Mondi is committed to playing its part to produce important supplies and components during the COVID-19 outbreak. As a global leader in packaging and paper, Mondi’s Personal Care Components team has found a way to convert a production line at its Gronau plant in Germany to manufacture soft, elastic straps which are now being used for face masks and used by medical professionals and consumers globally.

Mondi’s plant in Gronau, Germany, typically focuses on making materials used in hygiene products such baby diapers, adult incontinence pads and feminine care items. However, the plant was able to quickly adapt one of its manufacturing lines to produce a three-layer, laminated strap that binds a stretchable plastic film between layers of soft, nonwoven material. The straps, which Mondi supplies to its mask-making customers on a reel, are then cut and attached to each side of a mask, which can loop comfortably over the user’s ears to hold the mask in place.

This elastic material replaces a rubberised band that holds the mask to the face, thereby increasing operational speed of the machines in comparison to rubber which is slower.

“Mondi Gronau is working to provide straps that will fit more than one billion nonwoven face masks. As there is increasing demand for such types of face masks, we are building up our capability to meet this demand. By producing this soft elastic strap, we are able to produce more volume to meet growing demand,” says Dr. Michael Trinkaus, director of R&D and application engineering for Mondi’s Personal Care Components division.

Our support in China
Mondi also operates a plant in Taicang, China, that laminates film made in Gronau to make nonwoven hygiene products similar to those manufactured in Germany. While closely monitoring developments, assessing risks, and implementing preventative policies in line with the local government regulations and recommendations, the company was able to meet orders for mask straps from customers in China when the COVID-19 virus epidemic first broke out. Demand is now growing for more of such supplies from customers across Europe, prompting the Gronau plant to increase production of this material.

About Mondi
Mondi is a global leader in packaging and paper, contributing to a better world by making innovative, packaging and paper solutions that are sustainable by design. Our business is fully integrated across the value chain – from managing forests and producing pulp, paper and plastic films, to developing and manufacturing effective industrial and consumer packaging solutions. Sustainability is at the centre of our strategy and intrinsic in the way we do business. We lead the industry with our customer- centric approach, EcoSolutions, where we ask the right questions to find the most sustainable solution. In 2019, Mondi had revenues of €7.27 billion and underlying EBITDA of €1.66 billion.

Mondi has a premium listing on the London Stock Exchange (MNDI), and a secondary listing on the JSE Limited (MNP). Mondi is a FTSE 100 constituent, and has been included in the FTSE4Good Index Series since 2008 and the FTSE/JSE Responsible Investment Index Series since 2007.

About Mondi PCC
Mondi Personal Care Components is a global leading supplier of elastic and nonwoven solutions for the hygiene industry, offering comprehensive baby care, adult incontinence, feminine care, and nonwoven materials. Mondi PCC strives to make comfort a way of life and supports every generation. The product portfolio includes elastic stretch laminates and nonwoven components for baby diapers and adult incontinence products, film and nonwovens for femcare, and nonwovens for wipes.

In response to the nationwide shortage of personal protective equipment (PPE) during the COVID-19 crisis, Baptist Health is expanding its use of robotic disinfecting technology to clean and preserve N95 masks, which help team members protect themselves and others from the spread of infectious diseases such as COVID-19. The health system is one of the first in the region to use this approach, an innovative response to a shortage that has impacted hospitals across the U.S.

“Our use of LightStrike robots is just one part of our broader effort to provide the best possible care to all patients.”
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The LightStrike™ robots are designed and manufactured by Xenex® Disinfection Services™ and use pulsed xenon ultraviolet (UV) light to quickly deactivate microorganisms and disinfect high-touch surfaces in healthcare facilities. By damaging the DNA of bacteria and viruses, the intense UV light prevents them from multiplying or mutating. Baptist Health already uses LightStrike robots to disinfect patient and operating rooms, and now one robot at each hospital has been set aside specifically for cleaning N95s.

“As COVID-19 continues to spread, our teams are working hard to research and implement evidence-based strategies to address projected needs,” said Elizabeth Ransom, MD, FACS, executive vice president and chief physician executive at Baptist Health. “Our use of LightStrike robots is just one part of our broader effort to provide the best possible care to all patients.”

