Monitoring progress towards the first UNAIDS 90-90-90 target in key populations living with HIV in Norway

BMC Infectious Diseases

Table 1 Input data used for running the ECDC HIV modelling tool and CSAVR tool in Norway

Model	Input data item	Data source
ECDC HIV modelling tool	New HIV diagnoses^a	National surveillance data from 1987 to 2018 (n = 5318)
	New AIDS diagnoses	National surveillance data from 1983 to 1995^b (n = 481)
	New HIV/AIDS^c diagnoses	National surveillance data from 1987 to 2018 (n = 1140)
	CD4 count at diagnosis among non-HIV/AIDS diagnoses categorised into four strata (≥500, 350–499, 200–349, < 200)	Default model assumptions on CD4 distribution for whole study period OR Default model assumptions until 2003 and Danish national CD4 count data from 2004 to 2018, adjusted for route of transmission and region of birth^d.
	All-cause mortality and outmigration	National surveillance data from 1987 to 2018 (n = 759)^e
CSAVR tool	New HIV diagnoses^a	National surveillance data from 1987 to 2018 (n = 5318)
CSAVR tool	AIDS deaths	Adjusted estimates of AIDS-related deaths from 1990 to 2017 (n = 703)^f

^a All new HIV diagnoses, including those with AIDS at first diagnosis ^b AIDS diagnoses after 1995 were not used because the probability of progressing to AIDS would be affected by the use of combination ART, the effect of which is not incorporated into the model. ^c HIV diagnosis for which the reported clinical picture was AIDS. ^d Before 2004, the data completeness for CD4 count in Denmark was < 10%. In 2004 it was 48%, and over 80% from 2009 onwards (88% in 2018). ^e Data on outcome was known for 14% of HIV diagnoses (n = 759), all of which were reported as dead or out-migrated. ^f Estimates produced by the Institute of Health Metrics and Evaluation for the Global Burden of Disease Study [26]

ISSN: 1471-2334