2019
Cost‐effectiveness of expanding the capacity of opioid agonist treatment in Ukraine: dynamic modeling analysis
Morozova O, Crawford FW, Cohen T, Paltiel AD, Altice FL. Cost‐effectiveness of expanding the capacity of opioid agonist treatment in Ukraine: dynamic modeling analysis. Addiction 2019, 115: 437-450. PMID: 31478285, PMCID: PMC7015766, DOI: 10.1111/add.14797.Peer-Reviewed Original ResearchMeSH KeywordsAnalgesics, OpioidCost-Benefit AnalysisForecastingHealth Services Needs and DemandHIV InfectionsHumansModels, TheoreticalOpiate Substitution TreatmentOpioid-Related DisordersUkraineConceptsOpioid agonist treatmentOpioid use disorderOAT coverageAgonist treatmentGross domestic productOpioid use initiationOpioid addiction epidemicOAT accessHIV epidemicUse disordersAddiction epidemicCapita gross domestic productPay thresholdsTreatment demandUse initiationAddiction treatmentIncremental costBaseline capacityTreatmentPotential peer effectsDomestic productTreatment spilloversEpidemicPeer effectsCoverage levels
2016
Cost-effectiveness and resource implications of aggressive action on tuberculosis in China, India, and South Africa: a combined analysis of nine models
Menzies NA, Gomez GB, Bozzani F, Chatterjee S, Foster N, Baena IG, Laurence YV, Qiang S, Siroka A, Sweeney S, Verguet S, Arinaminpathy N, Azman AS, Bendavid E, Chang ST, Cohen T, Denholm JT, Dowdy DW, Eckhoff PA, Goldhaber-Fiebert JD, Handel A, Huynh GH, Lalli M, Lin HH, Mandal S, McBryde ES, Pandey S, Salomon JA, Suen SC, Sumner T, Trauer JM, Wagner BG, Whalen CC, Wu CY, Boccia D, Chadha VK, Charalambous S, Chin DP, Churchyard G, Daniels C, Dewan P, Ditiu L, Eaton JW, Grant AD, Hippner P, Hosseini M, Mametja D, Pretorius C, Pillay Y, Rade K, Sahu S, Wang L, Houben RMGJ, Kimerling ME, White RG, Vassall A. Cost-effectiveness and resource implications of aggressive action on tuberculosis in China, India, and South Africa: a combined analysis of nine models. The Lancet Global Health 2016, 4: e816-e826. PMID: 27720689, PMCID: PMC5527122, DOI: 10.1016/s2214-109x(16)30265-0.Peer-Reviewed Original ResearchMeSH KeywordsChinaCost-Benefit AnalysisDelivery of Health CareForecastingGoalsHealth Care CostsHealth ExpendituresHealth PolicyHealth ResourcesHealth Services AccessibilityHealth Services Needs and DemandHumansIndiaModels, TheoreticalPatient Acceptance of Health CareQuality-Adjusted Life YearsSouth AfricaTuberculosisConceptsPatient-incurred costsTuberculosis servicesConventional cost-effectiveness thresholdsHigh-burden countriesEnd TB StrategySubstantial health gainsNet cost savingsResource implicationsCost-effectiveness thresholdMost intervention approachesTB StrategyTuberculosis incidenceMost interventionsSocietal perspectiveHealth gainsIntervention mixMelinda Gates FoundationSubstantial healthHealth effectsCurrent practiceExpansion of accessIntervention approachesEmpirical cost dataCost dataIntervention
2014
How can mathematical models advance tuberculosis control in high HIV prevalence settings?
Houben RM, Dowdy DW, Vassall A, Cohen T, Nicol MP, Granich RM, Shea JE, Eckhoff P, Dye C, Kimerling ME, White RG, . How can mathematical models advance tuberculosis control in high HIV prevalence settings? The International Journal Of Tuberculosis And Lung Disease 2014, 18: 509-514. PMID: 24903784, PMCID: PMC4436821, DOI: 10.5588/ijtld.13.0773.Peer-Reviewed Original ResearchConceptsHigh HIV prevalence settingsHIV prevalence settingsTB-HIVTuberculosis controlPrevalence settingsHigh human immunodeficiency virus (HIV) prevalenceHuman immunodeficiency virus (HIV) prevalenceTB ModellingHealth policy makersDifficult diagnosisDisease progressionHigh riskHigh mortalityHealth systemNatural progressionVirus prevalencePublic healthProgressionMortalityPrevalenceSettingAnalysis ConsortiumDiagnosisExpert discussion