Yu Lan
Postdoctoral AssociateDownloadHi-Res Photo
About
Copy Link
Titles
Postdoctoral Associate
Biography
Dr. Lan is a spatial epidemiologist and health geographer who works on understanding and visualizing space-time transmission patterns in infectious diseases such as COVID-19 and tuberculosis. She is particularly interested on combining genomic (i.e., WGS) and spatial methods to further recognize strains associated transmission patterns.
Last Updated on March 28, 2024.
Departments & Organizations
Education & Training
- PhD
- University of North Carolina at Charlotte, Geography
- MA
- University of North Carolina at Charlotte, Geography
Research
Copy Link
Overview
Public Health Interests
Disease Transmission; GIS/Disease Mapping; COVID-19
ORCID
0000-0003-0373-1944- View Lab Website
Ted Cohen Lab
Research at a Glance
Yale Co-Authors
Frequent collaborators of Yu Lan's published research.
Publications Timeline
A big-picture view of Yu Lan's research output by year.
Joshua Warren, PhD
Daniel Weinberger, PhD
Elizabeth Corbett
Kate Nyhan, MLS
Patrick Cudahy, MD, MSc
Ted Cohen, DPH, MD, MPH
11Publications
8Citations
Publications
Featured Publications
Integrating genomic and spatial analyses to describe tuberculosis transmission: a scoping review
Lan Y, Rancu I, Chitwood M, Sobkowiak B, Nyhan K, Lin H, Wu C, Mathema B, Brown T, Colijn C, Warren J, Cohen T. Integrating genomic and spatial analyses to describe tuberculosis transmission: a scoping review. The Lancet Microbe 2025, 6: 101094. PMID: 40228509, PMCID: PMC12371702, DOI: 10.1016/j.lanmic.2025.101094.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsCitationsAltmetricConceptsGenome sequencing approachGenetic similarityGenomic dataSequencing approachGenotyping methodsPathogen geneticsGenetic methodsPathogen sequencesSampling completenessTuberculosis isolatesTransmission patternsTuberculosis casesPathogensTuberculosis transmissionM tuberculosis isolatesInfection-related mortalityEnvironmental factorsTuberculosis transmission dynamicsSpatial proximityTransmission clustersGenomeSpatial patternsTuberculosisTransmission dynamicsGeneticsIdentifying local foci of tuberculosis transmission in Moldova using a spatial multinomial logistic regression model
Lan Y, Crudu V, Ciobanu N, Codreanu A, Chitwood M, Sobkowiak B, Warren J, Cohen T. Identifying local foci of tuberculosis transmission in Moldova using a spatial multinomial logistic regression model. EBioMedicine 2024, 102: 105085. PMID: 38531172, PMCID: PMC10987885, DOI: 10.1016/j.ebiom.2024.105085.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsPatterns of spatial aggregationMTB strainsMDR-TBLogistic regression modelsGenome Epidemiology StudySpecific strainsMultidrug-resistant tuberculosisTreated TB casesNational Institute of AllergyMDR phenotypeRegression modelsM. tuberculosisInstitute of AllergyMultinomial logistic regression modelUS National Institutes of HealthNational Institutes of HealthMDR diseasePublic health concernAssociated with local transmissionIncident TBInstitutes of HealthMtbResistant tuberculosisStrainDiagnosing TBA web-based analytical framework for the detection and visualization space-time clusters of COVID-19
Lan, Y. and Delmelle, E., 2024. A web-based analytical framework for the detection and visualization space-time clusters of COVID-19. Cartography and Geographic Information Science, 51(2), pp.311-329.Peer-Reviewed Original ResearchSpace-time cluster detection techniques for infectious diseases: A systematic review.
