Antonio Gasparrini BSc Mbiol MSc PhD
About Antonio Gasparrini
Dr Antonio Gasparrini is a biostatistician and epidemiologist with interests in methodology, substantive applications in various research topics, and software development
- Antonio Gasparrini's Contacts
- Room 213
- 15-17 Tavistock Place
- WC1H 9SH
- T: 0044 (0)20 79272406
Dr Gasparrini graduated in in Biology at the University of Florence (Italy) in 2003. He completed a MSc in Biostatistics at the University of Bologna in 2005 and a 3-years post-graduate School of Biometry and Medical Statistics at the University of Milan in 2009. He was awarded a PhD on Medical Statistics at LSHTM in September 2011, with a thesis on statistical methods for studying temperature-health associations. Dr Gasparrini worked as an epidemiologist and statistician at the Centre for Study and Prevention of Cancer (CSPO) in Florence, before joining LSHTM in 2007. Since then he has been part of the Department of Medical Statistics and currently of the Department of Social and Environmental Health Research.
- Department of Social and Environmental Health Research
- Faculty of Epidemiology and Population Health
- Faculty of Public Health and Policy
Dr Gasparrini co-organizes the Statistical Computing module of the MSc in Medical Statistics, and coordinates workshops on the R software for the Talent and Educational Development (LSHTM staff) and Transferrable Skills Programme (LSHTM research degree students). He is responsible for lecture and practical sessions on Time Series Analysis within the Environmental Epidemiology module of the MSc in Public Health, and within the Advanced Statistical Modelling module of the MSc in Medical Statistics. Dr Gasparrini is also a Lecture Speaker and Practical Group Leader in the Basic Statistics module of the MSc in Public Health.
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Dr Gasparrini’s interests encompass various research areas in epidemiology and public health evaluation, from methodology, substantive analyses in different research topics, and software implementation. His methodological work focuses on the development of study designs and statistical methods, applied in particular to time series analysis, quasi-experimental studies, and survival data. Dr Gasparrini has contributed to the development and extensions of a number of statistical techniques, such as distributed lag models, smoothing methods and meta-analytical models. His substantive research topics cover several of areas, from investigations of the health effects of environmental or occupational factors to evaluation of public health interventions. Dr Gasparrini is a strong advocate of open science and reproducible research, and has contributed with the implementation of statistical methods in freely-available software and with release of code in public repositories. His current research focuses on studies on the impact of weather and climate change on health.
Dr Gasparrini is a founding member of the Centre for Statistical Methodology, which promotes research and training on statistical methods within LSHTM, and the co-ordinator for two themes (time series and statistical computing). In particular, he is responsible for the activities of the Centre about the R software. He previously coordinated the Environmental and Health Research Group (EHRG).
- Climate change
- Environmental Health
- Health impact analysis
- Impact evaluation
- Public health
- Statistical methods
Disease and Health Conditions
- Cardiovascular disease
- Kidney disease
- East Asia & Pacific (all income levels)
- European Union
- Latin America & Caribbean (all income levels)
- North America
- Korea, Rep.
- South Africa
- United Kingdom
- United States
- Air Pollution
- Analysis Of Longitudinal Data
- Big Data
- Centre for Statistical Methodology
- Computational statistics
- Electronic health records
- Epidemiological Methods
- Health Risk Assessment
- Interrupted time series analysis
- Longitudinal And Survival Data
- Longitudinal Data
- Multi Centre Studies
- Occupational Epidemiology
- R statistical language
- Statistical methodology
- Statistical modelling
- Survival Analysis
- Time Series
A penalized framework for distributed lag non-linear models.
Gasparrini, A. ; Scheipl, F. ; Armstrong, B. ; Kenward, M.G. ;
Interrupted time series regression for the evaluation of public health interventions: a tutorial.
Lopez Bernal, J.; Cummins, S.; Gasparrini, A.;
Int J Epidemiol, 2016;
Modelling lagged associations in environmental time series data: a simulation study.
Temporal Variation in Heat-Mortality Associations: A Multicountry Study.
Gasparrini, A.; Guo, Y.; Hashizume, M.; Kinney, P.L.; Petkova, E.P.; Lavigne, E.; Zanobetti, A.; Schwartz, J.D.; Tobias, A.; Leone, M.; Tong, S.; Honda, Y.; Kim, H.; Armstrong, B.G.;
Environ Health Perspect, 2015; 123(11):1200-7
Mortality risk attributable to high and low ambient temperature: a multicountry observational study.
Gasparrini, A.; Guo, Y.; Hashizume, M.; Lavigne, E.; Zanobetti, A.; Schwartz, J.; Tobias, A.; Tong, S.; Rocklöv, J.; Forsberg, B.; Leone, M.; De Sario, M.; Bell, M.L.; Guo, Y.L.; Wu, C.F.; Kan, H.; Yi, S.M.; de Sousa Zanotti Stagliorio Coelho, M.; Saldiva, P.H.; Honda, Y.; Kim, H.; Armstrong, B.;
Lancet, 2015; 386(9991):369-75
Multivariate meta-analysis for non-linear and other multi-parameter associations.
Gasparrini, A.; Armstrong, B.; Kenward, M.G.;
Stat Med, 2012; 31(29):3821-39
Distributed Lag Linear and Non-Linear Models in R: The Package dlnm.
J Stat Softw, 2011; 43(8):1-20
Distributed lag non-linear models.
Gasparrini, A.; Armstrong, B.; Kenward, M.G.;
Stat Med, 2010; 29(21):2224-34
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