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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...

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Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2021
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.
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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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