As the mask cleaning program is rolled out this week, each facility will have a room dedicated to disinfecting the masks, which will be strung along wire shelving, resembling clothes on a clothesline. After a five-minute disinfection cycle, the masks are rotated and then exposed for five minutes on the other side, allowing both their exterior and interior to be decontaminated. Units with high N95 use, such as the COVID-19 units and the emergency departments, are among the first to have their masks cleaned, and there are plans for the program to expand to other departments across the hospital system.

“During an ongoing crisis like the one we are facing now, our health system is applying innovative ideas that are shown to be effective,” said David Rice, MD, senior vice president and chief quality officer for Baptist Health. “The use of Xenex robots to disinfect our masks is just one of the ways we are rethinking how we do things so that we can benefit our patients and team members alike.”

If you are interested in setting up an interview to discuss the use of this Xenex technology at Baptist Health, please contact Cindy Hamilton at Cindy.Hamilton@bmcjax.com or 904.202.4907.

About Baptist Health

Baptist Health is a faith-based, mission-driven system in Northeast Florida comprised of Baptist Medical Center Jacksonville; Baptist Medical Center Beaches; Baptist Medical Center Nassau; Baptist Medical Center South; Baptist Clay Medical Campus and Wolfson Children’s Hospital – the region’s only children’s hospital. All Baptist Health hospitals, along with Baptist Home Health Care, have achieved Magnet™ status for excellence in patient care. Baptist Health is part of Coastal Community Health, a highly integrated regional hospital network focused on significant initiatives designed to enhance the quality and value of care provided to our contiguous communities. Baptist Health has the area’s only dedicated heart hospital; orthopedic institute; women’s services; neurological institute, including comprehensive neurosurgical services, a comprehensive stroke center and two primary stroke centers; a Bariatric Center of Excellence; a full range of psychology and psychiatry services; urgent care services; and primary and specialty care physicians’ offices throughout Northeast Florida. The Baptist MD Anderson Cancer Center is a regional destination for multidisciplinary cancer care which is clinically integrated with the MD Anderson Cancer Center, the internationally renowned cancer treatment and research institution in Houston. For more details, visit baptistjax.com.

An artificial intelligence (AI) tool accurately predicted which patients newly infected with 2019 coronavirus disease (COVID-19) would go on to develop severe respiratory disease, a new study finds.

The work was led by NYU Grossman School of Medicine and NYU Courant Institute of Mathematical Sciences, in partnership with Wenzhou Central Hospital and Cangnan People’s Hospital, both in Wenzhou, China.

Named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the new virus causes the disease called COVID-19. As of March 30, the virus had infected 735,560 people worldwide. According to the World Health Organization, the illness has caused more than 34,800 deaths to date, more often among older patients with underlying health conditions. The New York State Department of Health has reported 33,700 cases to date in New York City.

Published online March 30 in the journal Computers, Materials & Continua, the study also revealed the best indicators of future severity, and found that they were not as expected.

“While work remains to further validate our model, it holds promise as another tool to predict the patients most vulnerable to the virus, but only in support of physicians’ hard-won clinical experience in treating viral infections,” says corresponding study author Megan Coffee, MD, PhD, clinical assistant professor in the Department of Medicine and member of the Division of Infectious Diseases and Immunology at NYU Langone.

“Our goal was to design and deploy a decision-support tool using AI capabilities—mostly predictive analytics—to flag future clinical coronavirus severity,” says co-author Anasse Bari, PhD, a clinical assistant professor in computer science at NYU Courant Institute of Mathematical Science. “We hope that the tool, when fully developed, will be useful to physicians as they assess which moderately ill patients really need beds, and who can safely go home, when hospital resources are stretched thin.”
AI Tool Finds Surprise Predictors

For the study, demographic, laboratory, and radiological findings were collected from 53 patients as each tested positive in January 2020 for the SARS-CoV-2 virus at the two Chinese hospitals. Symptoms were typically mild to begin with, including cough, fever, and stomach upset. In a minority of patients, however, severe symptoms developed within a week, including pneumonia.

The goal of the new study was to determine whether AI techniques could help to accurately predict which patients with the virus would go on to develop acute respiratory distress syndrome, or ARDS, the fluid buildup in the lungs that can be fatal in the elderly.

