title: Using the TIME model in Spectrum to estimate tuberculosis-HIV incidence and mortality.
abstract: OBJECTIVE
  Reliable estimates of the joint burden of HIV and tuberculosis epidemics are crucial to planning strategic global and national tuberculosis responses. Prior to the Global Tuberculosis Report 2013, the Global Tuberculosis Programme (GTB) released estimates for tuberculosis-HIV incidence at the global level only. Neither GTB nor United Nations Programme on HIV/AIDS (UNAIDS) published country specific estimates for tuberculosis-HIV mortality. We used a regression approach that combined all available data from GTB and UNAIDS in order to estimate tuberculosis-HIV incidence and mortality at country level.
  
  
  METHODS
  A regression method was devised to relate CD4 dynamics (based on national Spectrum files) to an increased relative risk (RR) of tuberculosis disease. The objective function is based on least squares and incorporates all available country-level estimates of tuberculosis-HIV incidence. Global regression parameters, obtained from averaging results over countries with population survey estimates for tuberculosis-HIV burden, were applied to countries with no survey tuberculosis-HIV incidence estimates.
  
  
  RESULTS
  The method produced results that are in reasonably close agreement with existing GTB estimates for global tuberculosis-HIV burden. It estimated that tuberculosis-HIV accounts for 12.6% of global tuberculosis incidence, 21.3% of all tuberculosis deaths, and 20% of all HIV deaths as estimated by the Spectrum AIDS Impact Module (AIM). Regional estimates show the highest absolute incidence burden in East and Southeast Asia, and the highest per capita burden in sub-Saharan Africa, where between 12.5% (Central sub-Saharan Africa) and 60.6% (Southern sub-Saharan Africa) of all tuberculosis disease occurs in people living with HIV (PLWH). Tuberculosis mortality follows a similar pattern, except that a disproportionate percentage of global tuberculosis deaths (12.1%) relative to global incidence (8.7%) occurred in Southern sub-Saharan Africa.
  
  
  CONCLUSIONS
  The disaggregation of tuberculosis incidence using a regression method on RR of tuberculosis disease and all available data on HIV burden (from UNAIDS) and tuberculosis-HIV testing (survey, sentinel and routine surveillance data) produces results that closely match GTB estimates for 2011. The tuberculosis-HIV incidence and mortality results were published in the Global Tuberculosis Report 2013. Several limitations of and potential improvements to the process are suggested.
authors.affiliation: aFutures Institute, Glastonbury, Connecticut, 06033, USA bGlobal TB Programme, World Health Organization, 20 avenue Appia, 1211 Geneva 27, Switzerland cHealth Economics and Decision Science, School of Health and Related Research, University of Sheffield, Sheffield, S1 4DA, UK dTB Modelling Group, TB Centre, London School of Hygiene and Tropical Medicine, UK. *Philippe Glaziou, Peter J. Dodd and Richard White contributed equally to the writing of this article.
authors.forename: Carel
authors.initials: C
authors.lastname: Pretorius
authors.forename: Philippe
authors.initials: P
authors.lastname: Glaziou
authors.forename: Peter J
authors.initials: PJ
authors.lastname: Dodd
authors.forename: Richard
authors.initials: R
authors.lastname: White
authors.forename: Rein
authors.initials: R
authors.lastname: Houben
mesh_terms: D004812:Epidemiologic Methods; D014943:Global Health; D015658:HIV Infections / Q000150:complications* / Q000453:epidemiology*; D006801:Humans; D015994:Incidence; D012044:Regression Analysis; D016019:Survival Analysis; D013997:Time Factors; D014376:Tuberculosis / Q000453:epidemiology* / Q000401:mortality*