Elaine O. Nsoesie

About

Elaine O. Nsoesie is an Associate Professor in the Department of Global Health at the Boston University School of Public Health. She is an internationally recognized data scientist and a leading voice on the use of data and technology to advance health equity. Her expertise includes applying data science methods such as machine learning and artificial intelligence, utilizing data from non-traditional public health sources like mobile phones, satellites, and social media to address major global health challenges. She approaches health equity from multiple angles, including increasing representation of underrepresented communities in data science, addressing bias in health data and algorithms, and using data and policy to promote racial equity. Nsoesie has contributed significantly to the field through her leadership roles, including serving as a Data Science Faculty Fellow, a founding faculty member of the Boston University Faculty of Computing and Data Sciences, and a program lead and senior advisor to the NIH AIM-AHEAD Program. She has led projects such as the Racial Data Tracker at the Boston University Center for Antiracist Research and co-edited the book 'Urban Health in Africa.' Her work has involved collaborations with local health departments, international organizations like UNICEF and UNDP, and serving as a Data & Innovation Fellow in Sierra Leone. She has published extensively, received numerous awards, and is known for effectively communicating complex scientific…

Research topics

• Computer Security
• Sociology
• Computer Science
• Artificial Intelligence
• Data Mining
• Medicine
• Machine Learning
• Nursing
• Socioeconomics
• Economics

Selected publications

• Five insights from the Global Burden of Disease Study 2019

  The Lancet · 2020 · 678 citations

  DOI

• Neighbourhood income and physical distancing during the COVID-19 pandemic in the United States

  Nature Human Behaviour · 2020 · 365 citations

  DOI

• Privacy-first health research with federated learning

  npj Digital Medicine · 2021 · 177 citations

  Privacy protection is paramount in conducting health research. However, studies often rely on data stored in a centralized repository, where analysis is done with full access to the sensitive underlying content. Recent advances in federated learning enable building complex machine-learned models that are trained in a distributed fashion. These techniques facilitate the calculation of research study endpoints such that private data never leaves a given device or healthcare system. We show-on a di…

  DOI

• The overlapping global distribution of dengue, chikungunya, Zika and yellow fever

  Nature Communications · 2025-04-10 · 97 citations

  articleOpen access

  Arboviruses transmitted mainly by Aedes (Stegomyia) aegypti and Ae. albopictus, including dengue, chikungunya, and Zika viruses, and yellow fever virus in urban settings, pose an escalating global threat. Existing risk maps, often hampered by surveillance biases, may underestimate or misrepresent the true distribution of these diseases and do not incorporate epidemiological similarities despite shared vector species. We address this by generating new global environmental suitability maps for Aed…

  PublisherOA PDFDOI

• COVID-19 Mortality by Race and Ethnicity in US Metropolitan and Nonmetropolitan Areas, March 2020 to February 2022

  JAMA Network Open · 2023-05-02 · 86 citations

  articleOpen access

  Importance: Prior research has established that Hispanic and non-Hispanic Black residents in the US experienced substantially higher COVID-19 mortality rates in 2020 than non-Hispanic White residents owing to structural racism. In 2021, these disparities decreased. Objective: To assess to what extent national decreases in racial and ethnic disparities in COVID-19 mortality between the initial pandemic wave and subsequent Omicron wave reflect reductions in mortality vs other factors, such as the…

  PublisherOA PDFDOI

Recent grants

• A Framework for Integrating Multiple Data Sources for Modeling and Forecasting of Infectious Diseases

  NIH · $322k · 2014–2018

• An Approach for Estimating Foodborne Illnesses and Assessing Risk Factors

  NIH · $1.2M · 2015–2019

Frequent coauthors

• John S. Brownstein

  Boston Children's Hospital

  195 shared

• Simon I Hay

  62 shared

• Dan J. Stein

  South African Medical Research Council

  33 shared

• David M. Pigott

  31 shared

• Jared B. Hawkins

  29 shared

• Alize J Ferrari

  28 shared

• Sumiko R. Mekaru

  Boston University

  28 shared

• Nina Cesare

  Boston University

  26 shared

Awards & honors

• NIH Director's Award
• Mozilla Rise25 Award
• Boston University School of Public Health Excellence in Publ…
• Boston Congress of Public Health’s Health Innovators to Watc…

Similar researchers at Boston University

• Charles R Horsburghh-96
• Sydney B Rosenh-71
• William B. MacLeodh-53