What is she best known for?
The fields of study she is best known for:
- Statistics
- Internal medicine
- Disease
Francesca Dominici spends much of her time researching Air pollution, Environmental health, Particulates, Statistics and Air pollutants.
Her research in Air pollution intersects with topics in Air quality index, Pollution, Ozone and Morbidity mortality.
Francesca Dominici combines subjects such as Mortality rate, Particulate air pollution, Pollutant and Environmental protection with her study of Air quality index.
Her study in Environmental health is interdisciplinary in nature, drawing from both Cause of death, Life expectancy, Public health, Socioeconomic status and Fine particulate.
She has researched Particulates in several fields, including Seasonality, Demography and Environmental exposure.
Her research in Air pollutants focuses on subjects like Adverse health effect, which are connected to Air pollution in the United States and Data collection.
Her most cited work include:
- Fine Particulate Air Pollution and Mortality in 20 U.S. Cities, 1987–1994 (1952 citations)
- Fine Particulate Air Pollution and Hospital Admission for Cardiovascular and Respiratory Diseases (1805 citations)
- Ozone and short-term mortality in 95 US urban communities, 1987-2000. (891 citations)
What are the main themes of her work throughout her whole career to date?
The scientist’s investigation covers issues in Air pollution, Environmental health, Statistics, Econometrics and Particulates.
Her studies deal with areas such as Air quality index, Pollutant and Pollution as well as Air pollution.
Her studies in Environmental health integrate themes in fields like Cohort study and Public health.
Her work on Confounding, Bayesian probability, Nonparametric statistics and Linear regression as part of general Statistics research is frequently linked to Context, bridging the gap between disciplines.
As part of the same scientific family, Francesca Dominici usually focuses on Confounding, concentrating on Epidemiology and intersecting with Demography.
The various areas that Francesca Dominici examines in her Econometrics study include Bayesian inference and Time series.
She most often published in these fields:
- Air pollution (30.13%)
- Environmental health (25.32%)
- Statistics (18.99%)
What were the highlights of her more recent work (between 2018-2021)?
- Environmental health (25.32%)
- Air pollution (30.13%)
- Causal inference (10.63%)
In recent papers she was focusing on the following fields of study:
Francesca Dominici mainly focuses on Environmental health, Air pollution, Causal inference, Demography and Confidence interval.
Her work deals with themes such as Cohort study, Pollutant, Public health and 2019-20 coronavirus outbreak, which intersect with Environmental health.
Her Air pollution research integrates issues from Particulates, Epidemiology and Ozone.
Her Causal inference research is multidisciplinary, incorporating perspectives in Matching, Covariate and Inference.
Her Demography study incorporates themes from Storm, Medicaid, Term effect, Hazard ratio and Causal model.
Her Confidence interval research includes themes of Mortality rate, Tropical cyclone and Proportional hazards model.
Between 2018 and 2021, her most popular works were:
- Exposure to air pollution and COVID-19 mortality in the United States: A nationwide cross-sectional study. (500 citations)
- Aggregated mobility data could help fight COVID-19. (166 citations)
- All Models are Wrong, but Many are Useful: Learning a Variable's Importance by Studying an Entire Class of Prediction Models Simultaneously (125 citations)
In her most recent research, the most cited papers focused on:
- Statistics
- Internal medicine
- Disease
Her scientific interests lie mostly in Air pollution, Environmental health, Causal inference, Confidence interval and MEDLINE.
The various areas that she examines in her Air pollution study include Observational study, Mortality rate, Natural resource economics, Ozone and Process.
Her studies deal with areas such as Particulates, Particulate pollution, Pollutant and Cardiovascular outcomes as well as Environmental health.
Her Particulates research focuses on subjects like Global health, which are linked to Incidence.
Her Causal inference research is multidisciplinary, incorporating perspectives in Propensity score matching, Linear regression and Confounding.
The Confidence interval study combines topics in areas such as Epidemiology and Fine particulate.
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