Associated health and social determinants of mobile populations across HIV epidemic gradients in Southern Africa.

Disease mapping Health determinants Mobile population Southern Africa Spatial epidemiology

Journal

Journal of migration and health
ISSN: 2666-6235
Titre abrégé: J Migr Health
Pays: England
ID NLM: 101774615

Informations de publication

Date de publication:
2021
Historique:
received: 06 05 2020
revised: 11 03 2021
accepted: 22 03 2021
entrez: 18 8 2021
pubmed: 19 8 2021
medline: 19 8 2021
Statut: epublish

Résumé

Growing travel connectivity and economic development have dramatically increased the magnitude of human mobility in Africa. In public health, vulnerable population groups such as mobile individuals are at an elevated risk of sexually transmitted diseases, including HIV. The population-based Demographic Health Survey data of five Southern African countries with different HIV epidemic intensities (Angola, Malawi, South Africa, Zambia, and Zimbabwe) were used to investigate the association between HIV serostatus and population mobility adjusting for socio-demographic, sexual behavior and spatial covariates. Mobility was associated with HIV seropositive status only in Zimbabwe (adjusted odds ratio [AOR] = 1.37 [95% confidence interval [CI]: 1.01-1.67]). These associations were not significant in Angola, Malawi, South Africa, and Zambia. Females had higher odds of mobility than males in Zimbabwe (AOR = 1.37, CI: 1.10-1.69). The odds of mobility decreased with age in all five countries. Our findings highlight the heterogeneity of the social and health determinants of mobile populations in several countries with different HIV epidemic intensities. Effective interventions using precise geographic focus combined with detailed attribute characterization of mobile populations can enhance their impact especially in areas with high density of mobile individuals and high HIV prevalence.

Sections du résumé

BACKGROUND BACKGROUND
Growing travel connectivity and economic development have dramatically increased the magnitude of human mobility in Africa. In public health, vulnerable population groups such as mobile individuals are at an elevated risk of sexually transmitted diseases, including HIV.
METHODS METHODS
The population-based Demographic Health Survey data of five Southern African countries with different HIV epidemic intensities (Angola, Malawi, South Africa, Zambia, and Zimbabwe) were used to investigate the association between HIV serostatus and population mobility adjusting for socio-demographic, sexual behavior and spatial covariates.
RESULTS RESULTS
Mobility was associated with HIV seropositive status only in Zimbabwe (adjusted odds ratio [AOR] = 1.37 [95% confidence interval [CI]: 1.01-1.67]). These associations were not significant in Angola, Malawi, South Africa, and Zambia. Females had higher odds of mobility than males in Zimbabwe (AOR = 1.37, CI: 1.10-1.69). The odds of mobility decreased with age in all five countries.
CONCLUSIONS CONCLUSIONS
Our findings highlight the heterogeneity of the social and health determinants of mobile populations in several countries with different HIV epidemic intensities. Effective interventions using precise geographic focus combined with detailed attribute characterization of mobile populations can enhance their impact especially in areas with high density of mobile individuals and high HIV prevalence.

Identifiants

pubmed: 34405186
doi: 10.1016/j.jmh.2021.100038
pii: S2666-6235(21)00005-2
pmc: PMC8352162
doi:

Types de publication

Journal Article

Langues

eng

Pagination

100038

Informations de copyright

© 2021 The Authors. Published by Elsevier Ltd.

Déclaration de conflit d'intérêts

None.

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Auteurs

Esteban Correa-Agudelo (E)

Department of Geography and Geographic Information Science, University of Cincinnati, Cincinnati, OH, 45221, USA.
Health Geography and Disease Modeling Laboratory, University of Cincinnati, Cincinnati, USA.

Hae-Young Kim (HY)

Africa Health Research Institute, KwaZulu-Natal, South Africa.
KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP) KwaZulu-Natal, South Africa.
Department of Population Health, New York University Grossman School of Medicine, USA.

Godfrey N Musuka (GN)

ICAP at Columbia University, Harare, Zimbabwe.

Zindoga Mukandavire (Z)

Centre for Data Science, Coventry University, UK.
School of Computing, Electronics and Mathematics, Coventry University, UK.

Adam Akullian (A)

Institute for Disease Modeling, Global Good Fund, Bellevue, Washington, USA.
Department of Global Health, University of Washington, Seattle, Washington, USA.

Diego F Cuadros (DF)

Department of Geography and Geographic Information Science, University of Cincinnati, Cincinnati, OH, 45221, USA.
Health Geography and Disease Modeling Laboratory, University of Cincinnati, Cincinnati, USA.

Classifications MeSH