Lan Y, Delmelle E. Space-time cluster detection techniques for infectious diseases: A systematic review. Spat Spatiotemporal Epidemiol 2023, 44: 100563. PMID: 36707196, DOI: 10.1016/j.sste.2022.100563.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsDistribution and transmission of M. tuberculosis in a high-HIV prevalence city in Malawi: A genomic and spatial analysis
Chitwood M, Corbett E, Ndhlovu V, Sobkowiak B, Colijn C, Andrews J, Burke R, Cudahy P, Dodd P, Imai-Eaton J, Engelthaler D, Folkerts M, Feasey H, Lan Y, Lewis J, McNichol J, Menzies N, Chipungu G, Nliwasa M, Weinberger D, Warren J, Salomon J, MacPherson P, Cohen T. Distribution and transmission of M. tuberculosis in a high-HIV prevalence city in Malawi: A genomic and spatial analysis. PLOS Global Public Health 2025, 5: e0004040. PMID: 40173177, PMCID: PMC11964229, DOI: 10.1371/journal.pgph.0004040.Peer-Reviewed Original ResearchCitationsAltmetricConceptsHigh HIV prevalence citiesTime of tuberculosisPoor health outcomesCity-wide interventionsTransmission of M. tuberculosisHealth outcomesTargeted interventionsHighest tuberculosis burdenTargeted screeningGeneral populationGeographic concentrationSurveillance dataCommunity characteristicsTuberculosis burdenLocal tacticsBlantyreWhole-genome sequencingInfectious tuberculosisCulture-positive tuberculosis casesInterventionMalawiSustained impactTreated individualsCityEvidence of local transmission
2022
Uncertainty in geospatial health: challenges and opportunities ahead
Delmelle, E.M., Desjardins, M.R., Jung, P., Owusu, C., Lan, Y., Hohl, A. and Dony, C., 2022. Uncertainty in geospatial health: challenges and opportunities ahead. Annals of epidemiology, 65, pp.15-30.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus Statements
2021
Geovisualization of COVID-19: State of the Art and Opportunities
Lan, Y., Desjardins, M. R., Hohl, A., & Delmelle, E. (2021). Geovisualization of COVID-19: State of the Art and Opportunities. Cartographica: The International Journal for Geographic Information and Geovisualization, 56(1), 2-13.Peer-Reviewed Original ResearchNDS: an interactive, web-based system to visualize urban neighborhood dynamics in United States
Lan, Y., Delmelle, E. and Delmelle, E., 2021. NDS: an interactive, web-based system to visualize urban neighborhood dynamics in United States. Journal of Maps, 17(1), pp.62-70.Peer-Reviewed Original Research
2020
Daily surveillance of COVID-19 using the prospective space-time scan statistic in the United States
Hohl, A., Delmelle, E. M., Desjardins, M. R., & Lan, Y. (2020). Daily surveillance of COVID-19 using the prospective space-time scan statistic in the United States. Spatial and spatio-temporal epidemiology, 34, 100354.Peer-Reviewed Original ResearchA web-based spatial decision support system for monitoring the risk of water contamination in private wells
Lan, Y., Tang, W., Dye, S., & Delmelle, E. (2020). A web-based spatial decision support system for monitoring the risk of water contamination in private wells. Annals of GIS, 26(3), 293-309.Peer-Reviewed Original Research
Academic Achievements & Community Involvement
Copy Link
Honors
honor SISMID Scholarship
04/24/2024Other AwardSummer Institute in Statistics and Modeling in Infectious Diseaseshonor Student Honors Paper Competition Finalist
03/24/2023Other AwardGeographic Information Science and Systems Specialty Group, American Association of Geographershonor Dissertation Summer Fellowship
05/01/2022Other AwardGraduate School, UNC CharlotteDetailsUnited Stateshonor Robert Raskin Student Competition Finalist
03/01/2022Other AwardCyberinfrastructure Specialty Group, American Association of Geographershonor David Woodward Digital Map Award
04/10/2021Other AwardThe Cartography and Geographic Information SocietyDetailsUnited States
Links
Copy Link
Related Links
Get In Touch
Copy Link
Contacts
Email
Locations
Public Health Modeling Unit
Academic Office
350 George Street
New Haven, CT 06511