A recent paper in the Journal of General Internal Medicine looked at the association between U.S. state-level income inequality and the number of cases and deaths from covid-19. The researchers assessed for this correlation using the Gini index—an economic measure of income distribution—while covid-19 data was ascertained from the Johns Hopkins University covid-19 dashboard for each of the 50 U.S. states between January 22 and April 13. The Gini index for each state was positively correlated with the number of covid-19 cases (correlation coefficient=0.38, p=0.006) and covid-19 deaths (correlation coefficient=0.44, p=0.002). The authors also adjusted for various potential confounding variables—the proportion of those living below the poverty line, age older than 65, gender and race, median household income, number of covid-19 tests performed per capita, doctors per capita, beds per capita and whether a state had a stay-at-home or shelter-in-place policy. Even after adjusting for these factors, states with a higher Gini index (indicating greater income inequality in that state) had a relatively higher number of covid-19 deaths. The findings were statistically significant. However, higher scores on the index were only marginally associated with the number of covid-19 cases, and not statistically significant. While there were some important limitations to this study—the use of state level-data precluded any inferences about individual-level outcomes and the use of observational data meant that the researchers had to use complicated statistical methods to adjust for the aforementioned confounding variables—the data strongly suggest that income inequality is at least a modest predictor of mortality resulting from SARS-CoV-2 infection. This adds to a growing body of evidence that at the population level, income inequality is not only a surrogate for poor chronic health, but also a potential harbinger for morbidity and mortality in pandemics of emerging infectious diseases such as SARS-CoV-2.
Some patients with covid-19 have low oxygen levels despite experiencing no difficulty with breathing. Healthcare professionals call this "hypoxemia out of proportion to respiratory effort" or "silent hypoxemia." Pulse oximetry—the routine use of oxygen sensors placed on the fingers in order to measure oxygen levels—is often done in healthcare settings. However, prior to the covid-19 pandemic, the use of these technologies at home was uncommon and had not been studied. A new study appearing in Academic Emergency Medicine assessed 77 outpatients who were tested (and subsequently found to be positive) for SARS-CoV-2, given portable pulse oximeters, and sent home. Of these patients, most (79 percent) were enrolled from an emergency department (ED). Patients were instructed to record their oxygen levels three times daily and to return to the ED for levels under 92 percent. Among the patients, 25 percent had at-home oxygen saturations of less than 92 percent and 36 percent eventually returned to the ED. Of the returnees, 79 percent were hospitalized and 29 percent to intensive care units. A substantial number of patients, 29 percent, returned solely because of the oxygen levels (i.e. not because symptoms worsened). Unfortunately, inconsistencies in how subjects collected their data and the small numbers of patients enrolled in the study render the conclusions difficult to rely on. Therefore, the overall benefit in the use of these at-home devices in suspected but unconfirmed covid-19 patients remains unclear. However, given that 10 percent of these outpatients were later admitted to the ICU and 2.6 percent had died by the time the study concluded, pulse oximetry is an enticing low-risk intervention which seems to help identify outpatients with covid-19 at risk of progressing from mild or moderate to severe or critical disease.