Evidence map›Paper›PMID 36443848›Full record

ArticleInfectious diseases of poverty2022

Spatial-temporal heterogeneity and determinants of HIV prevalence in the Mano River Union countries.

Idrissa Laybohr Kamara, Liang Wang, Yaxin Guo, Shuting Huo, Yuanyuan Guo, Chengdong Xu, Yilan Liao, William J Liu, Wei Ma, George F Gao

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Article in Infectious diseases of poverty, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

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6citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Idrissa Laybohr KamaraDepartment of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, 250012, China.
Liang WangCAS Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Center for Influenza Research and Early-Warning (CASCIRE), CAS-TWAS Center of Excellence for Emerging Infectious Diseases (CEEID), Chinese Academy of Sciences, Beijing, 100101, China.
Yaxin GuoNHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China.
Shuting HuoNHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China.
Yuanyuan GuoDepartment of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, 250012, China.
Chengdong XuState Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China.
Yilan LiaoState Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China.
William J LiuNHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China.
Wei MaDepartment of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, 250012, China. weima@sdu.edu.cn.
George F GaoDepartment of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, 250012, China. gaof@im.ac.cn.ORCID http://orcid.org/0000-0002-3869-615X

Funding

Projects of International Cooperation and Exchanges NSFC 82161148008the Excellent Young Scientist Program of the NSFC 81822040
6 · The paper itself

Abstract

backgroundUtilizing population-based survey data in epidemiological research with a spatial perspective can integrate valuable context into the dynamics of HIV prevalence in West Africa. However, the situation in the Mano River Union (MRU) countries is largely unknown. This research aims to perform an ecological study to determine the HIV prevalence patterns in MRU.

methodsWe analyzed Demographic and Health Survey (DHS) and AIDS Indicator Survey (AIS) data on HIV prevalence in MRU from 2005 to 2020. We examined the country-specific, regional-specific and sex-specific ratios of respondents to profile the spatial-temporal heterogeneity of HIV prevalence and determine HIV hot spots. We employed Geodetector to measure the spatial stratified heterogeneity (SSH) of HIV prevalence for adult women and men. We assessed the comprehensive correct knowledge (CCK) about HIV/AIDS and HIV testing uptake by employing the Least Absolute Shrinkage and Selection Operator (LASSO) regression to predict which combinations of CCKs can scale up the ratio of HIV testing uptake with sex-specific needs.

resultsIn our analysis, we leveraged data for 158,408 respondents from 11 surveys in the MRU. From 2005-2015, Cote d'Ivoire was the hot spot for HIV prevalence with a Gi_Bin score of 3, Z-Score 8.0-10.1 and P < 0.001. From 2016 to 2020, Guinea and Sierra Leone were hot spots for HIV prevalence with a Gi_Bin score of 2, Z-Score of 3.17 and P < 0.01. The SSH confirmed the significant differences in HIV prevalence at the national level strata, with a higher level for Cote d'Ivoire compared to other countries in both sexes with q-values of 0.61 and 0.40, respectively. Our LASSO model predicted different combinations of CCKs with sex-specific needs to improve HIV testing uptake.

conclusionsThe spatial distribution of HIV prevalence in the MRU is skewed and the CCK about HIV/AIDS and HIV testing uptake are far below the threshold target set by UNAIDS for ending the epidemic in the sub-region. Geodetector detected statistically significant SSH within and between countries in the MRU. Our LASSO model predicted that different emphases should be implemented when popularizing the CCK about HIV/AIDS for adult women and men.

Indexed as

Acquired Immunodeficiency SyndromeEpidemicsAdultCote d'IvoireFemaleHumansMalePrevalenceSexual BehaviorAfricaComprehensive correct knowledgeGeodetectorLeast Absolute Shrinkage and Selection OperatorMachine learningSpatial distribution of HIV prevalenceSpatial stratified heterogeneity

Identifiers

PMID36443848
PMCPMC9706865

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.