Killian Meara

Even a short stay in the hospital with a COVID-19 infection can adversely affect the long-term health and financial stability of patients, according to a study by investigators at the National Heart, Lung and Blood Institute (NHLBI), which is a part of the National Institutes of Health (NIH).

Results from the study were published in 

“This isn’t patients saying, ‘I can’t run quite as far as I used to’. This is them saying ‘I can’t walk, I can’t cook, I can’t shower’. The effects are devastating,” C. Terri Hough, a co-lead author on the study said. “Unfortunately, we saw this even among patients with quite short hospital stays.”

For the study, the team of investigators enrolled 1300 patients at 44 major medical centers in the Prevention and Early Treatment of Acute Lung Injury (PETAL) Network. The analysis presented in this study included 253 patients who were hospitalized with COVID-19.

The study period lasted from the fall 2020 through the early part of 2021.

Findings from the study showed that close to 85% of people that were hospitalized with COVID-19 said that they were not back to their pre-COVID lifestyle 1 month later. Many of the participants had new or worse cardiopulmonary symptoms, along with other significant factors which may be driving their inability to fully recover.

Financial impact was also widespread, with 23% of the participants reporting using up their life savings. Additional findings showed that almost half of the patients who were surveyed during the study period reported a new disability that prevented them from taking part in daily living activities 1 month later.

“As we continue, we’re excited that this study will link the biology of initial hospitalizations for COVID-19 to long-term patient-centered outcomes, and thereby help us find treatments to decrease the burden of recovery from COVID-19,” Hough said. “There are few other national studies that have both details about the hospital stay and are continuing to ask for patient perspectives like we are.”

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Close to 85% of people hospitalized with COVID-19 said that they were not back to their pre-COVID lifestyle 1 month later, says the study.

COVID-19 Hospital Stays Disrupt Long-Term Health, Financial Stability

The early vaccine campaign that was initiated in the United States prevented a significant amount of deaths, as well as cases of COVID-19, according to a study conducted by investigators from the RAND Corporation, in collaboration with Indiana University.

Results from the study were published in the journal 

“This study brings into focus the dramatic success of the early months of the nation’s coronavirus vaccine rollout,” Christopher Whaley, senior author on the study said. “The findings provide support for policies that further expand vaccine administration to enable a larger proportion of the nation’s population to benefit.”

For the study, the team of investigators created models which estimated the number of COVID-19 deaths and cases that would have occurred if the early vaccine campaign had never happened.

The team gathered information from each state on the number of vaccine doses administered from the Bloomberg COVID-19 vaccine tracker and data on COVID-19 deaths for each state from The New York Times’ Coronavirus (COVID-19) Data in the United States database.

Findings from the study showed that progress of vaccinations varied over time in different states.

Deaths that were prevented because of the early vaccinations were estimated to be around 140,000, with cases prevented being an estimated 3 million by the second week of May, 2021.

Additionally, the economic value of the lives saved during the study period is estimated to be between $625 billion and $1.4 trillion.

“Our results suggest that further efforts to vaccinate populations globally and in a coordinated fashion will be critical to achieving greater control of the COVID-19 pandemic,” Sumedha Gupta, first author on the study said.

Investigators created models which estimated the number of COVID-19 deaths and cases that would have occurred if the early vaccine campaign had never happened.

Quick Action on Vaccines in US Prevented Deaths, says Study

Individuals who had a severe case of COVID-19 or experience long-lasting cases of the disease are more likely to have a higher level of an important antibody which helps fight a future infection, according to a study conducted by investigators at Rutgers University.

Results from the study were published in 

“Neurological changes, including brain fog and problems with memory or vision, were infrequent among infected participants but did tend to last for many months when they occurred," Daniel B. Horton, a co-author on the study said. "Notably, having persistent symptoms was also associated with having higher antibody levels over time. We know from other research that vaccination further enhances immune protection and sometimes even helps ease long-term symptoms.”

