Cargando…

Heterogeneity in geographical trends of HIV epidemics among key populations in Pakistan: a mathematical modeling study of survey data

BACKGROUND: Assessing patterns and trends in new infections is key to better understanding of HIV epidemics, and is best done through monitoring changes in incidence over time. In this study, we examined disparities in geographical trends of HIV epidemics among people who inject drugs (PWIDs), femal...

Descripción completa

Detalles Bibliográficos
Autores principales: Melesse, Dessalegn Y, Shafer, Leigh Anne, Emmanuel, Faran, Reza, Tahira, Achakzai, Baseer K, Furqan, Sofia, Blanchard, James F
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Edinburgh University Global Health Society 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5944903/
https://www.ncbi.nlm.nih.gov/pubmed/29770215
http://dx.doi.org/10.7189/jogh.08.010412
_version_ 1783321900550717440
author Melesse, Dessalegn Y
Shafer, Leigh Anne
Emmanuel, Faran
Reza, Tahira
Achakzai, Baseer K
Furqan, Sofia
Blanchard, James F
author_facet Melesse, Dessalegn Y
Shafer, Leigh Anne
Emmanuel, Faran
Reza, Tahira
Achakzai, Baseer K
Furqan, Sofia
Blanchard, James F
author_sort Melesse, Dessalegn Y
collection PubMed
description BACKGROUND: Assessing patterns and trends in new infections is key to better understanding of HIV epidemics, and is best done through monitoring changes in incidence over time. In this study, we examined disparities in geographical trends of HIV epidemics among people who inject drugs (PWIDs), female sex workers (FSWs) and hijra/transgender/male sex workers (H/MSWs), in Pakistan. METHODS: The UNAIDS Estimation and Projection Package (EPP) mathematical model was used to explore geographical trends in HIV epidemics. Four rounds of mapping and surveillance data collected among key populations (KPs) across 20 cities in Pakistan between 2005-2011 was used for modeling. Empirical estimates of HIV prevalence of each KP in each city were used to fit the model to estimate prevalence and incidence over time. RESULTS: HIV incidence among PWIDs in Pakistan reached its peak in 2011, estimated at 45.3 per 1000 person-years. Incidence was projected to continue to rise from 18.9 in 2015 to 24.3 in 2020 among H/MSWs and from 3.2 in 2015 to 6.3 in 2020 among FSWs. The number of people living with HIV in Pakistan was estimated to steadily increase through at least 2020. HIV incidence peak among PWIDs ranged from 16.2 in 1997 in Quetta to 71.0 in 2010 in Faisalabad (per 1000 person-years). Incidence among H/MSWs may continue to rise through 2020 in all the cities, except in Larkana where it peaked in the early 2000s. In 2015, model estimated incidence among FSWs was 8.1 in Karachi, 6.6 in Larkana, 2.0 in Sukkur and 1.2 in Lahore (per 1000 person-years). CONCLUSIONS: There exists significant geographical heterogeneity in patterns and trends of HIV sub-epidemics in Pakistan. Focused interventions and service delivery approaches, different by KP and city, are recommended.
format Online
Article
Text
id pubmed-5944903
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher Edinburgh University Global Health Society
record_format MEDLINE/PubMed
spelling pubmed-59449032018-05-16 Heterogeneity in geographical trends of HIV epidemics among key populations in Pakistan: a mathematical modeling study of survey data Melesse, Dessalegn Y Shafer, Leigh Anne Emmanuel, Faran Reza, Tahira Achakzai, Baseer K Furqan, Sofia Blanchard, James F J Glob Health Articles BACKGROUND: Assessing patterns and trends in new infections is key to better understanding of HIV epidemics, and is best done through monitoring changes in incidence over time. In this study, we examined disparities in geographical trends of HIV epidemics among people who inject drugs (PWIDs), female sex workers (FSWs) and hijra/transgender/male sex workers (H/MSWs), in Pakistan. METHODS: The UNAIDS