District-level HIV estimates using the spectrum model in five states of India, 2017

Abstract

Decentralized response has been the hallmark of the National AIDS Control Programme in India. District-level HIV burden estimates quantifying the distribution of the epidemics are needed to enhance this decentralized response further to monitor the progress on prevention, testing, and treatment interventions. In this paper, we describe the methodology and results of district-level estimates using the Spectrum model piloted in 5 states of India under National AIDS Control Programme.Using state spectrum model for HIV estimations 2017, we disaggregated state results by the district in pilot states. Each district was considered a subepidemic and HIV epidemic configuration was carried out in its general population as well as in key population. We used HIV surveillance data from antenatal clinics and routine pregnant women testing to model the general population's epidemic curve. We used HIV prevalence data available from HIV sentinel surveillance and integrated biological and behavioral surveys to inform the epidemic curve for key population. Estimation and projection packgage classic platform was used for the curve fitting. District-wide estimates extracted from subpopulation summary in Spectrum results section were used to calculate relative burden for each district and applied to approved State HIV Estimations 2017 estimates.No district in Tamil Nadu had an adult HIV prevalence of higher than 0.5% except for one, and the epidemic seems to be declining. In Maharashtra, the epidemic has shown a decline, with all except 5 districts showing an adult prevalence of less than 0.50%. In Gujarat and Uttar Pradesh, few districts showed rising HIV prevalence. However, none had an adult prevalence of higher than 0.50%. In Mizoram, 6 of 8 districts showed a rising HIV trend with an adult prevalence of 1% or more in 5 districts.Disaggregation of state-level estimates by districts provided insights on epidemic diversity within the analyzed states. It also provided baseline evidence to measure the progress toward the goal of end of AIDS by 2030.

Figure 1

Adult (15+ yr) HIV prevalence (%) in 2017. A, Adult HIV prevalence by districts in Gujarat. Color bins correspond to the 0.00 to 0.10, 0.10 to 0.20, 0.20 to 0.30, 0.30 to 0.40, and 0.40 to 0.50 to highlight variation within state of Gujarat. B, Adult HIV prevalence by districts in Maharashtra. Color bins correspond to the 0.10 to 0.20, 0.20 to 0.30, 0.30 to 0.40, 0.40 to 0.50, and >0.50 to highlight variation within state of Maharashtra. C, Adult HIV prevalence by districts in Mizoram. Color bins correspond to the 0.50 to 1.00, 1.00 to 1.50, 1.50 to 2.00, 2.00 to 2.50, and >2.50 to highlight variation within state of Mizoram. D, Adult HIV prevalence by districts in Tamil Nadu. Color bins correspond to the 0.10 to 0.20, 0.20 to 0.30, 0.30 to 0.40, 0.40 to 0.50, and >0.50 to highlight variation within state of Tamil Nadu. E, Adult HIV prevalence by districts in Uttar Pradesh. Color bins correspond to the 0.00 to 0.05, 0.05 to 0.10, 0.10 to 0.15, 0.15 to 0.20, and >0.20 to highlight variation within state of Uttar Pradesh.

Figure 2

PLHIV estimates in 2017. A, District-wide number of PLHIV in Gujarat. Color bins correspond to the <1000, 1000 to 2500, 2500 to 5000, 5000 to 7500, and >7500 to highlight variation within state of Gujarat. B, District-wide number of PLHIV in Maharashtra. Color bins correspond to the <5000, 5000 to 10,000, 10,000 to 15,000, 15,000 to 20,000, and > 20,000 to highlight variation within state of Maharashtra. C, District-wide number of PLHIV in Mizoram. Color bins correspond to the <500, 500 to 1000, 1000 to 2500, 2500 to 7500, and more than 7500 to highlight variation within state of Mizoram. D, District-wide number of PLHIV in Tamil Nadu. Color bins correspond to the <2500, 2500 to 5000, 5000 to 7500, 7500 to 10,000 and > 10,000 to highlight variation within state of Tamil Nadu. E, District-wide number of PLHIV in Uttar Pradesh. Color bins correspond to the <1000, 1000 to 2000, 2000 to 3000, 3000 to 4000, and >4000 to highlight variation within state of Uttar Pradesh.

Figure 3

Adult HIV prevalence (%) trend in 2017. This trend is from the EPP module of Spectrum. A, Adult HIV prevalence trend by districts in Gujarat. Districts in the state are grouped in 3 figures (i, ii, and iii) showing the trend. B, Adult HIV prevalence trend by districts in Maharashtra. Districts in the state are grouped into 3 figures (i, ii, and iii) showing the trend. C, Adult HIV prevalence trend by districts in Mizoram showing the adult prevalence trend. D, Adult HIV prevalence trend by districts in Tamil Nadu. Districts in the state are grouped in 3 figures (i, ii, and iii) showing the trend. E, Adult HIV prevalence trend by districts in Uttar Pradesh. Districts in the state are grouped into 3 figures (i, ii, and iii) showing the trend.