A third dose of COVID-19 vaccine offered essential workers some protection from developing long COVID during Omicron variant predominance, according to a new study in The Journal of Infectious Diseases.

In the study, researchers found that essential workers who received a third COVID-19 monovalent mRNA vaccine dose had lower odds of long-COVID–related gastrointestinal, neurologic, and other symptoms than unvaccinated participants, by 63%, 44%, and 52%, respectively. 

The study was based on outcomes seen among essential workers with COVID-19 infection between June 2021 and September 2022. The workers were from six US cities and worked in education, hospitality, and food service, among other jobs.

In the study, 936 participants had documented SARS-CoV-2 infection; of those, 23.6% (221) reported long-COVID symptoms, and 83.3% (779) were vaccinated. 

Among those who had received three or more vaccine doses, the adjusted odds ratio (aOR) for developing long COVID–associated gastrointestinal symptoms was 0.37 (95% confidence interval [CI], 0.16 to 0.85), while it was 0.56 (95% CI, 0.32 to 0.97) for neurologic symptoms, and 0.48 (95% CI, 0.25 to 0.91) for other symptoms.

This report demonstrates the effect of COVID-19 vaccination in reducing progression to PCC.

"This report demonstrates the effect of COVID-19 vaccination in reducing progression to PCC [post-COVID condition] during circulation of the SARS-CoV-2 Omicron variant in the U.S. and highlights that COVID-19 vaccination can serve as an important additional tool to prevent PCC,” the authors concluded. 

Surveillance data released yesterday by the Centers for Disease Control and Prevention (CDC) show that rates of meningococcal disease have risen sharply in the United States since 2021 and now exceed pre–COVID-19 levels.

A total of 438 confirmed and probable cases of meningococcal disease were reported in 2023, the most US cases reported since 2013. The increase has been driven primarily by Neisseria meningitidis serogroup Y, which is disproportionately affecting Black people, adults between the ages of 30 and 60, and those with HIV. Serogroup Y is one of four N meningitidis serogroups (B, C, and W are the others) that cause most meningococcal disease cases in the United States.

A recent study published in Morbidity and Mortality Weekly Reports described an outbreak of N meningitidis serogroup Y infections in Virginia from 2022 to 2024 in which 80% of cases were in Black residents and 63.9% in residents aged 30 to 60 years.

A rare but severe disease

Meningococcal disease is a rare but severe illness that most often presents as meningitis, with symptoms that may include fever, headache, stiff neck, vomiting, and altered mental status. It can worsen rapidly and become deadly within hours. Even with appropriate antibiotic treatment, the case-fatality rate is 10% to 15%. Prior to 2021, meningococcal disease incidence in the United States had been falling.

In March, the CDC issued a health advisory to alert healthcare providers to the increase in cases, advising them to have heightened awareness of meningococcal disease, particularly among disproportionately affected groups, and to be aware that some patients might present without symptoms typical of meningitis. 

The advisory also urged providers to ensure that everyone who's recommended to receive meningococcal vaccination is up to date. The CDC recommends meningococcal vaccination for all adolescents and for children and adults who are at increased risk for meningococcal disease.

A genomic surveillance study identified several multidrug-resistant (MDR), high-risk clones of Escherichia coli and Klebsiella pneumoniae in Kenya, Uganda, and Jordan, researchers reported this week in Emerging Infectious Diseases.

Using an antimicrobial resistance (AMR) surveillance program run by the US Armed Forces Health Surveillance Division, researchers analyzed MDR E coli and K pneumoniae isolates collected from patients with healthcare-associated and community-acquired infections in the three countries from 2012 through 2022. A total of 758 E coli and 378 K pneumoniae isolates were tested for susceptibility to a panel of different classes of antibiotics and subjected to whole-genome sequencing (WGS).

Genetically diverse, high-risk MDR clones

Among the E coli isolates, there were 124 sequence types (STs), 20 of which were shared among the three countries. The dominant ST was ST131, which has emerged as a major cause of MDR urinary tract infections worldwide, followed by ST1193, a high-risk clone that recently diverged from ST131. Three potential zoonotic E coli STs (ST10, ST95, and ST117) that are common in food animals and have pathogenic potential were also identified. Among K pneumoniae isolates, there were 123 STs, with ST14, ST147, ST307, and ST258 identified as the most concerning. 

WGS revealed acquired extended-spectrum beta-lactamase (ESBL) genes in 50.8% of E coli isolates and 68.8% of K pneumoniae isolates, while carbapenemase genes were detected in 1% of E coli and 12% of K pneumoniae isolates. Mobile colistin-resistance (MCR) genes were found in 2 E coli isolates (MCR-1.1) and 5 K pneumoniae isolates (MCR-8.1 and MCR-9).

"Overall, our study highlights the emergence and threat of genetically diverse high-risk MDR clones of 2 of the most critical groups of MDR bacteria causing severe infections with limited treatment options," the study authors wrote. "The abundance of global high-risk STs bearing resistance genes indicates their effective dissemination, the potential for intraspecies and interspecies transmission of resistance genes, and emergence of new high-risk clones."

Massachusetts General Hospital (MGH) researchers who developed a new artificial intelligence (AI) tool that uncovers previously unrecognized signs of long COVID in electronic medical records (EMRs) say it suggests that 23% of the population has the condition at some point.

Published last week in Med, the research may reveal the true scope of the pandemic's long-term consequences, offer a personalized approach to care, and diminish the biases that many patients have faced when seeking long-COVID care.

The AI tool identifies and tracks long-COVID signs or symptoms (eg, shortness of breath) that can't be explained by alternative diagnoses (eg, asthma) in the EMRs of patients who had COVID-19 at least 2 months before. The researchers developed the algorithm by deriving data from nearly 300,000 patients at 14 MGH hospitals and 20 community health centers. 

More accurate, less biased

While current estimates suggest a long-COVID prevalence of 7%, the researchers' estimate was much higher, at 22.8%. In addition, the AI tool was roughly 3% more accurate than the relevant diagnostic code and less biased toward certain populations, such as those with better healthcare access.