Estimation and Projection Package (EPP) mathematical model was used to explore geographical trends in HIV epidemics. Four rounds of mapping and surveillance data collected among key populations (KPs) across 20 cities in Pakistan between 2005-2011 was used for modeling. Empirical estimates of HIV prevalence of each KP in each city were used to fit the model to estimate prevalence and incidence over time. RESULTS: HIV incidence among PWIDs in Pakistan reached its peak in 2011, estimated at 45.3 per 1000 person-years. Incidence was projected to continue to rise from 18.9 in 2015 to 24.3 in 2020 among H/MSWs and from 3.2 in 2015 to 6.3 in 2020 among FSWs. The number of people living with HIV in Pakistan was estimated to steadily increase through at least 2020. HIV incidence peak among PWIDs ranged from 16.2 in 1997 in Quetta to 71.0 in 2010 in Faisalabad (per 1000 person-years). Incidence among H/MSWs may continue to rise through 2020 in all the cities, except in Larkana where it peaked in the early 2000s. In 2015, model estimated incidence among FSWs was 8.1 in Karachi, 6.6 in Larkana, 2.0 in Sukkur and 1.2 in Lahore (per 1000 person-years). CONCLUSIONS: There exists significant geographical heterogeneity in patterns and trends of HIV sub-epidemics in Pakistan. Focused interventions and service delivery approaches, different by KP and city, are recommended. Edinburgh University Global Health Society 2018-06 2018-05-10 /pmc/articles/PMC5944903/ /pubmed/29770215 http://dx.doi.org/10.7189/jogh.08.010412 Text en Copyright © 2018 by the Journal of Global Health. All rights reserved. http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License.
spellingShingle Articles
Melesse, Dessalegn Y
Shafer, Leigh Anne
Emmanuel, Faran
Reza, Tahira
Achakzai, Baseer K
Furqan, Sofia
Blanchard, James F
Heterogeneity in geographical trends of HIV epidemics among key populations in Pakistan: a mathematical modeling study of survey data
title Heterogeneity in geographical trends of HIV epidemics among key populations in Pakistan: a mathematical modeling study of survey data
title_full Heterogeneity in geographical trends of HIV epidemics among key populations in Pakistan: a mathematical modeling study of survey data
title_fullStr Heterogeneity in geographical trends of HIV epidemics among key populations in Pakistan: a mathematical modeling study of survey data
title_full_unstemmed Heterogeneity in geographical trends of HIV epidemics among key populations in Pakistan: a mathematical modeling study of survey data
title_short Heterogeneity in geographical trends of HIV epidemics among key populations in Pakistan: a mathematical modeling study of survey data
title_sort heterogeneity in geographical trends of hiv epidemics among key populations in pakistan: a mathematical modeling study of survey data
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5944903/
https://www.ncbi.nlm.nih.gov/pubmed/29770215
http://dx.doi.org/10.7189/jogh.08.010412
work_keys_str_mv AT melessedessalegny heterogeneityingeographicaltrendsofhivepidemicsamongkeypopulationsinpakistanamathematicalmodelingstudyofsurveydata
AT shaferleighanne heterogeneityingeographicaltrendsofhivepidemicsamongkeypopulationsinpakistanamathematicalmodelingstudyofsurveydata
AT emmanuelfaran heterogeneityingeographicaltrendsofhivepidemicsamongkeypopulationsinpakistanamathematicalmodelingstudyofsurveydata
AT rezatahira heterogeneityingeographicaltrendsofhivepidemicsamongkeypopulationsinpakistanamathematicalmodelingstudyofsurveydata
AT achakzaibaseerk heterogeneityingeographicaltrendsofhivepidemicsamongkeypopulationsinpakistanamathematicalmodelingstudyofsurveydata
AT furqansofia heterogeneityingeographicaltrendsofhivepidemicsamongkeypopulationsinpakistanamathematicalmodelingstudyofsurveydata
AT blanchardjamesf heterogeneityingeographicaltrendsofhivepidemicsamongkeypopulationsinpakistanamathematicalmodelingstudyofsurveydata