Laura Forastiere, PhD
Associate Professor of BiostatisticsCards
Additional Titles
Affiliated Faculty, Yale Institute for Global Health
Contact Info
About
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
Overview
Medical Subject Headings (MeSH)
ORCID
0000-0003-3721-9826
Research at a Glance
Yale Co-Authors
Publications Timeline
Research Interests
Sten H. Vermund, MD, PhD
Donna Spiegelman, ScD
Raul U. Hernandez-Ramirez, PhD
Ashley Hagaman, PhD, MPH
Emilie Egger
Frederick Lewis Altice, MD, MA
Global Health
Social Networking
Publications
2024
Maternal and child health intervention to promote behaviour change: a population-level cluster-randomised controlled trial in Honduras
Oles W, Alexander M, Negron R, Nelson J, Iriarte E, Airoldi E, Christakis N, Forastiere L. Maternal and child health intervention to promote behaviour change: a population-level cluster-randomised controlled trial in Honduras. BMJ Open 2024, 14: e060784. PMID: 38858139, PMCID: PMC11168147, DOI: 10.1136/bmjopen-2022-060784.Peer-Reviewed Original ResearchAltmetricMeSH Keywords and ConceptsConceptsCluster randomised controlled trialPrimary outcomeCounseling interventionChild health interventionsCommunity health workersProfessional care seekingBreast-feedingPromote behavior changeSecondary outcome measuresFacility birthsUmbilical cord careCare-seekingNewborn healthNewborn careHealth workersHealth facilitiesEndline surveyHealth interventionsEducational interventionChild healthCord careHome settingCaring behaviorsSecondary outcomesSustained educational interventionsAssessing Direct and Spillover Effects of Intervention Packages in Network-randomized Studies
Buchanan A, Hernández-Ramírez R, Lok J, Vermund S, Friedman S, Forastiere L, Spiegelman D. Assessing Direct and Spillover Effects of Intervention Packages in Network-randomized Studies. Epidemiology 2024, 35: 481-488. PMID: 38709023, DOI: 10.1097/ede.0000000000001742.Peer-Reviewed Original ResearchConceptsIntervention packageEffectiveness of interventional packageImprove intervention deliveryPeer education interventionHIV prevention trialsPeer educator trainingMarginal structural modelsPublic health impactHIV risk behaviorsIntervention deliveryIntervention NetworkEducational interventionParticipant visitsPrevention trialsFollow-up visitRisk behaviorsHealth impactsInterventionEducational trainingParticipantsSpillover effectsVisitsHIVExposed networksPeerCausal inference on networks under continuous treatment interference
Forastiere L, Del Prete D, Sciabolazza V. Causal inference on networks under continuous treatment interference. Social Networks 2024, 76: 88-111. DOI: 10.1016/j.socnet.2023.07.005.Peer-Reviewed Original ResearchCitationsAltmetricConcepts
2023
Doubly Robust Estimator for Off-Policy Evaluation with Large Action Spaces
Shimizu T, Forastiere L. Doubly Robust Estimator for Off-Policy Evaluation with Large Action Spaces. 2023, 00: 992-997. DOI: 10.1109/ssci52147.2023.10372057.Peer-Reviewed Original ResearchOverall, Direct, Spillover, and Composite Effects of Components of a Peer-Driven Intervention Package on Injection Risk Behavior Among People Who Inject Drugs in the HPTN 037 Study
Hernández-Ramírez R, Spiegelman D, Lok J, Forastiere L, Friedman S, Latkin C, Vermund S, Buchanan A. Overall, Direct, Spillover, and Composite Effects of Components of a Peer-Driven Intervention Package on Injection Risk Behavior Among People Who Inject Drugs in the HPTN 037 Study. AIDS And Behavior 2023, 28: 225-237. PMID: 37932493, PMCID: PMC11062514, DOI: 10.1007/s10461-023-04213-x.Peer-Reviewed Original ResearchCitationsAltmetricConceptsInjection risk behaviorsPeer education interventionRisk behaviorsClinical trial registrationSubsequent risk behaviorsTRIAL REGISTRATIONOutcome ratesSecondary data analysisIndex individualsRoutine evaluationIntervention componentsIntervention NetworkMixed effects modelsIntervention packageGroups/networksPeer education trainingPeer educatorsOverall rateInterventionPeer educationEffects modelTraining sessionsDrugsControl conditionBehavioral measuresEstimating Causal Effects of HIV Prevention Interventions with Interference in Network-based Studies among People Who Inject Drugs.
