Epidemiology and Data Management Unit
Established in 2022
Emily E. Ricotta, Ph.D., M.Sc. (She/Her/Hers)
Chief, Epidemiology and Data Management Unit
Independent Research Scholar
Contact: For contact information, search the NIH Enterprise Directory.
Major Areas of Research
- Infectious disease epidemiology
- COVID-19
- Invasive fungal infections
- Antimicrobial resistance
- Ebola
- Malaria
- Data management and science
- Non-randomized study design
- Data collection and standardization
- Epidemiologic and statistical analysis including machine learning, multivariable modeling, and geospatial analysis
- Data visualization
- Electronic medical record use and management
Program Description
Dr. Emily Ricotta is an Independent Research Scholar in the Division of Intramural Research at the National Institute of Allergy and Infectious Diseases, where she leads the Epidemiology and Data Management Unit (EDMU). The EDMU focuses on risk factors and transmission of infectious diseases of public health importance as well as the standardization of protocols for study development and data management of nonrandomized, clinical cohort studies to enhance the efficiency and reproducibility of infectious disease research, particularly during emerging infectious disease outbreaks.
Nonrandomized, observational population studies play a critical role in evaluating health outcomes after exposures of interest such as an infectious disease, an immune disorder, or a particular medical intervention. The strength of these studies is that, when well-designed and executed, they can be more representative of the exposure mechanism and population under study than a randomized control trial (RCT), which is considered the gold standard of medical research. However, while efforts have been made to standardize RCT protocols during infectious disease outbreaks, and for disease treatment in general, protocol standardization of nonrandomized studies is currently lacking. This results in missed opportunities for data and sample collection arising from slow start-up due to regulatory issues or disorganization, especially during emergent situations such as infectious disease outbreaks like Ebola or COVID-19, and problems with the data that is collected. The Epidemiology and Data Management Unit therefore aims to create and implement master protocols that share key elements of study design, thus improving data collection in observational studies and increasing the utility of existing data collection efforts.
The Epidemiology and Data Management Unit also leads and collaborates on studies involving understanding risk factors and transmission of infectious diseases, including leading NIAID's study evaluating the immune response to COVID-19 vaccines in individuals with immune disorders. The members of the EDM Unit are available to collaborate on infectious disease-related studies from design through data analysis.
Biography
Education
Ph.D., 2018, Swiss Tropical and Public Health Institute, University of Basel, Switzerland
M.Sc., 2012, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
Dr. Emily Ricotta received her Ph.D. in epidemiology in 2018 from the Swiss Tropical and Public Health Institute at the University of Basel where her research focused on how human behavior impacts the uptake and use of malaria prevention methods, specifically bed nets. Her M.Sc. in molecular microbiology and immunology was awarded in 2012 by the Johns Hopkins Bloomberg School of Public Health for her work on household-level risk factors for malaria transmission. Dr. Ricotta has over fifteen years of research experience in epidemiology and molecular microbiology working with a variety of human pathogens and has participated in global public health program monitoring and evaluation, policy development, and scientific advocacy. In addition to research, she teaches epidemiology, biostatistics, and clinical research methods to graduate students at George Washington University. In March 2019, she was selected to become an Emerging Leaders in Biosecurity Initiative Fellow by the Johns Hopkins Center for Health Security.
Clinical Studies
Selected Publications
Zendt M,* Bustos Carrillo FA,* Kelly S, Saturday T, DeGrange M, Ginigeme A, Wu L, Callier V, Ortega-Villa A, Bugal K, Khil P, Osei G, Regmi P, Anderson V, Daub J, DiMaggio T, Kreuzburg S, Pfister J, Treat J, Ulrick J, Faust M, Karkanitsa M, Sadtler K, Kalish H, Kuhns D, Long Priel D, Fink DL, Tsang JS, Sparks R, Uzel G, Zerbe CS, Delmonte OM, Bergerson JRE, Das S, Freeman AF, Lionakis MS, Van Doremalen N, Munster V, Notarangelo LD, Holland SM, Ricotta EE. Immune response to COVID-19 vaccines in people with immunodeficiencies. Manuscript accepted to Science Advances. Preprint available: Research Square; doi: 10.21203/rs.3.rs-2514984/v1.
