2022
Global Prevalence of Post-Coronavirus Disease 2019 (COVID-19) Condition or Long COVID: A Meta-Analysis and Systematic Review
Chen C, Haupert S, Zimmermann L, Shi X, Fritsche L, Mukherjee B. Global Prevalence of Post-Coronavirus Disease 2019 (COVID-19) Condition or Long COVID: A Meta-Analysis and Systematic Review. The Journal Of Infectious Diseases 2022, 226: 1593-1607. PMID: 35429399, PMCID: PMC9047189, DOI: 10.1093/infdis/jiac136.Peer-Reviewed Original ResearchConceptsPost-COVID-19 conditionCondition prevalenceMeta-analysisGlobal prevalenceHealth effects of COVID-19Prevalence of post-COVID-19 conditionRegional prevalence estimationHealthcare systemPrevalence estimatesPooled prevalencePost-COVID-19Systematic reviewDerSimonian-Laird estimatorMeta-analyzedMemory problemsHealth effectsPrevalenceEffects of COVID-19Post-coronavirus disease 2019Long COVIDCOVID-19COVID-19 conditionsNonhospitalized patientsUnited States
2014
The impact of exposure-biased sampling designs on detection of gene–environment interactions in case–control studies with potential exposure misclassification
Stenzel S, Ahn J, Boonstra P, Gruber S, Mukherjee B. The impact of exposure-biased sampling designs on detection of gene–environment interactions in case–control studies with potential exposure misclassification. European Journal Of Epidemiology 2014, 30: 413-423. PMID: 24894824, PMCID: PMC4256150, DOI: 10.1007/s10654-014-9908-1.Peer-Reviewed Original ResearchConceptsG-E interactionsExposure informationDetection of gene-environment interactionsPrevalence of exposureGene-environment interactionsSampling designCase-control studyRandom selection of subjectsPerformance of sampling designsCase-onlyExposure prevalenceJoint testExposure misclassificationCase-controlRare exposuresMarginal associationSelection of subjectsType I errorEmpirical simulation studyIdeal sampling schemesJoint effectsPrevalenceRandom selectionG-EMisclassification