Latest COVID-19 research looks at serologic testing, transmission with nonsevere disease

Research is lacking on use of serologic COVID-19 tests at the point of care, according to a systematic review and meta-analysis published by the BMJ on July 1. Researchers analyzed 40 studies that were published from Jan. 1 through April 30 and measured sensitivity, specificity, or both of COVID-19 serologic tests versus a reference standard of a viral culture or reverse transcriptase polymerase chain reaction test. Pooled sensitivity was 84.3% (95% CI, 75.6% to 90.9%) for enzyme-linked immunosorbent assays (ELISAs) measuring IgG or IgM, 66.0% (95% CI, 49.3% to 79.3%) for lateral flow immunoassays (LFIAs), and 97.8% (95% CI, 46.2% to 100%) for chemiluminescent immunoassays (CLIAs). LFIAs, which are potential point-of-care tests, had the lowest pooled sensitivity in all analyses, with commercial kits lower than noncommercial kits.

The range of pooled specificities for all tests was 96.6% to 99.7%. Sensitivity was higher three weeks or more after symptom onset versus the first week of symptoms (range, 69.9% to 98.9% vs. 13.4% to 50.3%). The authors concluded that existing research on COVID-19 serologic tests is affected by a high risk for bias, heterogeneity, and limited generalizability to point-of-care and outpatient testing and called urgently for higher-quality studies. “Currently, available evidence does not support the continued use of existing point-of-care serological tests,” they wrote.

Regarding transmission, a study published by Clinical Infectious Diseases on June 29 found that viral loads appear to decrease within a few days of symptom onset in patients with nonsevere COVID-19 disease. Researchers looked at 230 health care personnel at the Cleveland Clinic who were diagnosed with COVID-19 and recovered without being hospitalized. In 528 tests performed over a six-week period, rapid declines in viral loads were seen within a few days of symptom onset, and time since symptom onset was the only variable significantly associated with viral load. The authors concluded that viral loads in upper respiratory samples from patients with nonsevere COVID-19 peak two to three days after symptom onset and then begin to decrease quickly.

“The vast majority of the area under the viral load-time curve lies within 10 days of onset of symptoms,” they wrote. “These findings should help inform decisions about returning employees recovering from COVID-19 to work in both healthcare and non-healthcare organizations.”

Studies also addressed the use of frailty and viral load as potential measures to help guide care of patients hospitalized with COVID-19. Researchers looked at data on 1,564 adults to determine frailty prevalence and its potential association with in-hospital mortality. The Clinical Frailty Scale (CFS) was used, with scores of 1 to 2 indicating fit, 3 to 4 indicating vulnerable but not frail, 5 to 6 indicating initial signs of frailty but some degree of independence, and 7 to 9 indicating severe or very severe frailty. Results were published June 30 by The Lancet Public Health.

When compared to patients with a CFS score of 1 to 2, adjusted hazard ratios for time from hospital admission to death were 1.55 (95% CI, 1.00 to 2.41) for patients with a CFS score of 3 to 4, 1.83 (95% CI, 1.15 to 2.91) for those with a CFS score of 5 to 6, and 2.39 (95% CI, 1.50 to 3.81) for those with a CFS score of 7 to 9. Adjusted odds ratios for mortality at day 7 were 1.22 (95% CI, 0.63 to 2.38), 1.62 (95% CI, 0.81 to 3.26), and 3.12 (95% CI, 1.56 to 6.24), respectively.

“Overall, these findings support the use of frailty as a trigger for specialist resource allocation, pathway decision aid, and in shared decision making in people with COVID-19,” the authors wrote. “The findings show the importance of frailty assessment, rather than age, in combination with other measures in the context of COVID-19.”

A study published June 30 by Clinical Infectious Diseases found that COVID-19 patients with a higher viral load at hospital admission are at higher risk for intubation and death. The retrospective cohort study looked at 678 patients hospitalized with COVID-19 from March 30 to April 30 at two New York City hospitals. Rates of in-hospital mortality and intubation were 35.0% and 29.1%, 17.6% and 20.8%, and 6.2% and 14.9% for those with high, medium, and low viral loads, respectively. An independent association was seen between high viral load and both death and intubation (adjusted odds ratios, 6.05 [95% CI, 2.92 to 12.52] and 2.73 [95% CI, 1.68 to 4.44]). The researchers concluded that SARS-CoV-2 viral load at admission is independently associated with risk for intubation and in-hospital death and that providing this information to clinicians might help inform care decisions.

Finally, a research letter published by Annals of Internal Medicine on June 29 found that step counts worldwide decreased after COVID-19 was declared a global pandemic on March 11. According to deidentified individual data from the smartphones of 455,404 unique users in 187 countries, mean steps decreased 5.5% and 27.3% worldwide within 10 days and 30 days, respectively, of the pandemic declaration. Average step count change as well as the timing and rate of change varied widely by region, probably reflecting variations in COVID-19 timing, regional enforcement of mitigation efforts, and behavior change, the authors said.

In the United States, decreased mobility appears to have helped decrease COVID-19 transmission, according to a mathematical modeling study published by The Lancet Infectious Diseases on July 1. Researchers used anonymous aggregated mobility data derived from mobile phones to look at real-time trends in movement patterns in 25 U.S. counties and used epidemiologic data to determine COVID-19 growth rate ratios. They found a strong correlation between decreased COVID-19 case growth rates and mobility patterns, which dropped by 35% to 63% and appear to have started to decrease in many places in the U.S. before state or local stay-at-home orders were issued. The researchers concluded that their findings strongly support the effectiveness of social distancing as way to slow the spread of COVID-19 in the United States.