Literature DB >> 33503938

Spatiotemporal Analysis of AIDS Incidence and Its Influencing Factors on the Chinese Mainland, 2005-2017.

Yige Wang1, Chunhong Zhao1, Ziping Liu1, Decai Gao1.   

Abstract

Acquired Immune Deficiency Syndrome (AIDS) has become one of the most severe public health issues and nowadays around 38 million people are living with the human immunodeficiency virus (HIV). Ensuring healthy lives and promoting well-being is one of 17 United Nations Sustainable Development Goals. Here, we used the Markov chain matrix and geospatial clustering to comprehensively quantify the trends of the AIDS epidemic at the provincial administrate level in the mainland of China from 2005 to 2017. The Geographically Weighted Regression (GWR) model was further adopted to explore four groups of potential influencing factors (i.e., economy, traffic and transportation, medical care, and education) of the AIDS incidence rate in 2017 and their spatially distributed patterns. Results showed that the AIDS prevalence in southeastern China had been dominant and become prevalent in the past decade. The AIDS intensity level had been increasing between 2008 and 2011 but been gradually decreasing afterward. The analysis of the Markov chain matrix indicated that the AIDS epidemic has been generally in control on the Chinese mainland. The economic development was closely related to the rate of AIDS incidence on the Chinese mainland. The GWR result further suggested that medical care and the education effects on AIDS incidence rate can vary with different regions, but significant conclusions cannot be directly demonstrated. Our findings contribute an analytical framework of understanding AIDS epidemic trends and spatial variability of potential underlying factors throughout a complex extent to customize scientific prevention.

Entities:  

Keywords:  AIDS; Geographically Weighted Regression; Markov chain; Moran’s I index; spatial analysis; spatial epidemiology

Mesh:

Year:  2021        PMID: 33503938      PMCID: PMC7908178          DOI: 10.3390/ijerph18031043

Source DB:  PubMed          Journal:  Int J Environ Res Public Health        ISSN: 1660-4601            Impact factor:   3.390


  23 in total

1.  Notes on continuous stochastic phenomena.

Authors:  P A P MORAN
Journal:  Biometrika       Date:  1950-06       Impact factor: 2.445

2.  Education attainment as a predictor of HIV risk in rural Uganda: results from a population-based study.

Authors:  J Smith; F Nalagoda; M J Wawer; D Serwadda; N Sewankambo; J Konde-Lule; T Lutalo; C Li; R H Gray
Journal:  Int J STD AIDS       Date:  1999-07       Impact factor: 1.359

3.  Detection of spatial disease clusters with LISA functions.

Authors:  Paula Moraga; Francisco Montes
Journal:  Stat Med       Date:  2011-01-12       Impact factor: 2.373

4.  Analysis of critical land degradation and development processes and their driving mechanism in the Heihe River Basin.

Authors:  Yaqi Shao; Qun'ou Jiang; Chunli Wang; Meilin Wang; Ling Xiao; Yuanjing Qi
Journal:  Sci Total Environ       Date:  2020-02-03       Impact factor: 7.963

5.  A comparative study of the spatial distribution of HIV prevalence in the metropolis of Kermanshah, Iran, in 1996-2014 using geographical information systems.

Authors:  N Khademi; S Reshadat; A Zangeneh; S Saeidi; S R Ghasemi; N Rajabi-Gilan; A Zakiei
Journal:  HIV Med       Date:  2016-08-18       Impact factor: 3.180

6.  Localized spatial clustering of HIV infections in a widely disseminated rural South African epidemic.

Authors:  Frank Tanser; Till Bärnighausen; Graham S Cooke; Marie-Louise Newell
Journal:  Int J Epidemiol       Date:  2009-03-04       Impact factor: 7.196

7.  HIV/AIDS epidemic among older adults in China during 2005-2012: results from trend and spatial analysis.

Authors:  Jiannan Xing; Yin-ge Li; Weiming Tang; Wei Guo; Zhengwei Ding; Guowei Ding; Liyan Wang; Qianqian Qin; Yan Xu; Shasha Qian; Tanmay Mahapatra; Lu Wang
Journal:  Clin Infect Dis       Date:  2014-04-03       Impact factor: 9.079

8.  Mapping HIV prevalence in sub-Saharan Africa between 2000 and 2017.

Authors:  Laura Dwyer-Lindgren; Michael A Cork; Amber Sligar; Krista M Steuben; Kate F Wilson; Naomi R Provost; Benjamin K Mayala; John D VanderHeide; Michael L Collison; Jason B Hall; Molly H Biehl; Austin Carter; Tahvi Frank; Dirk Douwes-Schultz; Roy Burstein; Daniel C Casey; Aniruddha Deshpande; Lucas Earl; Charbel El Bcheraoui; Tamer H Farag; Nathaniel J Henry; Damaris Kinyoki; Laurie B Marczak; Molly R Nixon; Aaron Osgood-Zimmerman; David Pigott; Robert C Reiner; Jennifer M Ross; Lauren E Schaeffer; David L Smith; Nicole Davis Weaver; Kirsten E Wiens; Jeffrey W Eaton; Jessica E Justman; Alex Opio; Benn Sartorius; Frank Tanser; Njeri Wabiri; Peter Piot; Christopher J L Murray; Simon I Hay
Journal:  Nature       Date:  2019-05-15       Impact factor: 49.962

Review 9.  Spatial epidemiology: current approaches and future challenges.

Authors:  Paul Elliott; Daniel Wartenberg
Journal:  Environ Health Perspect       Date:  2004-06       Impact factor: 9.031

10.  Risk behaviors, prevalence of HIV and hepatitis C virus infection and population size of current injection drug users in a China-Myanmar border city: results from a Respondent-Driven Sampling Survey in 2012.

Authors:  Lei Li; Sawitri Assanangkornchai; Lin Duo; Edward McNeil; Jianhua Li
Journal:  PLoS One       Date:  2014-09-09       Impact factor: 3.240

View more
  2 in total

1.  Spatiotemporal Distribution of HIV Self-testing Kits Purchased on the Web and Implications for HIV Prevention in China: Population-Based Study.

Authors:  Ganfeng Luo; Lingyun Su; Anping Feng; Yi-Fan Lin; Yiguo Zhou; Tanwei Yuan; Yuqing Hu; Song Fan; Yong Lu; Yingsi Lai; Qian Shi; Jun Li; Mengjie Han; Huachun Zou
Journal:  JMIR Public Health Surveill       Date:  2022-10-04

2.  Influence of the Demographic, Social, and Environmental Factors on the COVID-19 Pandemic-Analysis of the Local Variations Using Geographically Weighted Regression.

Authors:  Krzysztof Rząsa; Mateusz Ciski
Journal:  Int J Environ Res Public Health       Date:  2022-09-20       Impact factor: 4.614

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.