Melanie H Chitwood, PhD
Postdoctoral AssociateDownloadHi-Res Photo
About
Titles
Postdoctoral Associate
Biography
Melanie H. Chitwood is a postdoctoral associate in the Ted Cohen Lab. She is interested in using mathematical models to understand the transmission and prevalence of tuberculosis in high burden settings. Melanie received her BA from Hampshire College, her MS in Global Health and Population from the Harvard T.H. Chan School of Public Health, and her PhD in Epidemiology (Microbial Diseases) from Yale School of Public Health.
Appointments
Epidemiology of Microbial Diseases
Postdoctoral AssociatePrimary
Other Departments & Organizations
Education & Training
- PhD
- Yale University , Epidemiology of Microbial Diseases
- MS
- Harvard T.H. Chan School of Publich Health, Global Health and Population
- BA
- Hamsphire College
Research
Research at a Glance
Yale Co-Authors
Frequent collaborators of Melanie H Chitwood's published research.
Publications Timeline
A big-picture view of Melanie H Chitwood's research output by year.
Ted Cohen, DPH, MD, MPH
Alexandra Savinkina, MSPH
Gregg Gonsalves, PhD
Jiye Kwon, MPH
Joshua Warren, PhD
Kenneth Gunasekera
7Publications
79Citations
Publications
2024
The recent rapid expansion of multidrug resistant Ural lineage Mycobacterium tuberculosis in Moldova
Chitwood M, Colijn C, Yang C, Crudu V, Ciobanu N, Codreanu A, Kim J, Rancu I, Rhee K, Cohen T, Sobkowiak B. The recent rapid expansion of multidrug resistant Ural lineage Mycobacterium tuberculosis in Moldova. Nature Communications 2024, 15: 2962. PMID: 38580642, PMCID: PMC10997638, DOI: 10.1038/s41467-024-47282-9.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsMDR M. tuberculosisGenome sequenceResistance-conferring mutationsBeijing sublineageMDR strainsReproductive fitnessBeijing strainsCulture-positive casesLineagesMtb strainsMultidrug-resistant tuberculosisMDRMtbStrainMDR-TBMutationsResistant tuberculosisMDR-MTBSubstantial riskSublineagesTuberculosisSequence
2023
Spatial Modeling of Mycobacterium Tuberculosis Transmission with Dyadic Genetic Relatedness Data
Warren J, Chitwood M, Sobkowiak B, Colijn C, Cohen T. Spatial Modeling of Mycobacterium Tuberculosis Transmission with Dyadic Genetic Relatedness Data. Biometrics 2023, 79: 3650-3663. PMID: 36745619, PMCID: PMC10404301, DOI: 10.1111/biom.13836.Peer-Reviewed Original ResearchCitationsMeSH Keywords and ConceptsEstimated Testing, Tracing, and Vaccination Targets for Containment of the US Mpox Outbreak
Chitwood M, Kwon J, Savinkina A, Walker J, Bilinski A, Gonsalves G. Estimated Testing, Tracing, and Vaccination Targets for Containment of the US Mpox Outbreak. JAMA Network Open 2023, 6: e2250984. PMID: 36637825, PMCID: PMC9857202, DOI: 10.1001/jamanetworkopen.2022.50984.Peer-Reviewed Original ResearchCitationsAltmetric
2022
A spatial-mechanistic model to estimate subnational tuberculosis burden with routinely collected data: An application in Brazilian municipalities
Chitwood M, Alves L, Bartholomay P, Couto R, Sanchez M, Castro M, Cohen T, Menzies N. A spatial-mechanistic model to estimate subnational tuberculosis burden with routinely collected data: An application in Brazilian municipalities. PLOS Global Public Health 2022, 2: e0000725. PMID: 36962578, PMCID: PMC10021638, DOI: 10.1371/journal.pgph.0000725.Peer-Reviewed Original ResearchCitationsAltmetricConceptsPerson/yearTB incidenceCase notificationBurden estimatesIncident TB casesTB case notificationTB control strategiesDisease burden estimatesIncident TBUntreated TBTB casesTuberculosis burdenDisease burdenIncidence rateCase detectionRoutine dataDeath recordsMortality dataIncidenceSubnational estimatesDisease control resourcesBurdenHigh needTBFraction of individualsReconstructing the course of the COVID-19 epidemic over 2020 for US states and counties: Results of a Bayesian evidence synthesis model
Chitwood MH, Russi M, Gunasekera K, Havumaki J, Klaassen F, Pitzer VE, Salomon JA, Swartwood NA, Warren JL, Weinberger DM, Cohen T, Menzies NA. Reconstructing the course of the COVID-19 epidemic over 2020 for US states and counties: Results of a Bayesian evidence synthesis model. PLOS Computational Biology 2022, 18: e1010465. PMID: 36040963, PMCID: PMC9467347, DOI: 10.1371/journal.pcbi.1010465.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsSARS-CoV-2 infectionCOVID-19 casesIncident SARS-CoV-2 infectionCOVID-19 disease burdenSymptomatic COVID-19 casesLocal epidemiological trendsSARS-CoV-2 transmissionBayesian evidence synthesis modelCOVID-19 outcomesEvidence synthesis modelMagnitude of infectionCOVID-19 deathsCumulative incidenceDisease burdenExcess mortalityCase ascertainmentEpidemiological trendsSeroprevalence estimatesUnderlying incidenceUS populationDisease trendsViral transmission dynamicsInfectionEpidemiological driversCOVID-19 epidemic
2021
Trends in Untreated Tuberculosis in Large Municipalities, Brazil, 2008–2017 - Volume 27, Number 3—March 2021 - Emerging Infectious Diseases journal - CDC
Chitwood MH, Pelissari DM, da Silva G, Bartholomay P, Rocha MS, Arakaki-Sanchez D, Sanchez M, Cohen T, Castro MC, Menzies NA. Trends in Untreated Tuberculosis in Large Municipalities, Brazil, 2008–2017 - Volume 27, Number 3—March 2021 - Emerging Infectious Diseases journal - CDC. Emerging Infectious Diseases 2021, 27: 957-960. PMID: 33622464, PMCID: PMC7920690, DOI: 10.3201/eid2703.204094.Peer-Reviewed Original ResearchCitationsAltmetricBayesian evidence synthesis to estimate subnational TB incidence: An application in Brazil
Chitwood MH, Pelissari DM, da Silva G, Bartholomay P, Rocha MS, Sanchez M, Arakaki-Sanchez D, Glaziou P, Cohen T, Castro MC, Menzies NA. Bayesian evidence synthesis to estimate subnational TB incidence: An application in Brazil. Epidemics 2021, 35: 100443. PMID: 33676092, PMCID: PMC8252152, DOI: 10.1016/j.epidem.2021.100443.Peer-Reviewed Original ResearchCitationsMeSH Keywords and ConceptsConceptsTB incidenceFraction of casesUntreated active diseaseIncident TB casesTB control programsLocal disease burdenIncident TBActive diseaseTB burdenTB casesTB outcomesTB notificationsDisease burdenBayesian evidence synthesisCase detectionIncidenceEvidence synthesisAverage annual increaseControl programsBurdenAnnual rateAnnual increaseFraction of individualsAverage annual rateSources of bias
Academic Achievements & Community Involvement
Honors
honor Inaugural Gerald Friedland Global Health Research Award
04/01/2022National AwardOffice of Global HealthDetailsUnited States