Laura Forastiere, PhD
Associate Professor of BiostatisticsCards
Additional Titles
Affiliated Faculty, Yale Institute for Global Health
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Titles
Associate Professor of Biostatistics
Affiliated Faculty, Yale Institute for Global Health
Biography
Laura Forastiere is an Associate Professor in the Department of Biostatistics at Yale School of Public Health. Her methodological research is focused on methods for assessing causal inference for evidence-based research, exploring the mechanisms underlying the effect of an intervention including causal pathways through intermediate variables or mechanisms of peer influence and spillover between connected units. Her research explores modeling, inferential, and other methodological issues that often arise in applied problems with complex clustered and network data, and standard statistical theory and methods are no longer adequate to support the goals of the analysis. Laura is eager to apply advanced statistical methodology to provide evidence on effective strategies to improve the health and wellbeing of vulnerable populations. She is particularly interested in exploring behavioral interventions that, relying on theories of behavioral economics and social phycology, exploit social interactions and peer influence among individuals. She is involved in many program evaluations and research studies in low- and middle-income countries on malaria, HIV and other STDs, maternal and child health, nutrition, cognitive development, health insurance and microcredit. Dr. Forastiere received her Ph.D. in statistics from the University of Florence (Italy) and postdoc training in statistics and biostatistics at Harvard University. Prior to joining the Department of Biostatistics at Yale School of Public Health, she was a Postdoctoral Associate in the Yale Institute for Network Science.
Appointments
Biostatistics
Associate Professor on TermPrimary
Other Departments & Organizations
Education & Training
- PhD
- University of Florence (2015)
Research
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Overview
Medical Research Interests
Public Health Interests
ORCID
0000-0003-3721-9826
Research at a Glance
Yale Co-Authors
Publications Timeline
Research Interests
Donna Spiegelman, ScD
Marcus Alexander, PhD, MD
Andrew DeWan, PhD, MPH
Kai Chen, PhD
Sten H. Vermund, MD, PhD
Luke Davis, MD
Causality
Global Health
Social Networking
Publications
2026
Discussion on ‘Causal inference with misspecified network interference structure’ by Bar Weinstein and Daniel Nevo
Fang F, Forastiere L. Discussion on ‘Causal inference with misspecified network interference structure’ by Bar Weinstein and Daniel Nevo. Biometrics 2026, 82: ujag027. PMID: 41725399, PMCID: PMC13017960, DOI: 10.1093/biomtc/ujag027.Peer-Reviewed Original ResearchCitations
2025
The role of cardiovascular disease as a mediator in mitigating the impact of ambient PM2.5 on dementia risk
Lin C, Zhang Y, DeWan A, Forastiere L, Chen K. The role of cardiovascular disease as a mediator in mitigating the impact of ambient PM2.5 on dementia risk. Environmental Epidemiology 2025, 9: e436. PMID: 41200148, PMCID: PMC12588692, DOI: 10.1097/ee9.0000000000000436.Peer-Reviewed Original ResearchCitationsAssessing spillover effects: Handling missing outcomes in network-based studies
Lee T, Buchanan A, Katenka N, Forastiere L, Halloran M, Nikolopoulos G. Assessing spillover effects: Handling missing outcomes in network-based studies. Statistical Methods In Medical Research 2025, 34: 2284-2301. PMID: 41056200, PMCID: PMC13045634, DOI: 10.1177/09622802251382586.Peer-Reviewed Original ResearchA Hypothetical PM2.5 Intervention for the Risk of Hospitalization for Cardiovascular Diseases
Lin C, Chu L, Liu R, Gasparrini A, DeWan A, Forastiere L, Chen K. A Hypothetical PM2.5 Intervention for the Risk of Hospitalization for Cardiovascular Diseases. JAMA Network Open 2025, 8: e2539862. PMID: 41148138, PMCID: PMC12569718, DOI: 10.1001/jamanetworkopen.2025.39862.Peer-Reviewed Original ResearchCitationsAltmetricSelecting subpopulations for causal inference in regression discontinuity designs
Forastiere L, Mattei A, Pescarini J, Barreto M, Mealli F. Selecting subpopulations for causal inference in regression discontinuity designs. The Annals Of Applied Statistics 2025, 19: 1801-1825. DOI: 10.1214/24-aoas1980.Peer-Reviewed Original ResearchCitationsDesign of egocentric network-based studies to estimate causal effects under interference
Fang J, Spiegelman D, Buchanan A, Forastiere L. Design of egocentric network-based studies to estimate causal effects under interference. Statistical Methods In Medical Research 2025, 34: 2034-2052. PMID: 40671608, PMCID: PMC12853655, DOI: 10.1177/09622802251357021.Peer-Reviewed Original ResearchCitationsAltmetricCognitive representations of social networks in isolated villages
Feltham E, Forastiere L, Christakis N. Cognitive representations of social networks in isolated villages. Nature Human Behaviour 2025, 9: 1737-1753. PMID: 40523958, PMCID: PMC12323711, DOI: 10.1038/s41562-025-02221-6.Peer-Reviewed Original ResearchCitationsAltmetricMental Health, Substance Use, and Tuberculosis Preventive Therapy in People With HIV: A Prospective Cohort Study
Johnson A, Chimoyi L, Shenoi S, Brault M, Forastiere L, Charalambous S, Chihota V, Davis J. Mental Health, Substance Use, and Tuberculosis Preventive Therapy in People With HIV: A Prospective Cohort Study. Open Forum Infectious Diseases 2025, 12: ofaf303. PMID: 40567997, PMCID: PMC12188208, DOI: 10.1093/ofid/ofaf303.Peer-Reviewed Original ResearchCitationsAltmetricEstimating the Effects of Hypothetical Ambient PM2.5 Interventions on the Risk of Dementia Using the Parametric g-Formula in the UK Biobank Cohort
Lin C, Liu R, Sutton C, DeWan A, Forastiere L, Chen K. Estimating the Effects of Hypothetical Ambient PM2.5 Interventions on the Risk of Dementia Using the Parametric g-Formula in the UK Biobank Cohort. Environmental Health Perspectives 2025, 133: 047007. PMID: 40062909, PMCID: PMC12010936, DOI: 10.1289/ehp14723.Peer-Reviewed Original ResearchCitationsAltmetricHETEROGENEOUS TREATMENT AND SPILLOVER EFFECTS UNDER CLUSTERED NETWORK INTERFERENCE
BARGAGLI-STOFFI F, Tortú C, Forastiere L. HETEROGENEOUS TREATMENT AND SPILLOVER EFFECTS UNDER CLUSTERED NETWORK INTERFERENCE. The Annals Of Applied Statistics 2025, 19: 28-55. PMID: 40642103, PMCID: PMC12245184, DOI: 10.1214/24-aoas1913.Peer-Reviewed Original ResearchCitations
Academic Achievements & Community Involvement
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Honors
honor Yale Global Health Spark Award
04/15/2023Yale University AwardYale Institute for Global Healthhonor Young Protagonist Researchers
11/15/2016International AwardEnte Cassa di Risparmio FirenzeDetailsItalyhonor Student Paper Award
08/03/2016National AwardHealth Policy Statistics Section - American Statistical AssociationDetailsUnited Stateshonor Thomas R. Ten Have Award
05/21/2014National AwardAtlantic Causal Inference ConferenceDetailsUnited States
News
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News
- September 03, 2024
Ariel Chao: a first in YSPH Biostatistics
- November 28, 2019
New Faculty Friday: Laura Forastiere, methodologist, statistician, world traveler
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