|Type||Journal Article - AIDS|
|Title||Empirical validation of the UNAIDS Spectrum model for subnational HIV estimates: case-study of children and adults in Manicaland, Zimbabwe|
Background: More cost-effective HIV control may be achieved by targeting geographical areas with high infection rates. The AIDS Impact model of Spectrum — used routinely to produce national HIV estimates — could provide the required subnational estimates but is rarely validated with empirical data, even at a national level.
Design: The validity of the Spectrum model estimates were compared with empirical estimates.
Methods: Antenatal surveillance and population survey data from a population HIV cohort study in Manicaland, East Zimbabwe, were input into Spectrum 5.441 to create a simulation representative of the cohort population. Model and empirical estimates were compared for key demographic and epidemiological outcomes. Alternative scenarios for data availability were examined and sensitivity analyses were conducted for model assumptions considered important for subnational estimates.
Results: Spectrum estimates generally agreed with observed data but HIV incidence estimates were higher than empirical estimates, whereas estimates of early age all-cause adult mortality were lower. Child HIV prevalence estimates matched well with the survey prevalence among children. Estimated paternal orphanhood was lower than empirical estimates. Including observations from earlier in the epidemic did not improve the HIV incidence model fit. Migration had little effect on observed discrepancies — possibly because the model ignores differences in HIV prevalence between migrants and residents.
Conclusion: The Spectrum model, using subnational surveillance and population data, provided reasonable subnational estimates although some discrepancies were noted. Differences in HIV prevalence between migrants and residents may need to be captured in the model if applied to subnational epidemics.
|»||Zimbabwe - Demographic and Health Survey 2005-2006|
|»||Zimbabwe - Demographic and Health Survey 2010-2011|