New study predicts impact of COVID-19 on labor and delivery in U.S.
In a study published online in the journal American College of Obstetrics & Gynecology MFM, physician-researchers from University Hospitals Cleveland Medical Center and Georgia State University project 52 COVID-19 related maternal mortalities in the United States this year. This is the first known study to forecast the impact of COVID-19 on labor and delivery hospitalization.
“We know that pregnancy alters the immune system, and given the fact that the majority of American women deliver in a hospital setting it creates a unique challenge in the fight against the novel coronavirus,” says David Hackney, MD, Director, Maternal Fetal Medicine, UH Cleveland Medical Center, and an author on the study. “The goal of our research is to best predict the impact of COVID-19 on obstetric care in the United States in order to better prepare maternity units and caregivers.”
The study used incidence data from March 1, 2020 – April 14, 2020 in a phenomenological model to forecast the incidence of COVID-19 in the US from April 15, 2020 – Dec. 31, 2020. Subsequently, Monte-Carlo simulation was performed for each week from March 1, 2020 – Dec. 31, 2020 to estimate COVID-19 cases in delivery hospitalizations. This is the same model that successfully forecasted the incidence of COVID-19 in several provinces in China.
“Our model projects an increase in the United States’ maternal mortality rate to at least 18.7 per 100,000 live births as a direct result of this pandemic,” says the studies’ principal investigator Manesha Putra, MD, Maternal Fetal Medicine, UH Cleveland Medical Center. “More specifically, the study predicts 3,308 severe and 681 critical COVID-19 cases among delivering women in the US, with about 52 maternal mortalities.”
“To our knowledge this is the first study on the incidence of COVID-19 in pregnancy,” says Dr. Putra. “Despite its limitations, this study has the ability to guide resource allocation and better prepare hospitals and caregivers on the frontlines.”
