Featured Publications
Quasi-experimental methods for pharmacoepidemiology: difference-in-differences and synthetic control methods with case studies for vaccine evaluation
Kennedy-Shaffer L. Quasi-experimental methods for pharmacoepidemiology: difference-in-differences and synthetic control methods with case studies for vaccine evaluation. American Journal Of Epidemiology 2024, 193: 1050-1058. PMID: 38456774, PMCID: PMC11228849, DOI: 10.1093/aje/kwae019.Peer-Reviewed Original ResearchConceptsSynthetic control methodDifference-in-differencesHealth policyCase studyAverage treatment effectQuasi-experimental methodPolicyQuasi-experimental designWeight assumptionPopulation-level effectsTime trendsStudy designSources of evidenceConfounding factorsEvaluation studiesPharmacoepidemiologyTarget estimandAbsence of contaminationPublic Health Impacts of Vaccines for COVID-19 and Beyond: Opportunities to Overcome Technical and Regulatory Barriers for Randomized Trials.
Kennedy-Shaffer L. Public Health Impacts of Vaccines for COVID-19 and Beyond: Opportunities to Overcome Technical and Regulatory Barriers for Randomized Trials. American Journal Of Public Health 2023, 113: 778-785. PMID: 37104734, PMCID: PMC10262256, DOI: 10.2105/ajph.2023.307302.Peer-Reviewed Original ResearchConceptsPublic health impactCOVID-19 pandemicPopulation healthEvidence baseCOVID-19Health impactsInfectious disease outbreaksCommunity levelRandomized trialsIndividual levelRegulatory barriersPivotal trialsClinical benefitTrialsClinical trialsVaccine trialsPrevent infectionStrategic deploymentVaccineHealthThe required size of cluster randomized trials of nonpharmaceutical interventions in epidemic settings
Sheen J, Haushofer J, Metcalf C, Kennedy‐Shaffer L. The required size of cluster randomized trials of nonpharmaceutical interventions in epidemic settings. Statistics In Medicine 2022, 41: 2466-2482. PMID: 35257398, PMCID: PMC9111156, DOI: 10.1002/sim.9365.Peer-Reviewed Original ResearchConceptsCluster randomized trialEffectiveness of interventionsSample sizeRandomized trialsPlanning such trialsApproximate sample size formulaeReduce transmissionEffect sizeNonpharmaceutical interventionsInfectious disease outbreaksObservational studyInterventionEpidemic settingsSample size methodsAdequate powerSARS-CoV-2 pandemicSARS-CoV-2 transmissionSample size formulaTested individualsSimulated bankTreatment effectsTrialsCommunity transmissionOutbreak settingsSize formulaEstimating Vaccine Efficacy Against Transmission via Effect on Viral Load
Kennedy-Shaffer L, Kahn R, Lipsitch M. Estimating Vaccine Efficacy Against Transmission via Effect on Viral Load. Epidemiology 2021, 32: 820-828. PMID: 34469363, PMCID: PMC8478108, DOI: 10.1097/ede.0000000000001415.Peer-Reviewed Original ResearchConceptsViral load measurementsVaccine efficacyViral loadMeasure of vaccine efficacyRandomized controlled trialsEstimates of vaccine efficacyVirological testingAsymptomatic infectionVaccine effectivenessSevere diseaseControlled trialsViral variantsSARS-CoV-2Estimate efficacyEfficacySARS-CoV-2 pandemicVaccineLoad measurementsInfectionVirus transmissionEstimating epidemiologic dynamics from cross-sectional viral load distributions
Hay J, Kennedy-Shaffer L, Kanjilal S, Lennon N, Gabriel S, Lipsitch M, Mina M. Estimating epidemiologic dynamics from cross-sectional viral load distributions. Science 2021, 373: eabh0635. PMID: 34083451, PMCID: PMC8527857, DOI: 10.1126/science.abh0635.Peer-Reviewed Original ResearchSnowball Sampling Study Design for Serosurveys Early in Disease Outbreaks
Kennedy-Shaffer L, Qiu X, Hanage W. Snowball Sampling Study Design for Serosurveys Early in Disease Outbreaks. American Journal Of Epidemiology 2021, 190: 1918-1927. PMID: 33831177, PMCID: PMC8083564, DOI: 10.1093/aje/kwab098.Peer-Reviewed Original ResearchPerfect as the enemy of good: tracing transmissions with low-sensitivity tests to mitigate SARS-CoV-2 outbreaks