Ricotta EE, Rid A, IG Cohen, Evans NG. Observational studies must be reformed before the next pandemic. Nat Med (2023). doi: 10.1038/s41591-023-02375-8. PMID: 37286807.
Mayer L, Lionakis MS, Kadri SS, Evans NG, Prevots DR, Ricotta EE. Assessment of a machine learning model to determine species and site-specific risk factors for invasive candidiasis in US hospitals, 2009-2017. Open Forum Infec Dis. 2022 Aug 3; ofac401. doi: 10.1093/ofid/ofac401. PMID: 36004317.
Matson MJ*, Ricotta EE*, Feldmann F, Massaquoi M, Sprecher A, Guiliani R, Edwards JK, Rosenke K, de Wit E, Feldmann H, Chertow DS, Munster VJ. Viral Load in Non-Surviving Liberian Ebola Virus Disease Patients Is Underestimated by Diagnostic qRT-PCR: A Retrospective Observational Study. Lancet Microbe. 2022 May 23. doi: 10.1016/S2666-5247(22)00065-9.
Abers MS*, Delmonte OM*, Ricotta EE*, Fintzi J*, Fink DL, de Jesus AAA, Zarember KA, Alehashemi S, Oikonomou V, Desai JV, Canna SW, Shakoory B, Dobbs K, Imberti L, Sottini A, Quiros-Roldan E, Castelli F, Rossi C, Brugnoni D, Biondi A, Bettini LR, D'Angio' M, Bonfanti P, Castagnoli R, Montagna D, Licari A, Marseglia GL, Gliniewicz EF, Shaw E, Kahle DE, Rastegar AT, Stack M, Myint-Hpu K, Levinson SL, DiNubile MJ, Chertow DW, Burbelo PD, Cohen JI, Calvo KR, Tsang JS; NIAID COVID-19 Consortium, Su HC, Gallin JI, Kuhns DB, Goldbach-Mansky R, Lionakis MS, Notarangelo LD. An immune-based biomarker signature is associated with mortality in COVID-19 patients. JCI Insight. 2021 Jan 11;6(1):e144455.
Additional Information
- Women Scientists Advisory Committee 30th Anniversary Lecture (Dr. Ricotta begins at minute 39)
- Training and Employment Opportunities Podcast episode: “Episode 7: Dr. Emily Ricotta COVID-19 Vaccine questions” Cystinosis Research Network. “Cystinosis Rare: A Journey into the Unknown Podcast. September 21, 2021.
- Interview: “Should People With Immune Problems Get Third Vaccine Doses?” Apoorva Mandavilli. New York Times. July 4, 2021.
- Interview: “Covid vaccines may not protect people with immune disorders. NIH trial seeks answers.” Akshay Syal. NBC News. May 13, 2021.
- Interview: "Incidence of non-bloodstream invasive candidiasis increases in US". Caitlyn Stulpin. Infectious Disease News. August 23, 2020.
- Interview: “Why COVID-19 death predictions will always be wrong.” Alexandra Appolonia and Victoria Barranco. Business Insider/Science Insider. April 29, 2020.
Research Networks
NIAID DIR Epidemiology
Training Opportunities
The Epidemiology and Data Management Unit is committed to training and enhancing diversity in public health and clinical research. We provide research opportunities to all levels of trainees, from post-baccalaureate to postdoctoral. In addition, we collaborate with researchers, science communicators, and policy makers from academia, government, and international organizations to provide trainees with opportunities to conduct research while learning about being successful, well-rounded scientists. Affiliated training programs include the Intramural Research Training Award, Presidential Management Fellowship, and the ORISE Emerging Leaders in Data Science and Technologies Fellowship.
Research Group
The Epidemiology and Data Management Unit studies risk factors and transmission of infectious diseases, including immune response to COVID-19 vaccines in individuals with immune disorders. We focus on standardization of protocols and data management of nonrandomized, clinical cohort studies to enhance efficiency and reproducibility of research.