NIH awards research grants for COVID-19 detection technologies


The National Institutes of Health has given 8 research grants for refining new technologies to provide early diagnosis of severe illness associated with COVID-19 infection in children.

The National Institutes of Health (NIH) recently awarded 8 research grants for the development of new technologies aiming for early diagnosis of serious infections caused by COVID-19 in pediatric patients.

The NIH’s Predicting Viral-Associated Inflammatory Disease Severity in Children with Laboratory Diagnostics and Artificial Intelligence (PreVAILkIds) initiative granted the awards. They support a program for new approaches and uses of tools for addressing gaps in COVID-19 testing and surveillance.

Some cases of COVID-19 lead to mild or no symptoms, but others lead to severe outcomes such as multisystem inflammatory syndrome in children (MIS-C), leading to inflammation of 1 or more organs. These include the kidneys, lungs, heart, skin, brain, eyes, and gastrointestinal tract.

Research funded from the 2020 awards led to prototype methods and techniques that could potentially be used in clinics. Results from PreVAILkIds studies in 2020 led to a laboratory technique that can detect immune cells linked to MIS-C, along with databases to determine the risks of MIS-C and severe COVID-19 in children.

With the new awards, researchers will be able to develop further methods of rapidly diagnosing MIS-C and determining which individuals are at an increased risk of long-term severe effects from COVID-19. 

One recipient of the latest award is Jane C. Burns, MD, from the University of California. Burns was awarded for diagnosing and predicting the risks in children with COVID-19 related illnesses.

Another recipient of the award is Cedric Manlhiot, PhD, from Johns Hopkins University. Manlhiot was awarded for a data science approach to identifying and managing MIS-C related to COVID-19.

A third recipient is Ananth V. Annapragada, PhD, from the Baylor College of Medicine, for the use of artificial intelligence to assess COVID-19 risk for kids. A fourth recipient is Audrey R. Odom John, MD, PhD, from the Children’s Hospital of Philadelphia, for diagnosing MIS-C in febrile children.

A fifth recipient is Usha Sethuraman, MD, for using severity protectors integrating salivary transcriptomics and proteomics with multineural network intelligence in children with COVID-19.

A sixth recipient is Juan C. Salazar, MD, MPH, from Connecticut Children’s Medical Center,for identifying biomarker signatures of prognostic value for MIS-C. A seventh recipient is Charles Yen Chiu, MD, PhD, from the University of California, for the discovery and clinical validation of host biomarkers of disease severity and MIS-C in cases of COVID-19.

The final recipient was Lawrence Kleinman, MD, MPH, from Rutgers Robert Wood Johnson Medical School, for creating a network which expanded clinical and translational approaches for predicting severe illness in children with COVID-19.


NIH funds eight studies to advance rapid diagnosis of COVID-19-related inflammatory syndrome in children. National Institutes of Health. January 9, 2023. Accessed January 10, 2023.

Related Videos
Carissa Baker-Smith
Perry Roy, MD
Perry Roy, MD | Image Credit: Carolina Attention Specialists
Angela Nash, PhD, APRN, CPNP-PC, PMHS | Image credit: UTHealth Houston
Allison Scott, DNP, CPNP-PC, IBCLC
Joanne M. Howard, MSN, MA, RN, CPNP-PC, PMHS & Anne Craig, MSN, RN, CPNP-PC
Juanita Mora, MD
Natasha Hoyte, MPH, CPNP-PC
Lauren Flagg
© 2024 MJH Life Sciences

All rights reserved.