Table 1.
Study variables by survey and age band.
Fig 1.
Population size estimation process: AGYW who are HIV-negative and at risk for HIV infection.
Table 2.
Percentage of AGYW who are classified as at-risk of HIV infection, by estimation methodology.
Table 3.
Prevalent HIV infection by risk profile methodology.
Table 4.
Complimentary log-log regression results.
Table 5.
LCA conditional response probabilities and membership classification.
Table 6.
Percentage of AGYW who are classified as at risk and HIV-negative, by method.
Fig 2.
Subnational comparison of risk prevalence estimates, by method (mean with 95% CI).
Percentage of AGYW who are HIV-negative and classified as at-risk of HIV infection by country, age band, subnational unit, and model. (A) Haiti–Department level. (B) Mozambique–Provincial level. (C) Eswatini–Regional level.
Fig 3.
Hyperlocal heat maps of HIV risk prevalence (percentage at risk) and population density (number at risk), based on any-risk profile in Haiti, by age band.
The number-at-risk is calculated as those AGYW who are both classified as at-risk and HIV-negative for AGYW ages 15+ and the number-at-risk for AGYW 10–14 years is calculated as those AGYW classified as at-risk. Base map and data from the Spatial Data Repository, The Demographic and Health Surveys Program.
Fig 4.
Hyperlocal heat maps of HIV risk prevalence (percentage at risk) and population density (number at risk), based on any-risk profile in Mozambique, by age band.
The number-at-risk is calculated as those AGYW who are both classified as at-risk and HIV-negative for AGYW ages 15+, and the number-at-risk for AGYW 10–14 years is calculated as those AGYW classified as at-risk. Base map and data from the Spatial Data Repository, The Demographic and Health Surveys Program.