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Updates to the Spectrum/Estimations and Projections Package model for estimating trends and current values for key
John Stover1, Tim Brown, Robert Puckett
1aAvenir Health, Glastonbury, Connecticut bEast West Center, Honolulu, Hawaii, USA.
Background:
The Spectrum model is used by national programs and UNAIDS to prepare annual estimates of the status of the HIV epidemic in 160 countries. The model and assumptions are updated regularly under the guidance of the UNAIDS Reference Group on Estimates, Modelling and Projections in response to new data, studies, and program needs. This study describes the most recent updates for the 2016 round of estimates.
Methods:
Meetings of the UNAIDS Reference Group include individuals with extensive knowledge of HIV programs, research, statistics, and public policy. The Reference Group also collaborates with other institutions (such as the United Nations Population Division and the US Census Bureau) and projects (such as the ALPHA Network and IeDEA Consortium) to ensure that latest methods and data are used in the preparation of the annual estimates. In the past year new methods and data have been introduced for pediatric estimates, incidence fitting, and ART mortality (described elsewhere in this supplement).
Results:
The 2016 version of Spectrum includes a number of other enhancements, including updated demographic data from the United Nations Population Division, program options for treatment (treat all), and programs to prevent mother-to-child transmission (option B+), improved methods to aggregate uncertainty to regional and global levels, several options for generating incidence trends, adjustments to the Estimations and Projections Package model to better incorporate aging effects, adjustments to account for the changing bias in prevalence from antenatal clinic surveillance, and an option to fit incidence among all adults 15+ in addition to 15-49.
Conclusion:
The new methods and data implemented in the 2016 version of Spectrum allow national programs more flexibility in describing their programs and improve the estimates of key indicators and their uncertainty.
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