For the new study, the researchers designed computer models that make decisions based on the data fed into them, with programs getting “smarter” the more data they consider. Specifically, the current study used decision trees that track series of decisions between options and that model the potential consequences of choices at each step in a pathway.

The researchers were surprised to find that characteristics considered to be hallmarks of COVID-19, like certain patterns seen in lung images (for example, ground glass opacities), fever, and strong immune responses, were not useful in predicting which of the many patients with initial, mild symptoms would go on to develop severe lung disease. Neither were age and gender helpful in predicting serious disease, although past studies had found men over 60 to be at higher risk.

Instead, the new AI tool found that changes in three features—levels of the liver enzyme alanine aminotransferase (ALT), reported myalgia, and hemoglobin levels—were most accurately predictive of subsequent, severe disease. Together with other factors, the team reported being able to predict risk of ARDS with up to 80 percent accuracy.

ALT levels—which rise dramatically as diseases like hepatitis damage the liver—were only a bit higher in patients with COVID-19, researchers say, but still featured prominently in prediction of severity. In addition, deep muscle aches (myalgia) were also more commonplace, and have been linked by past research to higher general inflammation in the body. Is there an immune element causing worse outcomes?

Lastly, higher levels of hemoglobin, the iron-containing protein that enables blood cells to carry oxygen to bodily tissues, were also linked to later respiratory distress. Could this be explained by other factors, like unreported smoking of tobacco, which has been linked to increased hemoglobin levels. Of the 33 patients at Wenzhou Central Hospital interviewed on smoking status, the 2 who reported having smoked also reported that they had quit.

Limitations of the study, say the authors, included the relatively small dataset and the limited clinical severity of disease in the population studied. The latter may be due in part to an as yet unexplained dearth of older patients admitted into the hospitals during the study period. The average patient age was 43.

“I will be paying more attention in my clinical practice to our data points, watching patients closer if they for instance complain of severe myalgia,” adds Dr. Coffee. “It’s exciting to be able to share data with the field in real time when it can be useful. In all past epidemics, journal papers only published well after the infections had waned.”

Along with Dr. Coffee and Dr. Bari, authors of the study included first author Xiangao Jiang, along with Jianping Huang, Jichan Shi, Jianyi Dai, Jing Cai, Zhengxing Wu, and Guiqing He, in the Department of Infectious Diseases at Wenzhou Central Hospital. Also from Wenzhou Central Hospital was author Yitong Huang of the Department of Gynaecology.

Also study authors were Junzhang Wang of NYU Courant Institute of Mathematical Sciences, Xinyue Jiang of Columbia University, and Tianxiao Zhang in Department of Infectious Diseases at Cangnan People’s Hospital. Dr. Coffee is also adjunct faculty in the Department of Population and Family Health at Columbia University Mailman School of Public Health.

As part of its broader COVID-19 response, UCSF Health is working with hospitals across the City of San Francisco to expand inpatient and critical care capacity to meet the anticipated surge in demand due to the novel coronavirus disease.

San Francisco Mayor London Breed on March 25 announced the opening of a new COVID-19 facility at Saint Francis Memorial Hospital to help the city prepare for a surge in patients. The facility will include 40 beds on a dedicated floor at Saint Francis, with an additional eight-bed intensive care unit. The first 10 beds will be available the first week in April.

The facility is the product of a collaboration across San Francisco hospitals – led by the Hospital Council, the San Francisco Department of Public Health, Zuckerberg San Francisco General Hospital and Trauma Center, Dignity Health and UCSF Health – that aims to address the epidemic on a united front.

In addition to providing medical staff, UCSF Health is contributing $1 million to help build out the unit and providing nursing leadership to replicate the staffing model used in the UCSF COVID-19 unit at Parnassus Heights. UCSF School of Pharmacy is also contributing clinical pharmacy expertise. Kaiser Permanente, Sutter Health and Chinese Hospital will supplement physician staffing.

The collaboration also includes a new predictive modeling system, developed in partnership with UC Berkeley researchers, in which all city hospitals will collectively track the numbers and outcomes of COVID-19 patients in hospitals citywide.

The city estimates that if the current shelter-in-place efforts are not successful, San Francisco will need significant numbers of additional beds to meet the needs of a surge in the coming weeks. This effort is one of several steps that San Francisco hospitals are taking to help meet that demand.