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A mathematical modeling study of the HIV epidemics at two rural townships in the Liangshan Prefecture of the Sichuan Province of China

BACKGROUND: As a response to a severe HIV epidemic in the Liangshan Prefecture, one of the worst in China, population based HIV interventions, including two population-wide HIV screening, have been carried out since 2005 at two townships in a remote mountainous region of Liangshan. The objective of...

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Autores principales: Su, Zhimin, Dong, Caiting, Li, Ping, Deng, Hongxia, Gong, Yuhan, Zhong, Shiyong, Wu, Min, Ruan, Yuhua, Qin, Guangming, Yang, Wen, Shao, Yiming, Li, Michael
Formato: Online Artículo Texto
Lenguaje:English
Publicado: KeAi Publishing 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5963326/
https://www.ncbi.nlm.nih.gov/pubmed/29928717
http://dx.doi.org/10.1016/j.idm.2016.05.001
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author Su, Zhimin
Dong, Caiting
Li, Ping
Deng, Hongxia
Gong, Yuhan
Zhong, Shiyong
Wu, Min
Ruan, Yuhua
Qin, Guangming
Yang, Wen
Shao, Yiming
Li, Michael
author_facet Su, Zhimin
Dong, Caiting
Li, Ping
Deng, Hongxia
Gong, Yuhan
Zhong, Shiyong
Wu, Min
Ruan, Yuhua
Qin, Guangming
Yang, Wen
Shao, Yiming
Li, Michael
author_sort Su, Zhimin
collection PubMed
description BACKGROUND: As a response to a severe HIV epidemic in the Liangshan Prefecture, one of the worst in China, population based HIV interventions, including two population-wide HIV screening, have been carried out since 2005 at two townships in a remote mountainous region of Liangshan. The objective of our mathematical modeling study is to assess the temporal dynamics of the HIV epidemic in the two townships based on the data collected in the study area during the period 2005–2010. METHODS: A mathematical model was set up to describe the population dynamics of HIV transmission in study area. The model was calibrated by fitting it to the HIV testing and treatment data from 2005 to 2008. Validation of the model was done by comparing its predicted value of HIV prevalence in 2010 to the prevalence data obtained in the 2010 population wide HIV testing. The validated model was used to produce estimation of HIV incidence, prevalence and death. RESULTS: Our model estimations show that population-based HIV interventions have significantly slowed down the rise of the HIV epidemic in the two townships. Over the five-year period from 2005 to 2010, the year-over-year rate of increase in HIV incidence, prevalence, and death has declined by 91.5%, 28.7%, and 52.3%, respectively. CONCLUSION: Mathematical models, when integrated with epidemiological and surveillance data, can be an effective tool for predicting the temporal dynamics of HIV and assessing the impacts of HIV interventions.
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spelling pubmed-59633262018-06-20 A mathematical modeling study of the HIV epidemics at two rural townships in the Liangshan Prefecture of the Sichuan Province of China Su, Zhimin Dong, Caiting Li, Ping Deng, Hongxia Gong, Yuhan Zhong, Shiyong Wu, Min Ruan, Yuhua Qin, Guangming Yang, Wen Shao, Yiming Li, Michael Infect Dis Model Article BACKGROUND: As a response to a severe HIV epidemic in the Liangshan Prefecture, one of the worst in China, population based HIV interventions, including two population-wide HIV screening, have been carried out since 2005 at two townships in a remote mountainous region of Liangshan. The objective of our mathematical modeling study is to assess the temporal dynamics of the HIV epidemic in the two townships based on the data collected in the study area during the period 2005–2010. METHODS: A mathematical model was set up to describe the population dynamics of HIV transmission in study area. The model was calibrated by fitting it to the HIV testing and treatment data from 2005 to 2008. Validation of the model was done by comparing its predicted value of HIV prevalence in 2010 to the prevalence data obtained in the 2010 population wide HIV testing. The validated model was used to produce estimation of HIV incidence, prevalence and death. RESULTS: Our model estimations show that population-based HIV interventions have significantly slowed down the rise of the HIV epidemic in the two townships. Over the five-year period from 2005 to 2010, the year-over-year rate of increase in HIV incidence, prevalence, and death has declined by 91.5%, 28.7%, and 52.3%, respectively. CONCLUSION: Mathematical models, when integrated with epidemiological and surveillance data, can be an effective tool for predicting the temporal dynamics of HIV and assessing the impacts of HIV interventions. KeAi Publishing 2016-05-16 /pmc/articles/PMC5963326/ /pubmed/29928717 http://dx.doi.org/10.1016/j.idm.2016.05.001 Text en © 2016 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Article
Su, Zhimin
Dong, Caiting
Li, Ping
Deng, Hongxia
Gong, Yuhan
Zhong, Shiyong
Wu, Min
Ruan, Yuhua
Qin, Guangming
Yang, Wen
Shao, Yiming
Li, Michael
A mathematical modeling study of the HIV epidemics at two rural townships in the Liangshan Prefecture of the Sichuan Province of China
title A mathematical modeling study of the HIV epidemics at two rural townships in the Liangshan Prefecture of the Sichuan Province of China
title_full A mathematical modeling study of the HIV epidemics at two rural townships in the Liangshan Prefecture of the Sichuan Province of China
title_fullStr A mathematical modeling study of the HIV epidemics at two rural townships in the Liangshan Prefecture of the Sichuan Province of China
title_full_unstemmed A mathematical modeling study of the HIV epidemics at two rural townships in the Liangshan Prefecture of the Sichuan Province of China
title_short A mathematical modeling study of the HIV epidemics at two rural townships in the Liangshan Prefecture of the Sichuan Province of China
title_sort mathematical modeling study of the hiv epidemics at two rural townships in the liangshan prefecture of the sichuan province of china
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5963326/
https://www.ncbi.nlm.nih.gov/pubmed/29928717
http://dx.doi.org/10.1016/j.idm.2016.05.001
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