title: InterVA versus Spectrum: how comparable are they in estimating AIDS mortality patterns in Nairobi's informal settlements?
abstract: BACKGROUND
  The Spectrum computer package is used to generate national AIDS mortality estimates in settings where vital registration systems are lacking. Similarly, InterVA-4 (the latest version of the InterVA programme) is used to estimate cause-of-mortality data in countries where cause-specific mortality data are not available.
  
  
  OBJECTIVE
  This study aims to compare trends in adult AIDS-related mortality estimated by Spectrum with trends from the InterVA-4 programme applied to data from a Health and Demographic Surveillance System (HDSS) in Nairobi, Kenya.
  
  
  METHODS
  A Spectrum model was generated for the city of Nairobi based on HIV prevalence data for Nairobi and national antiretroviral therapy coverage, underlying mortality, and migration assumptions. We then used data, generated through verbal autopsies, on 1,799 deaths that occurred in the HDSS area from 2003 to 2010 among adults aged 15-59. These data were then entered into InterVA-4 to estimate causes of death using probabilistic modelling. Estimates of AIDS-related mortality rates and all-cause mortality rates from Spectrum and InterVA-4 were compared and presented as annualised trends.
  
  
  RESULTS
  Spectrum estimated that HIV prevalence in Nairobi was 7%, while the HDSS site measured 12% in 2010. Despite this difference, Spectrum estimated higher levels of AIDS-related mortality. Between 2003 and 2010, the proportion of AIDS-related mortality in Nairobi decreased from 63 to 40% according to Spectrum and from 25 to 16% according to InterVA. The net AIDS-related mortality in Spectrum was closer to the combined mortality rates when AIDS and tuberculosis (TB) deaths were included for InterVA-4.
  
  
  CONCLUSIONS
  Overall trends in AIDS-related deaths from both methods were similar, although the values were closer when TB deaths were included in InterVA. InterVA-4 might not accurately differentiate between TB and AIDS deaths.
authors.affiliation: African Population and Health Research Center, Nairobi, Kenya; Department of Global Health, Amsterdam Institute for Global Health and Development, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands; soti@aphrc.org.
authors.forename: Samuel Oji
authors.initials: SO
authors.lastname: Oti
authors.forename: Marilyn
authors.initials: M
authors.lastname: Wamukoya
authors.forename: Mary
authors.initials: M
authors.lastname: Mahy
authors.forename: Catherine
authors.initials: C
authors.lastname: Kyobutungi
mesh_terms: D000163:Acquired Immunodeficiency Syndrome / Q000401:mortality*; D000293:Adolescent; D000328:Adult; D000367:Age Factors; D001344:Autopsy / Q000379:methods; D002423:Cause of Death / Q000639:trends; D005260:Female; D015658:HIV Infections / Q000453:epidemiology; D006801:Humans; D007630:Kenya / Q000453:epidemiology; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D011159:Population Surveillance / Q000379:methods*; D015995:Prevalence; D012737:Sex Factors; D014505:Urban Population / Q000706:statistics & numerical data; D055815:Young Adult
keywords: AIDS; InterVA; Nairobi; Spectrum; mortality