Kennedy-Shaffer L, Baym M, Hanage W. Perfect as the enemy of good: tracing transmissions with low-sensitivity tests to mitigate SARS-CoV-2 outbreaks. The Lancet Microbe 2021, 2: e219-e224. PMID: 33748803, PMCID: PMC7954468, DOI: 10.1016/s2666-5247(21)00004-5.Peer-Reviewed Original ResearchStatistical Properties of Stepped Wedge Cluster-Randomized Trials in Infectious Disease Outbreaks
Kennedy-Shaffer L, Lipsitch M. Statistical Properties of Stepped Wedge Cluster-Randomized Trials in Infectious Disease Outbreaks. American Journal Of Epidemiology 2020, 189: 1324-1332. PMID: 32648891, PMCID: PMC7604531, DOI: 10.1093/aje/kwaa141.Peer-Reviewed Original ResearchConceptsWedge trialsParallel-arm cluster-randomized trialsStepped wedge cluster randomized trialStatistical propertiesCluster randomized trialStatistical disadvantageStepped wedge trialIndividual randomizationInfectious disease outbreaksCluster randomized designEvaluation of interventionsEvaluate various designsTrial designDetect intervention effectsWedge designRandomized controlled trialsIntervention effectsEffect estimatesControlled trialsParallel-armEpidemic settingsLogistical factorsAdequate powerInfectious disease incidenceRandomized trialsSample size estimation for stratified individual and cluster randomized trials with binary outcomes
Kennedy‐Shaffer L, Hughes M. Sample size estimation for stratified individual and cluster randomized trials with binary outcomes. Statistics In Medicine 2020, 39: 1489-1513. PMID: 32003492, PMCID: PMC7247053, DOI: 10.1002/sim.8492.Peer-Reviewed Original ResearchConceptsCluster randomized trialIndividual randomized trialsIntracluster correlation coefficientSample size estimationBinary outcomesRandomized trialsSample sizeStratify individualsLogistic regressionSample size reductionProbabilities of eventsContinuous outcomesSize estimationStratified trialCorrelation coefficientOutcomesTrialsEstimationProbabilityNovel methods for the analysis of stepped wedge cluster randomized trials
Kennedy‐Shaffer L, de Gruttola V, Lipsitch M. Novel methods for the analysis of stepped wedge cluster randomized trials. Statistics In Medicine 2019, 39: 815-844. PMID: 31876979, PMCID: PMC7247054, DOI: 10.1002/sim.8451.Peer-Reviewed Original ResearchConceptsSW-CRTsRobust inference proceduresStepped wedge cluster randomized trialParametric model assumptionsModel assumptionsCluster randomized trialNonparametric analysis methodsTheoretical propertiesInference proceduresNonparametric methodsIncorporating covariatesRestrictive assumptionsAssumptionsEffects modelControl approachFeasibility advantagesSynthetic control approachIncreased powerRandomized trialsIntervention clustersMixed effects modelsEstimationTime trendsInterventionModel-based approach
2023
Anastomotic Stricture After Minimally Invasive Esophagectomy
Feingold P, Bryan D, Kuckelman J, Kennedy-Shaffer L, Wang V, Deeb A, Wee J, Jaklitsch M, Marshall M. Anastomotic Stricture After Minimally Invasive Esophagectomy. The Annals Of Thoracic Surgery 2023, 116: 712-719. PMID: 37244601, DOI: 10.1016/j.athoracsur.2023.05.013.Peer-Reviewed Original ResearchConceptsMinimally invasive esophagectomyInvasive esophagectomyAnastomotic strictureMinimally invasive esophagectomy approachesUnivariate analysis of patientsSingle-institution retrospective reviewAssociated with strictureAnalysis of patientsProportion of patientsDay of surgeryPercentage of patientsAssociated with anastomotic strictureTumor histologyTumor stageAnastomotic dilatationInitial dilationSurgeon variablesUnivariate analysisMultivariate analysisPrimary outcomeEsophagectomyStricturePatientsRisk factorsImprove outcomesComparative performance of between-population vaccine allocation strategies with applications for emerging pandemics
