About: Declining trend in HIV new infections in Guangxi, China: insights from linking reported HIV/AIDS cases with CD4-at-diagnosis data

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About: Declining trend in HIV new infections in Guangxi, China: insights from linking reported HIV/AIDS cases with CD4-at-diagnosis data Goto Sponge NotDistinct Permalink

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Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Declining trend in HIV new infections in Guangxi, China: insights from linking reported HIV/AIDS cases with CD4-at-diagnosis data
Creator	Xiao, Yanni Tang, Sanyi Shen, Zhiyong Sun, Xiaodan Shen, Mingwang Chen, Huanhuan Ruan, Yuhua Tang, Shuai Wang, Tianyang Yang, Wenmin Zhu, Qiuying
Source	Medline; PMC
abstract	BACKGROUND: The Guangxi Zhuang Autonomous Region bears a relatively high burden of HIV/AIDS infection. The number of accumulatively reported HIV/AIDS cases in Guangxi is the third highest among 31 provinces or Autonomous Region from 2004 to 2007, changed to the second highest between 2011 and 2013, then returned to the third highest again after 2014. We aim to estimate the new infections and evaluate the real-time HIV epidemic in Guangxi, China, in order to reveal the rule of HIV transmission. METHODS: Firstly, the number of annually reported HIV and AIDS cases, as well as the number of cases linked with CD4 data are extracted from the HIV/AIDS information system in China. Secondly, two CD4-staged models are formulated by linking the with-host information on CD4 level to between-host transmission and surveillance data. Thirdly, new HIV infections, diagnosis rates and undiagnosed infections over time are estimated by using Bayesian method and Maximum Likelihood Estimation method. RESULTS: The data reveal that the newly reported cases have been decreasing since 2011, while lots of cases are identified at late CD4 stage. The data fitted results indicate that both models can describe the trend of the epidemic well. The estimation results show that the new and undiagnosed infections began to decrease from the period2006 - 2008. However, the diagnosis probabilities/rates keep at a very low level, and there are still a large number of infections undiagnosed, most of which have a large probability to be identified at late CD4 stage. CONCLUSIONS: Our findings suggest that HIV/AIDS epidemic in Guangxi has been controlled to a certain extent, while the diagnosis rate still needs to be improved. More attentions should be paid to identify infections at their early CD4 stages. Meanwhile, comprehensive intervention measures should be continually strengthened in avoid of the rebound of new infections.
has issue date	2020-06-12(xsd:dateTime)
bibo:doi	10.1186/s12889-020-09021-9
bibo:pmid	32532238
has license	cc-by
sha1sum (hex)	b4d19ef66abd807a9a05a9ef88a1f3ef1770922c
schema:url	https://doi.org/10.1186/s12889-020-09021-9
resource representing a document's title	Declining trend in HIV new infections in Guangxi, China: insights from linking reported HIV/AIDS cases with CD4-at-diagnosis data
has PubMed Central identifier	PMC7290136
has PubMed identifier	32532238
schema:publication	BMC Public Health
resource representing a document's body	covid:b4d19ef66abd807a9a05a9ef88a1f3ef1770922c#body_text
is schema:about of	named entity 'evaluate' named entity 'reveal' named entity 'REGION' named entity 'epidemic' named entity 'changed' named entity 'bears' named entity 'insights' named entity 'HIV/AIDS' named entity 'linking' named entity 'Guangxi' named entity 'Guangxi' named entity 'HIV transmission' named entity 'infection' named entity 'CD4' named entity 'HIV/AIDS cases' named entity 'CD4' named entity 'CD4' named entity 'AIDS' named entity '85%' named entity 'CD4' named entity 'HIV infection' named entity 'HIV' named entity 'follow-up' named entity 'HIV/AIDS epidemic' named entity '1, 2' named entity 'China' named entity '1, 2' named entity '95% CI' named entity 'SARS' named entity 'CD4' named entity 'HIV' named entity 'likelihood function' named entity 'Guangxi' named entity 'follow-up' named entity 'probability' named entity 'CD4' named entity 'HIV' named entity 'AIDS' named entity 'follow-up' named entity 'MCMC' named entity 'deterministic' named entity 'Guangxi' named entity 'CD4' named entity 'CD4' named entity 'HIV' named entity 'Guangxi' named entity 'HIV' named entity 'HIV/AIDS epidemic' named entity 'HIV infections' named entity 'reported cases' named entity 'HIV' named entity 'prior distribution' named entity 'Markov model' named entity 'HIV' named entity 'CD4' named entity 'reported cases' named entity 'Maximum Likelihood Estimation' named entity 'HIV infection' named entity 'Guangxi' named entity 'China' named entity 'epidemic' named entity 'reported cases' named entity 'stochastic' named entity 'AIDS' named entity 'HIV/AIDS' named entity 'HIV' named entity 'AIDS' named entity 'infection' named entity 'HIV' named entity 'Guangxi' named entity 'CD4'

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