been straining the US health system. COVID-19 patients with underlying chronic conditions have a disproportionately higher risk of hospitalization and intensive care unit (ICU) admission. We developed a retrospective analytical model of COVID-19 related hospitalizations and ICU admissions linked to each of the three major chronic conditions - hypertension, diabetes, and cardiovascular diseases (CVD). METHODS: Based on the differential probability of hospitalization of the COVID-19 patients with and without a chronic condition, we estimate a baseline cumulative hospitalization rate and ICU admission rate using the population level chronic condition prevalence from the 2019 Behavioral Risk Factor Surveillance System survey. Next, we estimate the hospitalization and ICU admission rates under an alternative scenario of a lower prevalence of the same chronic condition, aligned with the World Health Organization target of 25% relative reduction of prevalence by 2025. We then compare the outcomes of the baseline and the alternative scenarios. RESULTS: We estimate that the lower prevalence of hypertension would have lowered the cumulative hospitalization and ICU admission rates by more than 2.5%. The lower prevalence of diabetes and CVD would lower the cumulative hospitalization rate by 0.6% and 1.4% respectively. The decrease in the rates would have been relatively higher among Black and elderly (age 55+). CONCLUSIONS: Our model, thus, provides evidence on the importance of prevention, control, and management of chronic conditions to lessen the overwhelming financial and public health burden on the health system during a pandemic like the COVID-19.

Racial Disparities in the Epidemiology of COVID-19 in Georgia: Trends Since State-Wide Reopening.

Objective: To examine county-level factors associated with coronavirus disease 2019 (COVID-19) incidence and mortality in Georgia, focusing on changes after relaxation of "shelter-in-place" orders on April 24, 2020. Methods: County-level data on confirmed COVID-19 cases and deaths were obtained from the Johns Hopkins 2019 Novel Coronavirus Data Repository and linked with county-level data from the 2020 County Health Rankings. We examined associations of county-level factors with mortality and incidence rates (quantiles) using a logistic regression model. This research was conducted in June-July 2020 in Augusta, GA. Results: Counties in the highest quartile for mortality had higher proportions of non-Hispanic (NH)-Black residents (median: 37.4%; interquartile range [IQR]: 29.5-45.0; p<0.01) and residents with incomes less than $20,000 (median: 32.9%; IQR: 26.6-35.0; p<0.01). Counties in the highest quartile for NH-Black residents (38.7-78.0% NH-Black population) showed a 13-fold increase in odds (odds ratio=13.15, 95% confidence interval=1.40-123.80, p=0.05) for increased COVID-19 mortality controlling for income. Conclusions: Although highlighted by the pandemic, racial disparities predated COVID-19, exposing the urgency for diversion of resources to address the systematic residential segregation, educational gaps, and poverty levels experienced disproportionately by Black communities.

Altered mental status is an independent predictor of mortality in hospitalized COVID-19 patients.

BACKGROUND/AIMS: Limited data exists on the outcomes of COVID-19 patients presenting with altered mental status (AMS). Hence, we studied the characteristics and outcomes of hospitalized COVID-19 patients who presented with AMS at our hospital in rural southwest Georgia. METHODS: Data from electronic medical records of all hospitalized COVID-19 patients from March 2, 2020, to June 17, 2020, were analyzed. Patients were divided in 2 groups, those presenting with and without AMS. Primary outcome of interest was in-hospital mortality. Secondary outcomes were needed for mechanical ventilation, need for intensive care unit (ICU) care, need for dialysis, and length of stay. All analyses were performed using SAS 9.4 and R 3.6.0. RESULTS: Out of 710 patients, 73 (10.3%) presented with AMS. Majority of the population was African American (83.4%). Patients with AMS were older and more likely to have hypertension, chronic kidney disease (CKD), cerebrovascular disease, and dementia. Patients with AMS were less likely to present with typical COVID-19 symptoms, including dyspnea, cough, fever, and gastrointestinal symptoms. Predictors of AMS included age ≥ 70 years, CKD, cerebrovascular disease, and dementia. After multivariable adjustment, patients with AMS had higher rates of in-hospital mortality (30.1% vs 14.8%, odds ratio (OR) 2.139, p = 0.019), ICU admission (43.8% vs 40.2%, OR 2.59, p < 0.001), and need for mechanical ventilation (27.4% vs 18.5%, OR 2.06, p = 0.023). Patients presenting with AMS had increased length of stay. CONCLUSIONS: Patients with COVID-19 presenting with AMS are less likely to have typical COVID-19 symptoms, and AMS is an independent predictor of in-hospital mortality, need for ICU admission, and need for mechanical ventilation.