Published in:
Open Access 01-12-2014 | Research
Correcting and estimating HIV mortality in Thailand based on 2005 verbal autopsy data focusing on demographic factors, 1996-2009
Published in: Population Health Metrics | Issue 1/2014
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Background
It is known that death registry (DR) underestimates HIV deaths. The objectives of this study were to examine under-reporting/misclassification and to estimate HIV mortality in Thailand during 1996-2009 from a model based on 2005 verbal autopsy (VA) data.
Methods
Logistic regression was used to predict HIV deaths from the VA dataset with and without demographic covariates. This full model was then used to predict individual HIV deaths from the DR dataset of provinces in which VA was conducted. The proportions in the remaining provinces were predicted from spatial interpolation based on coefficients of the VA provinces.
Results
Area under Receiver Operating Characteristic curve of the full model was 0.969 compared to 0.879 of the simple cross-referencing model when demographic covariates were not included. DR-reported HIV deaths accounted for only one-third of all VA-estimated HIV deaths. The most misclassified HIV deaths were those registered as tuberculosis and mental and nervous system. Under-reporting was most common among females and people aged 20-39 years, and effect of province was highest in the upper north and upper south regions.
Conclusions
For approximately two-thirds of all HIV deaths estimated by the full model, the causes were reported under other categories, not HIV. Demographic variables are essential for accurately correcting causes of death from death registries.