The study was part of the Rutgers Corona Cohort Study, which followed 548 healthcare workers, along with 283 non-healthcare workers, from the beginning of the pandemic so that they could better understand risk factors, antibody responses and symptoms associated with a SARS-CoV-2 infection.

Findings from the study showed that within 6 months from when the study started, more than 93 of the participants had tested positive for the virus or for antibodies. Of those, 24 had severe symptoms and 14 were asymptomatic.

The study also found that healthcare workers were significantly more likely to become infected and have severe symptoms.

Around one-third of the participants showed symptoms which lasted for at least 1 month, including fatigue, shortness of breath and loss of taste and smell.

Additionally, the majority of the infected participants developed sustained antibodies which last up to 6 months. However, more of those with the severe symptoms were seen to have antibodies compared to those with mild to moderate symptoms.

“One-third of infected participants had symptoms lasting 1 month or longer. Fatigue, respiratory, and neurologic symptoms lasted for months in at least 10% of affected individuals,” the authors wrote. “Participants with prolonged symptoms, who were generally more severely symptomatic, also tended to have higher antibody levels over time. Going forward, this cohort of uninfected and infected, seropositive and seronegative, participants will allow further investigation of post-acute sequelae of SARS-CoV-2 infection, risks factors for re-infection, and relationships between infection and vaccine responses.”

Health care workers were significantly more likely to become infected and have severe symptoms, the study found.

High Levels of Important Antibody Seen in Those with Severe COVID

The history of COVID-19 continues to be a work in progress. The Centers for Disease Control and Prevention (CDC) confirmed the 

 in the United States of what was then still generally referred to as the “novel coronavirus” on January 20, 2020. The nature of diseases and how they spread always made that a soft start-time, open to reinterpretation and updates.

A recent study conducted by investigators from the National Institutes of Health has discovered evidence of COVID-19 infections in 5 states earlier than was initially reported. The study builds upon CDC findings which suggested the virus was in the country as far back as December 2019.

“This study allows us to uncover more information about the beginning of the U.S. epidemic and highlights the real-world value of longitudinal research in understanding dynamics of emerging diseases like COVID-19,” Josh Denny, an author of the study said. “Our participants come from diverse communities across the U.S. and give generously of themselves to drive a wide range of biomedical discoveries, which are vital for informing public health strategies and preparedness.”

For the study, the team of investigators worked with Quest Diagnostics, an American clinical laboratory, and tested over 24,000 blood samples for antibodies against SARS-CoV-2 from across all 50 states between January 2 and March 18 of 2020.

The team used 2 platforms, the Abbott Architect SARS-CoV-2 IgG ELISA and the EUROIMMUN SARS-CoV-2 ELISA (IgG), in order to minimize the amount of false positive tests.

Findings from the study demonstrated that some participants, including ones from Illinois and Massachusetts, tested positive for antibodies on January 7 and 8 of 2020, indicating that they were exposed at least 2 weeks earlier. This would mean that the virus was circulating in the country in at least mid-December.

The investigators did note some limitations, including that they did not know if the participants who tested positive became infected while travelling outside of their communities.

“Antibody testing of blood samples helps us better understand the spread of SARS-CoV-2 in the U.S. in the early days of the U.S. epidemic, when testing was restricted and public health officials could not see that the virus had already spread outside of recognized initial points of entry,” Keri N. Althoff, lead author on the study said. “This study also demonstrates the importance of using multiple serology platforms, as recommended by the CDC.”

The first official case may have been recorded January 20, 2020, but recent evidence suggests that COVID came home for the holidays in the U.S. in mid-December of that year.

COVID-19 May Have Hit the U.S. Earlier Than Previously Thought

When the United States and rest of the world struggled against the first waves of COVID-19 last year, it quickly became apparent that health care professionals were outgunned. There was just not enough personal protective equipment (PPE) 

 for PPE and mask use, allowing them to be reused, and hospitals also turned to just-in-time fit testing to help mitigate the problem, as 

A mask that doesn’t fit properly doesn’t offer much protection.

