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Principal Investigator: DANIEL K. BENJAMIN
Organization: DUKE UNIVERSITY
Fiscal Year: 2020
Award: $869,057
Funding agency: National Center for Advancing Translational Sciences
PROJECT SUMMARY/ABSTRACT
The impact of the current COVID-19 global pandemic is likely underestimated. The specific impact on pregnant
women, their infants and children is even less well characterized. We will use the infrastructure of the Duke /
Vanderbilt Trial Innovation Center to address these knowledge gaps with three projects. We will use an
existing electronic data warehouse of clinical data from approximately 100,000 infants admitted to over 200
neonatal intensive care units in the US to examine the epidemiology and outcomes through 12 months of age
for infants born to mothers during the current pandemic. Our collaborative research team, comprising
neonatologists and biostatisticians from the Duke Clinical Research Institute (DCRI) and the Pediatrix Medical
Group, is uniquely positioned to complete this project. In addition, we will perform a direct-to-family
observational study to evaluate the natural history of SARS-CoV-2 infection in children exposed to the virus
presumably via health care worker household contact. Up to 1000 children will be enrolled across the United
States. We will identify households using existing registries/trials and will evaluate the rate of infection, viral
shedding, and immune response of children exposed to SARS-CoV-2. Finally, to realize the full value of the
data collected as part of the multiple ongoing COVID-19 studies, data needs to be curated and harmonized.
Here, data curation is defined as a metadata management activity that results in data with well-defined
outcomes and exposures. The majority of curation will occur at individual study level. After the data have been
harmonized, we will perform detailed quality checks. The resulting harmonized data will made availabel at
different timepoints to various audiences with the final result beign a publically available de-identitified dataset.
As a result of this research, we will fill major knowledge gaps related to COVID-19 and improve public health.
Terms: <0-11 years old><2019 novel coronavirus><2019-nCoV><21+ years old><Address><Administrative Supplement><Adult><Adult Human><Affect><Age-Months><Award><COVID><COVID-19><COVID-19 epidemic><COVID-19 pandemic><COVID19><COVID19 epidemic><COVID19 pandemic><Child><Child Youth><Children (0-21)><Clinical Data><Clinical Research><Clinical Study><Clinical and Translational Science Awards><CoV disease><Data><Data Pooling><Data Set><Dataset><Emergencies><Emergency Situation><Enrollment><Epidemiology><Exposure to><Family><Frequencies><Health Care Providers><Health Personnel><Healthcare Providers><Healthcare worker><Household><Immune response><Immunological response><Individual><Infant><Infection><Infrastructure><Knowledge><Medical><Metadata><Monitor><Mothers><Natural History><Neonatal Intensive Care Units><Newborn Intensive Care Units><Observation research><Observation study><Observational Study><Observational research><Outcome><Position><Positioning Attribute><Pregnant Women><Public Health><Registries><Research><Research Design><Research Institute><SARS-CoV-2><SARS-CoV2><SARS-associated coronavirus 2><SARS-coronavirus-2><SARS-related coronavirus 2><Safety><Severe acute respiratory syndrome coronavirus 2><Site><Study Type><Transmission><United States><Universities><Viral Shedding><Virus><Virus Shedding><Wuhan coronavirus><adulthood><children><childrens'><clinical data repository><clinical data warehouse><corona virus disease><corona virus disease 2019><corona virus disease 2019 epidemic><corona virus disease 2019 pandemic><coronavirus disease><coronavirus disease 2019><coronavirus disease 2019 epidemic><coronavirus disease 2019 pandemic><data curation><data harmonization><electronic data><enroll><epidemiologic><epidemiological><expectant mother><expecting mother><harmonized data><health care personnel><health care worker><health provider><health workforce><healthcare personnel><host response><immunoresponse><improved><infant outcome><infection rate><innovate><innovation><innovative><medical personnel><meta data><neonatal ICU><pandemic><pandemic disease><pregnant mothers><programs><rate of infection><response><study design><transmission process><treatment provider><youngster>