ipopba/istock via Getty Images

NIH Antibody Study Examines Early COVID-19 Biospecimens

An antibody study analyzed biospecimens from NIH’s All of Us Research Program and found that COVID- 19 infections appeared earlier in the US than previously reported.

A recent antibody study analyzed preserved biospecimens from the National Institutes of Health’s (NIH) All of Us Research Program and discovered that COVID-19 infections appeared as early as January 7th in five states, earlier than previously reported. The study was published in Clinical Infectious Diseases.

Researchers studied over 24,000 blood samples from All of Us participants in all 50 states, collected between January and March of 2020, prior to in-person visits being paused because of COVID-19. A retrospective analysis of preserved blood samples indicated that positive cases were present in the US prior to the first confirmed cases.

The All of Us Research Program seeks to recruit over a million people across the country to aid in medical research, according to its website. Participants share health information and donate samples and EHR data in order to advance NIH research efforts.

Most positive samples collected by researchers were received before the first positive cases were reported in those states, providing updated knowledge on the early spread of COVID-19 in the US.

"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, MD, MS, chief executive officer of All of Us and one of the study’s authors, said in a press release.

"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."

To determine if a sample was positive and to mitigate false positives, all samples had to be tested on two platforms per the Centers for Disease Control and Prevention’s (CDC) guidance. The samples were tested using the Abbott Architect SARS-CoV-2 IgG ELISA and the EUROIMMUNE SARS-CoV-2 ELISA (IgG) platforms in a sequential testing algorithm. While 147 participants received a positive Abbott result, only 9 participants were also positive on EUROIMMUNE.

In the states of Illinois, Wisconsin, Massachusetts, Mississippi, and Pennsylvania, seven preserved biospecimens tested positive before the first confirmed COVID-19 case in the given states.

The study stated that the earliest symptoms were recognized publicly on January 14th, 2020, and all 12 of the earliest cases were connected to people who had traveled to mainland China or were in contact with those who did. Most states did not acknowledge their first confirmed cases until late February or March.

“Determining the presence and location of SARS-CoV-2 in the earliest days of the US pandemic, together with other information on the spread and severity of COVID-19 illness, is important for understanding of the emergence of the virus, the epidemiology of this virus, and informing simulation models used to predict cases, deaths, and healthcare utilization and subsequently guide future pandemic planning, policy development and resource allocation,” the study stated.

The study was limited due to the number of samples in many states being very low. Additionally, it is unclear how participants were infected, whether it was through travel or in their own 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, PhD, the study’s lead author and associate professor of epidemiology at the Johns Hopkins Bloomberg School of Public Health in Baltimore explained in the press release.

"This study also demonstrates the importance of using multiple serology platforms, as recommended by the CDC."

Next Steps

Dig Deeper on Artificial intelligence in healthcare

xtelligent Health IT and EHR
xtelligent Healthtech Security
xtelligent Healthcare Payers
xtelligent Pharma Life Sciences
Close