Exports, HIV incidence and the Baltic Dry Index: Further evidence from sub-Saharan Africa

2015 ◽  
Vol 126 ◽  
pp. 35-39 ◽  
Author(s):  
Faqin Lin ◽  
Nicholas C.S. Sim
Author(s):  
Ngoc Thien Anh Pham ◽  
Nicholas Sim

Abstract Unlike other developing countries, urbanisation in sub-Saharan Africa appears to be unaccompanied by an improvement in economic fundamentals. This paper provides new evidence that exports may increase urbanisation in sub-Saharan Africa. To address the issue of reverse causality, we instrument exports with information linked to the Baltic Dry Index, which reflects the shipping cost of primary commodities that the sub-Saharan Africa countries mainly export. To handle a large class of confounding variables and cross-sectional dependence, we employ panel regressions with interactive fixed effects. We find that exports have a sizable positive effect on urbanisation. Interestingly, we also find that exports will lose their statistical significance if cross-sectional dependence is overlooked, suggesting that the true effect of an economic fundamental on urbanisation could be obscured by cross-sectional dependence.


2021 ◽  
Author(s):  
Deepa Jahagirdar ◽  
Magdalene Walters ◽  
Avina Vongpradith ◽  
Xiaochen Dai ◽  
Amanda Novotney ◽  
...  

AbstractHIV incidence in sub-Saharan Africa declined substantially between 2000 and 2015. In this analysis, we consider the relative associations of nine structural and individual determinants with this decline. A linear mixed effects model of logged HIV incidence rates versus determinants was used. The data were from mathematical modelling as part of the 2019 Global Burden of Disease Study in 43 sub-Saharan African countries. We used forwards selection to determine a single final model of HIV incidence rate. The association of economic variables and HIV knowledge with incidence was found to be driven by education, while ART coverage had the largest impact on other determinants’ coefficients. In the final model, education years per capita contributed the most to explaining variation in HIV incidence rates; a 1-year increase in mean education years was associated with a 0.39 (− 0.56; − 0.2, t = − 4.48 p < 0.01) % decline in incidence rate while a unit increase in ART coverage was associated with a 0.81 (− 1.34; − 0.28, t = − 3.01, p < 0.01) % decline in incidence rate.


Vaccine ◽  
2009 ◽  
Vol 27 (6) ◽  
pp. 940-946 ◽  
Author(s):  
Esther E. Freeman ◽  
Richard G. White ◽  
Roel Bakker ◽  
Kate K. Orroth ◽  
Helen A. Weiss ◽  
...  

2019 ◽  
Author(s):  
Aziza Merzouki ◽  
Janne Estill ◽  
Erol Orel ◽  
Kali Tal ◽  
Olivia Keiser

AbstractIntroductionHIV 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.MethodsWe 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.ResultsThe 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)).


2016 ◽  
Vol 3 (9) ◽  
pp. e441-e448 ◽  
Author(s):  
Jessica B McGillen ◽  
Sarah-Jane Anderson ◽  
Mark R Dybul ◽  
Timothy B Hallett

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