title: The Impact and Cost-Effectiveness of a Four-Month Regimen for First-Line Treatment of Active Tuberculosis in South Africa.
abstract: BACKGROUND
  A 4-month first-line treatment regimen for tuberculosis disease (TB) is expected to have a direct impact on patient outcomes and societal costs, as well as an indirect impact on Mycobacterium tuberculosis transmission. We aimed to estimate this combined impact in a high TB-burden country: South Africa.
  
  
  METHODS
  An individual based M. tb transmission model was fitted to the TB burden of South Africa using a standard TB natural history framework. We measured the impact on TB burden from 2015-2035 of introduction of a non-inferior 4-month regimen replacing the standard 6-month regimen as first-line therapy. Impact was measured with respect to three separate baselines (Guidelines, Policy and Current), reflecting differences in adherence to TB and HIV treatment guidelines. Further scenario analyses considered the variation in treatment-related parameters and resistance levels. Impact was measured in terms of differences in TB burden and Disability Adjusted Life Years (DALYs) averted. We also examined the highest cost at which the new regimen would be cost-effective for several willingness-to-pay thresholds.
  
  
  RESULTS
  It was estimated that a 4-month regimen would avert less than 1% of the predicted 6 million person years with TB disease in South Africa between 2015 and 2035. A similarly small impact was seen on deaths and DALYs averted. Despite this small impact, with the health systems and patient cost savings from regimen shortening, the 4-month regimen could be cost-effective at $436 [NA, 5983] (mean [range]) per month at a willingness-to-pay threshold of one GDP per capita ($6,618).
  
  
  CONCLUSIONS
  The introduction of a non-inferior 4-month first-line TB regimen into South Africa would have little impact on the TB burden. However, under several scenarios, it is likely that the averted societal costs would make such a regimen cost-effective in South Africa.
authors.affiliation: Centre for Mathematical Modelling of Infectious Diseases, TB Centre, TB Modeling Group, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom.
authors.forename: Gwenan M
authors.initials: GM
authors.lastname: Knight
authors.affiliation: Amsterdam Institute for Global Health and Development and Department of Global Health, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands.|Department of Global Health and Development, London School of Hygiene and Tropical Medicine, London, United Kingdom.
authors.forename: Gabriela B
authors.initials: GB
authors.lastname: Gomez
authors.affiliation: School of Health and Related Research, University of Sheffield, Sheffield, United Kingdom.
authors.forename: Peter J
authors.initials: PJ
authors.lastname: Dodd
authors.affiliation: Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, United States of America.
authors.forename: David
authors.initials: D
authors.lastname: Dowdy
authors.affiliation: Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, United States of America.
authors.forename: Alice
authors.initials: A
authors.lastname: Zwerling
authors.affiliation: Global Alliance for TB Drug Development, New York, United States of America.
authors.forename: William A
authors.initials: WA
authors.lastname: Wells
authors.affiliation: Amsterdam Institute for Global Health and Development and Department of Global Health, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands.|KNCV Tuberculosis Foundation, The Hague, The Netherlands.
authors.forename: Frank
authors.initials: F
authors.lastname: Cobelens
authors.affiliation: Department of Global Health and Development, London School of Hygiene and Tropical Medicine, London, United Kingdom.
authors.forename: Anna
authors.initials: A
authors.lastname: Vassall
authors.affiliation: Centre for Mathematical Modelling of Infectious Diseases, TB Centre, TB Modeling Group, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom.
authors.forename: Richard G
authors.initials: RG
authors.lastname: White
mesh_terms: D000995:Antitubercular Agents / Q000191:economics* / Q000627:therapeutic use*; D003362:Cost-Benefit Analysis; D017048:Health Care Costs; D006801:Humans; D018803:Models, Economic; D009169:Mycobacterium tuberculosis / Q000187:drug effects; D019057:Quality-Adjusted Life Years; D011877:Radionuclide Imaging; D013019:South Africa; D014376:Tuberculosis / Q000000981:diagnostic imaging / Q000188:drug therapy* / Q000191:economics*
chemical_list: D000995:Antitubercular Agents