Impact of Endemic Infections on HIV Susceptibility in Sub-Saharan Africa

Yegorov, Sergey; Joag, Vineet; Galiwango, Ronald M.; Good, Sara V.; Okech, Brenda; Kaul, Rupert

doi:10.1186/s40794-019-0097-5

Cited by 16 publications

(15 citation statements)

References 237 publications

(282 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…And even though we included many more variables than is common practice ( Hajizadeh et al., 2014 ; Lakew, Benedict & Haile, 2015 ; Kidman & Anglewicz, 2016 ; Kim, Skordis-Worrall & Haghparast-Bidgoli, 2016 ; Ashaba et al., 2018 ; Kenyon, Buyze & Schwartz, 2018 ), we still had to exclude many factors that can play a critical role in HIV transmission, including the prevalence of excessive alcohol consumption, STIs ( Looker et al., 2017 ; Torrone et al., 2018 ) (ex. genital herpes, gonorrhea and syphilis), endemic infections ( Hotez et al., 2019 ; Yegorov et al., 2019 )(ex. malaria and helminthiases), ART adherence and drug resistance, as well as the distribution of different HIV strains and subtypes ( Buonaguro, Tornesello & Buonaguro, 2007 ; Esbjörnsson et al., 2019 ; Gartner et al., 2020 ).…”

Section: Discussionmentioning

confidence: 99%

Clusters of sub-Saharan African countries based on sociobehavioural characteristics and associated HIV incidence

Merzouki

Estill

Orel

et al. 2021

PeerJ

View full text Add to dashboard Cite

Introduction HIV incidence varies widely between sub-Saharan African (SSA) countries. This variation coincides with a substantial sociobehavioural heterogeneity, which complicates the design of effective interventions. In this study, we investigated how sociobehavioural heterogeneity in sub-Saharan Africa could account for the variance of HIV incidence between countries. Methods We analysed aggregated data, at the national-level, from the most recent Demographic and Health Surveys of 29 SSA countries (2010–2017), which included 594,644 persons (183,310 men and 411,334 women). We preselected 48 demographic, socio-economic, behavioural and HIV-related attributes to describe each country. We used Principal Component Analysis to visualize sociobehavioural similarity between countries, and to identify the variables that accounted for most sociobehavioural variance in SSA. We used hierarchical clustering to identify groups of countries with similar sociobehavioural profiles, and we compared the distribution of HIV incidence (estimates from UNAIDS) and sociobehavioural variables within each cluster. Results The most important characteristics, which explained 69% of sociobehavioural variance across SSA among the variables we assessed were: religion; male circumcision; number of sexual partners; literacy; uptake of HIV testing; women’s empowerment; accepting attitude toward people living with HIV/AIDS; rurality; ART coverage; and, knowledge about AIDS. Our model revealed three groups of countries, each with characteristic sociobehavioural profiles. HIV incidence was mostly similar within each cluster and different between clusters (median (IQR); 0.5/1000 (0.6/1000), 1.8/1000 (1.3/1000) and 5.0/1000 (4.2/1000)). Conclusions Our findings suggest that the combination of sociobehavioural factors play a key role in determining the course of the HIV epidemic, and that similar techniques can help to predict the effects of behavioural change on the HIV epidemic and to design targeted interventions to impede HIV transmission in SSA.

show abstract

Section: Discussionmentioning

confidence: 99%

Clusters of sub-Saharan African countries based on sociobehavioural characteristics and associated HIV incidence

Merzouki

Estill

Orel

et al. 2021

PeerJ

View full text Add to dashboard Cite

show abstract

“…However, many West and Central African countries with population characteristics like Mozambique in terms of sexual practices, literacy, knowledge about AIDS, HIV testing and ART coverage, had much lower HIV prevalence and incidence, possibly because males were circumcised at twice the rate. Compared to other West and Central African countries, an aggravating factor in Mozambique can also be the high prevalence of female genital schistosomiasis (Hotez et al, 2019;Yegorov et al, 2019). On the other side of the spectrum, despite a low uptake of male circumcision, it is also possible that the combination of lower numbers of sexual partners, higher per capita rural populations, more literacy, more accurate knowledge about AIDS, more HIV testing, and broader ART coverage could account for lower HIV incidence, like in Rwanda and Burundi.…”

Section: Discussionmentioning

confidence: 99%

“…And even though we included many more variables than is common practice (Hajizadeh et al, 2014;Lakew, Benedict & Haile, 2015;Kidman & Anglewicz, 2016;Kim et al, 2016;Ashaba et al, 2018;Kenyon, Buyze & Schwartz, 2018), we still had to exclude many factors that can play a critical role in HIV transmission, including the prevalence of excessive alcohol consumption, STIs (Looker et al, 2017;Torrone et al, 2018) (ex. genital herpes, gonorrhea and syphilis), endemic infections (Hotez et al, 2019;Yegorov et al, 2019)(ex. malaria and helminthiases), ART adherence and drug resistance, as well as the distribution of different HIV strains and subtypes (Buonaguro, Tornesello & Buonaguro, 2007;Esbjörnsson et al, 2019;Gartner et al, 2020).…”

Section: Discussionmentioning

confidence: 99%

Clusters of sub-Saharan African countries based on sociobehavioural characteristics and associated HIV incidence