In fact, masks that don’t fit properly might actually increase a health care worker’s chances of contracting COVID-19. That’s the conclusion reached by investigators at the University of Cincinnati’s College of Engineering and Applied Sciences, in collaboration with the FDA’s Division of Applied Mechanics.

Results from their study were published in the journal 

“Many people do not realize that the fit of face masks can vary. There are different face shapes and different sizes of masks,” Rupak Banerjee, a professor in UC’s Department of Mechanical and Materials Engineering said. “If you do not match them well, you can lead to greater leaks and higher risks of infection.”

 in March, Beau Wangtrakuldee, PhD, the CEO and founder of a company called AmorSui, pointed out that “in the health care industry in general, small sizes are typically based on Caucasian males, so once you get to women who truly have smaller frames there are no products available for them.”

Wangtrakuldee also spoke about a hospital ward in the United Kingdom in which 80% of the staff were women and how “they developed ulcers from having to tie N95 masks too tightly in order to feel protected or have them fit properly.”

 study, investigators employed computerized tomography (CT) scans of 3 different sized face masks which were attached to 3 different sized dummy heads to measure the gaps between the face and the fabric.

They then created a 3D computer-aided design model using the CT scans that showed the gaps between the mask and the dummy head and calculated the rate of airflow through them to identify the relative risk of infection for each mask.

Findings from the study demonstrated that the aerosol transport due to the gaps between the mask and the dummy heads varied from 30% to 95%. Leaks were seen to be largest around the nose.

The most poorly fitting mask can almost double the risk of infection for the wearers and even those around them.

The investigators hope that the results from this research will help to educate consumers and aid manufacturers in developing masks.

“The set of computational models presented are useful for predicting the relative infection risk for different types of protection, facial profile types, pathogen characteristics, and level of compliance,” the authors wrote. “The leakage and the risk-assessment models can be helpful in developing protection strategy, establishing PPE guidelines, and promoting awareness for the general public during a pandemic.”

If the Mask Doesn’t Fit, COVID-19 Will Hit

 test that renders results faster than you can count to 1. Investigators with the University of Florida, in collaboration with Taiwan’s National Chiao Tung University, not only imagined it, they invented it, according to a study in the 

Journal of Vacuum Science & Technology B. 

To perhaps point out the obvious, that’s significantly quicker than most currently available COVID-19 testing methods.

“This could alleviate slow COVID-19 testing turnaround time issues,” Minghan Xian, an author and a chemical engineering doctoral candidate at the University of Florida said.

For the study, the team of investigators worked upon previous research that they conducted which demonstrated the detection of biomarkers that are relevant in the Zika virus, heart attacks, and cerebral spinal fluid leaks.

The team developed a sensor system that amplifies the binding signal for a target biomarker in order to detect the presence of a virus.

The system has sensor strips which are connected to a circuit board via a connector which sends a short, electric signal between a gold electrode which is bonded with a COVID-19 antibody and an auxiliary electrode. Once this is completed, the signal returns to the circuit board where it is analyzed.

“Our sensor system, a circuit board, uses a transistor to amplify the electrical signal, which then gets converted into a number on the screen,” Xian said. “The magnitude of this number depends on the concentration of antigen, the viral protein, present within our test solution.”

Additionally, the cost of the test is able to be greatly reduced due to the fact that the test circuit board is reusable. The investigators believe that this technology can also be adopted for other uses.

“By altering the type of antibodies attached to the gold surface, we can repurpose the system to detect other diseases,” Xian said. “The system can serve as a prototype for modularized, inexpensive protein biomarker sensors for expedient real-time feedback within clinical applications, operating rooms, or home use.”

Investigators developed a sensor system that amplifies the binding signal for a target biomarker in order to detect the presence of a virus.