- Insights from an N3C RECOVER EHR-based Cohort Study Characterizing SARS-CoV-2 Reinfections and Long COVID
This is the result of an electronic health record study cohort of over 3 million patients from the National COVID Cohort Collaborative as part of the NIH Researching COVID to Enhance Recovery Initiative. These investigators calculated summary statistics, effect sizes, and Kaplan–Meier curves to better understand COVID-19 reinfections. The article includes a ‘plain language summary’ in addition to the abstract and other sections of the paper. More than three years after the start of the COVID-19 pandemic, individuals are frequently reporting multiple COVID-19 infections. They report finding that individuals with severe initial infection are more likely to experience severe reinfection, that some protein levels are lower, leading to reinfection, and that a lower proportion of individuals are diagnosed with Long COVID following reinfection than initial infection. Here we read that the largest proportion of Long COVID diagnoses occurred among individuals with a first reinfection in the Delta epoch. But then they report that the rate of Long COVID diagnoses has been increasing with each successive Omicron variant.
- Cost-effectiveness of COVID Rapid Diagnostic Tests for Patients with Severe/Critical Illness in Low- and Middle-income Countries: A Modeling Study
Rapid diagnostic tests (RDTs) for coronavirus disease (COVID) are used in low- and middle-income countries (LMICs) to inform treatment decisions. But is this cost-effective or helpful? This study assessed the cost-effectiveness of COVID RDTs to inform the treatment of patients with severe illness in LMICs, considering real-world practice. They included the side effects of corticosteroids, which are often the only available treatment for COVID. They found that SARS-CoV-2 testing of patients with severe COVID-like illness can be cost-effective in all LMICs, though only in some circumstances. High influenza prevalence among suspected COVID cases improves cost-effectiveness, since incorrectly provided corticosteroids may worsen influenza outcomes. The authors suggest that the primary limitation of this analysis was substantial uncertainty around some of the parameters in the model due to limited data, most notably on current COVID mortality with standard of care, and insufficient evidence on the impact of corticosteroids on patients with severe influenza.
- Durability of Protection Against COVID-19 Through the Delta Surge for the NVX-CoV2373 Vaccine
Here are the results of the PREVENT-19 vaccine trial which used a blinded crossover design; the original placebo arm received NVX-CoV2373 after efficacy was established. “Using novel statistical methods that integrate surveillance data of circulating strains with post-crossover cases, we estimated placebo-controlled vaccine efficacy and durability of NVX-CoV2373 against both pre-Delta and Delta strains of SARS-CoV-2,” the authors say. Vaccine efficacy against pre-Delta strains of COVID-19 was 89% (95% CI, 75–95%) and 87% (72–94%) at zero and 90 days after two doses of NVX-CoV2373, respectively, with no evidence of waning (P = .93). Vaccine efficacy against the Delta strain was 88% (71–95%), 82% (56–92%), and 77% (44–90%) at 40, 120, and 180 days, respectively, with evidence of waning (P < .01). In sensitivity analyses, the estimated Delta vaccine efficacy at 120 days ranged from 66% (15–86%) to 89% (74–95%) per various assumptions of the surveillance data. - Combined Protection of Vaccination and Nirmatrelvir-Ritonavir Against Hospitalization in Adults With COVID-19
These are the results of a retrospective analysis of patient records in Cosmos, a dataset that, at the time of this study, included electronic health record information for more than 160 million individual users of U.S. health systems that use Epic electronic health record software. Among 731,349 patients with a COVID-19 diagnosis in an outpatient setting eligible for nirmatrelvir-ritonavir, 177,757 (24.3%) were unvaccinated, 157,011 (21.5%) received two mRNA vaccines, 330,448 (45.2%) received three or more mRNA vaccines, and 66,133 (9.0%) were categorized in the other vaccination category. Among those who were unvaccinated, 35,826 of 141,931 (20.2%) received nirmatrelvir-ritonavir compared with 42,355 of 157,011 (27.0%) who received two mRNA doses and 130,778 of 330,448 (33.0%) who received three or more mRNA vaccine doses.
- Tracking cognitive trajectories in older survivors of COVID-19 up to 2.5 years post-infection
In this study, 1,245 COVID-19 survivors and 358 uninfected spouses completed the 30-month follow-up. The investigators were looking at Telephone Interview for Cognitive Status-40 (TICS-40) scores. The TICS-40 includes the following variables and corresponding point values: date (5 points), address (3 points), counting backward (2 points), word list learning (10 points), subtractions (5 points), responsive naming (2 points), repetition (1 point), and President/Vice President’s last name (2 points), and delayed word list recall (10 points). The overall incidence of cognitive impairment was 19.1% among older COVID-19 survivors. Individuals with severe cases had a higher proportion of cognitive impairment than individuals with nonsevere cases (39.90% versus 14.95%, P < 0.001) and controls (39.90% versus 14.25%, P < 0.001). More specifically, individuals with severe cases had a higher proportion of suspected dementia and mild cognitive impairment (MCI) than individuals with nonsevere cases (dementia: 12.5% versus 1.74%, P < 0.001; MCI: 27.40% versus 13.21%, P < 0.001) and controls (dementia: 12.5% versus 1.68%, P < 0.001; MCI: 27.40% versus 12.57%, P < 0.001).
Situation Dashboards
World Health Organization (WHO)
Novel Coronavirus (COVID-19) Situation from World Health Organization (WHO)
Johns Hopkins University (JHU)
Coronavirus COVID-19 Global Cases by the Center for Systems Science and Engineering (CSSE) at JHU
COVID-19 in US and Canada
1Point3Acres Real-Time Coronavirus (COVID-19) Updates in US and Canada with Credible Sources
Genomic Epidemiology COVID-19
Genomic Epidemiology of (COVID-19) Maintained by the Nextstrain team, enabled by data from GISAID.