Spatial distribution and characteristics of HIV clusters in Ethiopia

Ying, Roger; Fekadu, Lelisa; Schackman, Bruce R.; Verguet, Stéphane

doi:10.1111/tmi.13356

Cited by 12 publications

(14 citation statements)

References 21 publications

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“…Substantial spatial variation was observed in all three diseases at regional and local levels in Ethiopia. Previous studies have reported similar spatial clustering of HIV, TB and malaria in Ethiopia 13 15 53. However, the current study provided additional information in which the spatial distribution of HIV, TB and malaria overlapped in some parts of the country.…”

Section: Discussionsupporting

confidence: 45%

Spatial codistribution of HIV, tuberculosis and malaria in Ethiopia

et al. 2022

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BackgroundHIV, tuberculosis (TB) and malaria are the three most important infectious diseases in Ethiopia, and sub-Saharan Africa. Understanding the spatial codistribution of these diseases is critical for designing geographically targeted and integrated disease control programmes. This study investigated the spatial overlap and drivers of HIV, TB and malaria prevalence in Ethiopia.MethodsHIV, TB and malaria data were obtained from different nationwide prevalence surveys, and geospatial covariates were obtained from publicly available sources. A Bayesian model-based geostatistical framework was applied to each survey leveraging the strength of high-resolution spatial covariates to predict continuous disease-specific prevalence surfaces and their codistribution.ResultsThe national prevalence was 1.54% (95% CI 1.40 to 1.70) for HIV, 0.39% (95% CI 0.34 to 0.45) for TB and 1.1% (95%CI 0.95 to 1.32) for malaria. Substantial subnational variation was predicted with the highest HIV prevalence estimated in Gambela (4.52%), Addis Ababa (3.52%) and Dire Dawa (2.67%) regions. TB prevalence was highest in Dire Dawa (0.96%) and Gambela (0.88%), while malaria was highest in Gambela (6.1%) and Benishangul-Gumuz (3.8%). Spatial overlap of their prevalence was observed in some parts of the country, mainly Gambela region. Spatial distribution of the diseases was significantly associated with healthcare access, demographic, and climatic factors.ConclusionsThe national distribution of HIV, TB and malaria was highly focal in Ethiopia, with substantial variation at subnational and local levels. Spatial distribution of the diseases was significantly associated with healthcare access, demographic and climatic factors. Spatial overlap of HIV, TB and malaria prevalence was observed in some parts of the country. Integrated control programmes for these diseases should be targeted to these areas with high levels of co-endemicity.

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Section: Discussionsupporting

confidence: 45%

Spatial codistribution of HIV, tuberculosis and malaria in Ethiopia

et al. 2022

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“…Even though adult HIV prevalence, or the proportion of persons in a population who are living with HIV at a specific point in time, has declined at the national level, little information is available about sub-geographic areas and certain subpopulations in urban Ethiopia. Analysis of data from the 2011-2016 demographic and health survey in Ethiopia indicated that the distribution of HIV infection in Ethiopia is not random [6][7][8]. A study in one region in Ethiopia revealed that low educational status and migration status are determinants of HIV infection in Ethiopia [9].…”

Section: Introductionmentioning

confidence: 99%

“…Geospatial analysis of epidemiological data can generate precise maps of hotspot locations where HIV prevalence is concentrated [13]. Local spatial analyses can show geographic variation of the HIV epidemic and its drivers and inform targeted interventions; however, few geospatial analyses use data from subpopulations in Ethiopia [6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Spatial distribution and determinants of HIV prevalence among adults in urban Ethiopia: Findings from the Ethiopia Population-based HIV Impact Assessment Survey (2017–2018)

et al. 2022

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The design and evaluation of national HIV programs often rely on aggregated national data, which may obscure localized HIV epidemics. In Ethiopia, even though the national adult HIV prevalence has decreased, little information is available about local areas and subpopulations. To inform HIV prevention efforts for specific populations, we identified geographic locations and drivers of HIV transmission. We used data from adults aged 15–64 years who participated in the Ethiopian Population-based HIV Impact Assessment survey (October 2017–April 2018). Location-related information for the survey clusters was obtained from the 2007 Ethiopia population census. Spatial autocorrelation of HIV prevalence data were analyzed via a Global Moran’s I test. Geographically weighted regression analysis was used to show the relationship of covariates. The finding indicated that uncircumcised men in certain hotspot towns and divorced or widowed individuals in hotspot woredas/towns might have contributed to the average increase in HIV prevalence in the hotspot areas. Hotspot analysis findings indicated that, localized, context-specific intervention efforts tailored to at-risk populations, such as divorced or widowed women or uncircumcised men, could decrease HIV transmission and prevalence in urban Ethiopia.

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“…The HIV-1 group M is responsible for the global pandemic associated with HIV; the HIV-2 strain is mainly found in West Africa, Mozambique, Angola, and southwest India (Eberle & Gürtler, 2012), and is less pathogenic than the HIV-1 strain. Geographic HIV clusters are driven by different biological and behavioural risk factors (Ying et al, 2020). In eastern and southern Africa, HIV prevalence among sex workers is extremely high; adolescent girls and young women account for 30% of new infections, and above 50% of sex workers are living with HIV (UNAIDS, 2020).…”

Section: Introductionmentioning

confidence: 99%

Methodological Approaches to Spatiotemporal Analysis in HIV Epidemiology - a protocol for a systematic review

Eze-Emiri

Igwe

Patrick

et al. 2022

Preprint

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Background There is a geographic disparity in the epidemiology of HIV infection globally. These differences are interrelated with the sociodemographic and behavioural circumstances applicable to the respective regions. For instance, the HIV-2 strain is mostly found in West Africa. The most significant number of people injecting drugs (PWID) are in East and South-East Asia, North America, and Eastern Europe; they also have the highest prevalence of HIV among PWID. Spatiotemporal analytical methods use geographic and time-related factors to explain observed spatial heterogeneity; thereby, identifying disease patterns, risk factors, and trends relevant to a particular region. Spatiotemporal analytical methods use geographic and time-related factors to explain observed spatial heterogeneity; thereby, identifying disease patterns, risk factors, and trends relevant to a particular region. Objectives This paper presents a protocol for a systematic review that will describe the methods used in the spatial analysis of HIV epidemiology globally. Methods A systematic literature search of geospatial studies of HIV will be conducted using PubMed, EBSCOhost, and Google scholar; with neither language nor date restriction from inception to date. The protocol for this systematic review was prospectively registered in PROSPERO with ID number –CRD42022314604. Results Results will be available once the review is finalised. Discussion This systematic review will identify and report the various spatial analytical methods that have been employed in HIV epidemiology; in addition to highlighting the predominant spatial methodologies applied.

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Spatial distribution and characteristics of HIV clusters in Ethiopia

Cited by 12 publications

References 21 publications

Spatial codistribution of HIV, tuberculosis and malaria in Ethiopia

Spatial codistribution of HIV, tuberculosis and malaria in Ethiopia

Spatial distribution and determinants of HIV prevalence among adults in urban Ethiopia: Findings from the Ethiopia Population-based HIV Impact Assessment Survey (2017–2018)

Methodological Approaches to Spatiotemporal Analysis in HIV Epidemiology - a protocol for a systematic review

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