Joshi K, Rumpler E, Kennedy-Shaffer L, Bosan R, Lipsitch M. Comparative performance of between-population vaccine allocation strategies with applications for emerging pandemics. Vaccine 2023, 41: 1864-1874. PMID: 36697312, PMCID: PMC10075509, DOI: 10.1016/j.vaccine.2022.12.053.Peer-Reviewed Original Research
2021
Power and sample size calculations for cluster randomized trials with binary outcomes when intracluster correlation coefficients vary by treatment arm
Kennedy-Shaffer L, Hughes M. Power and sample size calculations for cluster randomized trials with binary outcomes when intracluster correlation coefficients vary by treatment arm. Clinical Trials 2021, 19: 42-51. PMID: 34879711, PMCID: PMC8883478, DOI: 10.1177/17407745211059845.Peer-Reviewed Original ResearchConceptsWorking correlation structureIntracluster correlation coefficientIntracluster correlation coefficient valuesAsymptotic varianceCorrelation structureClustered binary dataSample size requirementsSample size calculationCluster-level covariatesExchangeable working correlation structureCluster randomized trialModest-sized clustersBinary covariateSize calculationBinary outcomesBinary dataDistribution of cluster sizesFormulaCluster size distributionSize requirementsCovariatesEquationsSample sizeCluster sizeRandomized trialsJoint Estimation of Generation Time and Incubation Period for Coronavirus Disease 2019
Lau Y, Tsang T, Kennedy-Shaffer L, Kahn R, Lau E, Chen D, Wong J, Ali T, Wu P, Cowling B. Joint Estimation of Generation Time and Incubation Period for Coronavirus Disease 2019. The Journal Of Infectious Diseases 2021, 224: 1664-1671. PMID: 34423821, PMCID: PMC8499762, DOI: 10.1093/infdis/jiab424.Peer-Reviewed Original ResearchHow to detect and reduce potential sources of biases in studies of SARS-CoV-2 and COVID-19
Accorsi E, Qiu X, Rumpler E, Kennedy-Shaffer L, Kahn R, Joshi K, Goldstein E, Stensrud M, Niehus R, Cevik M, Lipsitch M. How to detect and reduce potential sources of biases in studies of SARS-CoV-2 and COVID-19. European Journal Of Epidemiology 2021, 36: 179-196. PMID: 33634345, PMCID: PMC7906244, DOI: 10.1007/s10654-021-00727-7.Peer-Reviewed Original ResearchConceptsRisk Factors StudyPublic health scientistsPotential sources of biasBody of literatureSources of biasStudy designFactor studiesHealth scientistsCategories of studiesObservational studyCOVID-19Selection biasPotential biasSecondary attack rateRisk of infectionGeographical areasAttack rateRiskSusceptibility to infectionStudy of COVID-19Cross-sectional seroprevalenceConfoundingCoronavirus diseaseIntervention
2020
Decreasing Trends in Heavy Sugar-Sweetened Beverage Consumption in the United States, 2003 to 2016
Vercammen K, Moran A, Soto M, Kennedy-Shaffer L, Bleich S. Decreasing Trends in Heavy Sugar-Sweetened Beverage Consumption in the United States, 2003 to 2016. Journal Of The Academy Of Nutrition And Dietetics 2020, 120: 1974-1985.e5. PMID: 32981886, DOI: 10.1016/j.jand.2020.07.012.Peer-Reviewed Original ResearchConceptsSugar-sweetened beveragesSSB intakeHispanic adultsSugar-sweetened beverage consumersNational Health and Nutrition Examination SurveyHealth and Nutrition Examination SurveyIncome statusSurvey-weighted logistic regressionNutrition Examination SurveyDietary recall dataAge groupsFamily income statusHigher-income adultsExamination SurveyUnited StatesSociodemographic characteristicsBeverage consumptionNational estimatesRecall dataIntake patternsProgrammatic effortsLogistic regressionEnergy intakeNo significant changesAdultsPotential Biases Arising From Epidemic Dynamics in Observational Seroprotection Studies
Kahn R, Kennedy-Shaffer L, Grad Y, Robins J, Lipsitch M. Potential Biases Arising From Epidemic Dynamics in Observational Seroprotection Studies. American Journal Of Epidemiology 2020, 190: 328-335. PMID: 32870977, PMCID: PMC7499481, DOI: 10.1093/aje/kwaa188.Peer-Reviewed Original Research