Merzouki¹,

Estill

Orel³

et al. 2019

Preprint

View full text Add to dashboard Cite

ObjectiveHIV incidence varies widely between sub-Saharan African (SSA) countries. This variation coincides with a substantial sociobehavioural heterogeneity, which complicates the design of effective interventions. In this study, we investigated how socio-behavioural heterogeneity in sub-Saharan Africa could account for the variance of HIV incidence between countries.MethodsWe used unsupervised machine learning to analyse data from the Demographic and Health Surveys of 29 SSA countries completed after 2010. We preselected 48 demographic, socio-economic, behavioural and HIV-related attributes to describe each country. We used Principle Component Analysis to visualize sociobehavioural similarity between countries, and to identify the variables that accounted for most sociobehavioural variance in SSA. We used hierarchical clustering to identify groups of countries with similar sociobehavioural profiles, and we compared the distribution of HIV incidence and sociobehavioural variables within each cluster.FindingsThe most important characteristics, which explained 69% of sociobehavioural variance across SSA among the variables we assessed were: religion; male circumcision; number of sexual partners; literacy; uptake of HIV testing; women’s empowerment; accepting attitude toward people living with HIV/AIDS; rurality; ART coverage; and, knowledge about AIDS. Our model revealed three groups of countries, each with characteristic sociobehavioural profiles. HIV incidence was mostly similar within each cluster and different between clusters (median(IQR); 0.5/1000(0.6/1000), 1.8/1000(1.3/1000) and 5.0/1000(4.2/1000)).ConclusionOur findings suggest that sociobehavioural factors play a key role in determining the course of the HIV epidemic, and that similar techniques can help to design and predict the effects of targeted country-specific interventions to impede HIV transmission.Research in contextKnowledge before this studyWe searched PubMed with the terms: “HIV”, “inequality”, “factors” and “sub-Saharan Africa” for articles published in English before February 28th, 2019. The reviewed literature was usually limited to a certain sub-population, sub-national region, or country; but some recent studies covered up to 31 sub-Saharan African countries. Based on a relatively small number of variable (5 to 13), and using descriptive statistics, regressions and concentration indices, previous works analysed the association between socio-economic inequalities, male circumcision, high-risk sexual behaviour, or HIV-related stigma, with HIV testing, uptake of treatment, ART adherence, or HIV prevalence.Contribution of this studyTo our knowledge, this is the first study where unsupervised machine learning techniques (Principle Component Analysis and hierarchical clustering) were used to analyse the sociobehavioural heterogeneity in sub-Saharan Africa (SSA) and how it associates with the variability of HIV incidence in the region. We identified three distinct sociobehavioural profiles, which were associated with different geographical regions and different levels of HIV incidence in SSA. Because the association between the variability of HIV incidence across SSA and its underlying sociobehavioural factors is still not well understood, we believe that our analysis that compares 29 SSA countries based on 48 sociobehavioural characteristics brings significant value to the field. Identifying and comparing sociobehavioural profiles of countries helps to design and predict the effect of tailored country-specific interventions to impede HIV transmission.

show abstract

“…Interestingly, in chronic HIV-1 infection, HIV causes the Th1 subclass to switch predominately to the Th2 subclass [ 68 , 69 , 70 , 71 ]. This leads to a decrease in the Th1:Th2 ratio from an alteration in cytokine balance.…”

Section: Th1 Vs Th2 In Context Of Tb and Hivmentioning

confidence: 99%

“…Overall, these studies support the importance of Th1 cells' role in inhibiting M. tb infections. Interestingly, in chronic HIV-1 infection, HIV causes the Th1 subclass to switch predominately to the Th2 subclass [68][69][70][71]. This leads to a decrease in the Th1:Th2 ratio from an alteration in cytokine balance.…”

Section: Th1 Vs Th2 In Context Of Tb and Hivmentioning

confidence: 99%

The Role of Dendritic Cells in TB and HIV Infection

Abrahem

Chiang

Haquang

et al. 2020

JCM

View full text Add to dashboard Cite

Dendritic cells are the principal antigen-presenting cells (APCs) in the host defense mechanism. An altered dendritic cell response increases the risk of susceptibility of infections, such as Mycobacterium tuberculosis (M. tb), and the survival of the human immunodeficiency virus (HIV). The altered response of dendritic cells leads to decreased activity of T-helper-1 (Th1), Th2, Regulatory T cells (Tregs), and Th17 cells in tuberculosis (TB) infections due to a diminishment of cytokine release from these APCs, while HIV infection leads to DC maturation, allowing DCs to migrate to lymph nodes and the sub-mucosa where they then transfer HIV to CD4 T cells, although there is controversy around this topic. Increases in the levels of the antioxidant glutathione (GSH) plays a critical role in maintaining dendritic cell redox homeostasis, leading to an adequate immune response with sufficient cytokine release and a subsequent robust immune response. Thus, an understanding of the intricate pathways involved in the dendritic cell response are needed to prevent co-infections and co-morbidities in individuals with TB and HIV.

show abstract

Impact of Endemic Infections on HIV Susceptibility in Sub-Saharan Africa

Cited by 16 publications

References 237 publications

Clusters of sub-Saharan African countries based on sociobehavioural characteristics and associated HIV incidence

Clusters of sub-Saharan African countries based on sociobehavioural characteristics and associated HIV incidence

Clusters of sub-Saharan African countries based on sociobehavioural characteristics and associated HIV incidence

The Role of Dendritic Cells in TB and HIV Infection

Contact Info

Product

Resources

About