title: Probabilistic methods for verbal autopsy interpretation: InterVA robustness in relation to variations in a priori probabilities.
abstract: BACKGROUND
  InterVA is a probabilistic method for interpreting verbal autopsy (VA) data. It uses a priori approximations of probabilities relating to diseases and symptoms to calculate the probability of specific causes of death given reported symptoms recorded in a VA interview. The extent to which InterVA's ability to characterise a population's mortality composition might be sensitive to variations in these a priori probabilities was investigated.
  
  
  METHODS
  A priori InterVA probabilities were changed by 1, 2 or 3 steps on the logarithmic scale on which the original probabilities were based. These changes were made to a random selection of 25% and 50% of the original probabilities, giving six model variants. A random sample of 1,000 VAs from South Africa, were used as a basis for experimentation and were processed using the original InterVA model and 20 random instances of each of the six InterVA model variants. Rank order of cause of death and cause-specific mortality fractions (CSMFs) from the original InterVA model and the mean, maximum and minimum results from the 20 randomly modified InterVA models for each of the six variants were compared.
  
  
  RESULTS
  CSMFs were functionally similar between the original InterVA model and the models with modified a priori probabilities such that even the CSMFs based on the InterVA model with the greatest degree of variation in the a priori probabilities would not lead to substantially different public health conclusions. The rank order of causes were also similar between all versions of InterVA.
  
  
  CONCLUSIONS
  InterVA is a robust model for interpreting VA data and even relatively large variations in a priori probabilities do not affect InterVA-derived results to a great degree. The original physician-derived a priori probabilities are likely to be sufficient for the global application of InterVA in settings without routine death certification.
authors.affiliation: Department of Public Health and Clinical Medicine, Umeå Centre for Global Health Research, Umeå University, Umeå, Sweden. Edward.Fottrell@epiph.umu.se
authors.forename: Edward
authors.initials: E
authors.lastname: Fottrell
authors.forename: Kathleen
authors.initials: K
authors.lastname: Kahn
authors.forename: Stephen
authors.initials: S
authors.lastname: Tollman
authors.forename: Peter
authors.initials: P
authors.lastname: Byass
mesh_terms: D001344:Autopsy; D002423:Cause of Death; D006801:Humans; D011336:Probability; D013060:Speech
references.citation: Epidemiol Rev. 2010;32:38-55
references.pmid: 20203105
references.citation: PLoS Med. 2010 Aug 17;7(8):e1000325
references.pmid: 20808956
references.citation: Trop Med Int Health. 2008 Jul;13 Suppl 1:14-24
references.pmid: 18578808
references.citation: PLoS Med. 2007 Nov 20;4(11):e333
references.pmid: 18031198
references.citation: Bull World Health Organ. 2006 Mar;84(3):204-10
references.pmid: 16583079
references.citation: Trop Med Int Health. 2010 Oct;15(10):1256-65
references.pmid: 20701726
references.citation: Scand J Public Health Suppl. 2007 Aug;69:8-20
references.pmid: 17676498
references.citation: Trop Med Int Health. 2000 Nov;5(11):824-31
references.pmid: 11123832
references.citation: Popul Health Metr. 2007 Feb 08;5:1
references.pmid: 17288607
references.citation: Trop Med Int Health. 1999 Jun;4(6):433-41
references.pmid: 10444319
references.citation: Scand J Public Health. 2006;34(1):26-31
references.pmid: 16449041
references.citation: Trop Med Int Health. 2010 Feb;15(2):241-50
references.pmid: 19961564
references.citation: Scand J Public Health Suppl. 2003;62:32-7
references.pmid: 14649636
references.citation: PLoS Med. 2007 Nov 20;4(11):e327
references.pmid: 18031196