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District-level HIV estimates using the spectrum model in five states of India, 2017
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 inte...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Lippincott Williams & Wilkins
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8284765/ https://www.ncbi.nlm.nih.gov/pubmed/34260537 http://dx.doi.org/10.1097/MD.0000000000026578 |
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author | Kumar, Pradeep Sahu, Damodar Rajan, Shobini Mendu, Vishnu Vardhana Rao Das, Chinmoyee Kumar, Arvind Chandra, Nalini Camara, Bilali Rai, Sanjay Arumugam, Elangovan Godbole, Sheela Virendra Singh, Shri Kant Kant, Shashi Pandey, Arvind Reddy, Dandu Chandra Sekhar Mehendale, Sanjay |
author_facet | Kumar, Pradeep Sahu, Damodar Rajan, Shobini Mendu, Vishnu Vardhana Rao Das, Chinmoyee Kumar, Arvind Chandra, Nalini Camara, Bilali Rai, Sanjay Arumugam, Elangovan Godbole, Sheela Virendra Singh, Shri Kant Kant, Shashi Pandey, Arvind Reddy, Dandu Chandra Sekhar Mehendale, Sanjay |
author_sort | Kumar, Pradeep |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8284765 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Lippincott Williams & Wilkins |
record_format | MEDLINE/PubMed |
spelling | pubmed-82847652021-07-19 District-level HIV estimates using the spectrum model in five states of India, 2017 Kumar, Pradeep Sahu, Damodar Rajan, Shobini Mendu, Vishnu Vardhana Rao Das, Chinmoyee Kumar, Arvind Chandra, Nalini Camara, Bilali Rai, Sanjay Arumugam, Elangovan Godbole, Sheela Virendra Singh, Shri Kant Kant, Shashi Pandey, Arvind Reddy, Dandu Chandra Sekhar Mehendale, Sanjay Medicine (Baltimore) 4850 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. Lippincott Williams & Wilkins 2021-07-16 /pmc/articles/PMC8284765/ /pubmed/34260537 http://dx.doi.org/10.1097/MD.0000000000026578 Text en Copyright © 2021 the Author(s). Published by Wolters Kluwer Health, Inc. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial License 4.0 (CCBY-NC), where it is permissible to download, share, remix, transform, and buildup the work provided it is properly cited. The work cannot be used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc/4.0 (https://creativecommons.org/licenses/by-nc/4.0/) |
spellingShingle | 4850 Kumar, Pradeep Sahu, Damodar Rajan, Shobini Mendu, Vishnu Vardhana Rao Das, Chinmoyee Kumar, Arvind Chandra, Nalini Camara, Bilali Rai, Sanjay Arumugam, Elangovan Godbole, Sheela Virendra Singh, Shri Kant Kant, Shashi Pandey, Arvind Reddy, Dandu Chandra Sekhar Mehendale, Sanjay District-level HIV estimates using the spectrum model in five states of India, 2017 |
title | District-level HIV estimates using the spectrum model in five states of India, 2017 |
title_full | District-level HIV estimates using the spectrum model in five states of India, 2017 |
title_fullStr | District-level HIV estimates using the spectrum model in five states of India, 2017 |
title_full_unstemmed | District-level HIV estimates using the spectrum model in five states of India, 2017 |
title_short | District-level HIV estimates using the spectrum model in five states of India, 2017 |
title_sort | district-level hiv estimates using the spectrum model in five states of india, 2017 |
topic | 4850 |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8284765/ https://www.ncbi.nlm.nih.gov/pubmed/34260537 http://dx.doi.org/10.1097/MD.0000000000026578 |
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