Lee T, Buchanan A, Katenka N, Forastiere L, Halloran M, Friedman S, Nikolopoulos G. Estimating Causal Effects of HIV Prevention Interventions with Interference in Network-based Studies among People Who Inject Drugs. The Annals Of Applied Statistics 2023, 17: 2165-2191. PMID: 38250709, PMCID: PMC10798667, DOI: 10.1214/22-aoas1713.Peer-Reviewed Original ResearchCitationsMass gatherings for political expression had no discernible association with the local course of the COVID-19 pandemic in the USA in 2020 and 2021
Feltham E, Forastiere L, Alexander M, Christakis N. Mass gatherings for political expression had no discernible association with the local course of the COVID-19 pandemic in the USA in 2020 and 2021. Nature Human Behaviour 2023, 7: 1708-1728. PMID: 37524931, DOI: 10.1038/s41562-023-01654-1.Peer-Reviewed Original ResearchCitationsAltmetricEstimating causal effects of community health financing via principal stratification
Noirjean S, Biggeri M, Forastiere L, Mealli F, Nannini M. Estimating causal effects of community health financing via principal stratification. Statistical Methods & Applications 2023, 32: 1317-1350. DOI: 10.1007/s10260-023-00706-0.Peer-Reviewed Original ResearchImplementation of a Hardware-Assisted Bluetooth-Based COVID-19 Tracking Device in a High School: Mixed Methods Study
Li D, Shelby T, Brault M, Manohar R, Vermund S, Hagaman A, Forastiere L, Caruthers T, Egger E, Wang Y, Manohar N, Manohar P, Davis J, Zhou X. Implementation of a Hardware-Assisted Bluetooth-Based COVID-19 Tracking Device in a High School: Mixed Methods Study. JMIR Formative Research 2023, 7: e39765. PMID: 36525333, PMCID: PMC10131711, DOI: 10.2196/39765.Peer-Reviewed Original ResearchAltmetricConceptsContact tracingPilot implementation studyPublic health toolMixed-methods evaluationTechnical difficultiesSignificant numberQualitative focus group discussionsClose contactInfectious diseasesHealth toolsLarge-scale pandemicMixed-methods studyImplementation outcomesCOVID-19Significant differencesImplementation studyEmotional reassuranceFocus group discussionsMost contactMixed methods designMethods studySustained useCase interviewsMaintenance frameworkHabitsAssessing Principal Causal Effects Using Principal Score Methods
Mattei A, Forastiere L, Mealli F. Assessing Principal Causal Effects Using Principal Score Methods. 2023, 313-348. DOI: 10.1201/9781003102670-17.Peer-Reviewed Original ResearchCitations
Academic Achievements & Community Involvement
honor Yale Global Health Spark Award
Yale University AwardYale Institute for Global HealthDetails04/15/2023honor Young Protagonist Researchers
International AwardEnte Cassa di Risparmio FirenzeDetails11/15/2016Italyhonor Student Paper Award
National AwardHealth Policy Statistics Section - American Statistical AssociationDetails08/03/2016United Stateshonor Thomas R. Ten Have Award
National AwardAtlantic Causal Inference ConferenceDetails05/21/2014United States
News
News
- September 03, 2024
Ariel Chao: a first in YSPH Biostatistics
- November 28, 2019
New Faculty Friday: Laura Forastiere, methodologist, statistician, world traveler