PBDEs in the atmosphere over the Asian marginal seas, and the Indian and Atlantic oceans

Air samples were collected from Jan 16 to Mar 14, 2008 onboard the Oceanic II- The Scholar Ship which navigated an east–west transect from Shanghai to Cape Verde, and polybrominated diphenyl ethers (PBDEs) were analyzed in these samples. PBDE concentrations in the atmosphere over the open seas were influenced by proximity to source areas and land, and air mass origins. The concentrations of Σ21PBDEs over the East and South China Seas, the Bay of Bengal and the Andaman Sea, the Indian Ocean, and the Atlantic Ocean were 10.8 ± 6.13, 3.22 ± 1.57, 5.12 ± 3.56, and 2.87 ± 1.81 pg m−3, respectively. BDE-47 and -99 were the dominant congeners in all the samples, suggesting that the widely used commercial penta-BDE products were the original sources. Over some parts of Atlantic and Indian Ocean, daytime concentrations of BDE-47 and BDE-99 were higher than the concentrations at night. The strong atmospheric variability does not always coincide with a diurnal cycle, but the variability in air concentrations in such remote areas of the ocean remains strong. No significant trends were found for each of PBDE congener with latitude.

Public-health and individual approaches to antiretroviral therapy: township South Africa and Switzerland compared

BACKGROUND: The provision of highly active antiretroviral therapy (HAART) in resource-limited settings follows a public health approach, which is characterised by a limited number of regimens and the standardisation of clinical and laboratory monitoring. In industrialized countries doctors prescribe from the full range of available antiretroviral drugs, supported by resistance testing and frequent laboratory monitoring. We compared virologic response, changes to first-line regimens, and mortality in HIV-infected patients starting HAART in South Africa and Switzerland. METHODS AND FINDINGS: We analysed data from the Swiss HIV Cohort Study and two HAART programmes in townships of Cape Town, South Africa. We included treatment-naïve patients aged 16 y or older who had started treatment with at least three drugs since 2001, and excluded intravenous drug users. Data from a total of 2,348 patients from South Africa and 1,016 patients from the Swiss HIV Cohort Study were analysed. Median baseline CD4+ T cell counts were 80 cells/mul in South Africa and 204 cells/mul in Switzerland. In South Africa, patients started with one of four first-line regimens, which was subsequently changed in 514 patients (22%). In Switzerland, 36 first-line regimens were used initially, and these were changed in 539 patients (53%). In most patients HIV-1 RNA was suppressed to 500 copies/ml or less within one year: 96% (95% confidence interval [CI] 95%-97%) in South Africa and 96% (94%-97%) in Switzerland, and 26% (22%-29%) and 27% (24%-31%), respectively, developed viral rebound within two years. Mortality was higher in South Africa than in Switzerland during the first months of HAART: adjusted hazard ratios were 5.90 (95% CI 1.81-19.2) during months 1-3 and 1.77 (0.90-3.50) during months 4-24. CONCLUSIONS: Compared to the highly individualised approach in Switzerland, programmatic HAART in South Africa resulted in similar virologic outcomes, with relatively few changes to initial regimens. Further innovation and resources are required in South Africa to both achieve more timely access to HAART and improve the prognosis of patients who start HAART with advanced disease.

CD4(+) T cell count decreases by ethnicity among untreated patients with HIV infection in South Africa and Switzerland

BACKGROUND: Estimates of the decrease in CD4(+) cell counts in untreated patients with human immunodeficiency virus (HIV) infection are important for patient care and public health. We analyzed CD4(+) cell count decreases in the Cape Town AIDS Cohort and the Swiss HIV Cohort Study. METHODS: We used mixed-effects models and joint models that allowed for the correlation between CD4(+) cell count decreases and survival and stratified analyses by the initial cell count (50-199, 200-349, 350-499, and 500-750 cells/microL). Results are presented as the mean decrease in CD4(+) cell count with 95% confidence intervals (CIs) during the first year after the initial CD4(+) cell count. RESULTS: A total of 784 South African (629 nonwhite) and 2030 Swiss (218 nonwhite) patients with HIV infection contributed 13,388 CD4(+) cell counts. Decreases in CD4(+) cell count were steeper in white patients, patients with higher initial CD4(+) cell counts, and older patients. Decreases ranged from a mean of 38 cells/microL (95% CI, 24-54 cells/microL) in nonwhite patients from the Swiss HIV Cohort Study 15-39 years of age with an initial CD4(+) cell count of 200-349 cells/microL to a mean of 210 cells/microL (95% CI, 143-268 cells/microL) in white patients in the Cape Town AIDS Cohort > or =40 years of age with an initial CD4(+) cell count of 500-750 cells/microL. CONCLUSIONS: Among both patients from Switzerland and patients from South Africa, CD4(+) cell count decreases were greater in white patients with HIV infection than they were in nonwhite patients with HIV infection.

Monitoring of antiretroviral therapy and mortality in HIV programmes in Malawi, South Africa and Zambia: mathematical modelling study

OBJECTIVES Mortality in patients starting antiretroviral therapy (ART) is higher in Malawi and Zambia than in South Africa. We examined whether different monitoring of ART (viral load [VL] in South Africa and CD4 count in Malawi and Zambia) could explain this mortality difference. DESIGN Mathematical modelling study based on data from ART programmes. METHODS We used a stochastic simulation model to study the effect of VL monitoring on mortality over 5 years. In baseline scenario A all parameters were identical between strategies except for more timely and complete detection of treatment failure with VL monitoring. Additional scenarios introduced delays in switching to second-line ART (scenario B) or higher virologic failure rates (due to worse adherence) when monitoring was based on CD4 counts only (scenario C). Results are presented as relative risks (RR) with 95% prediction intervals and percent of observed mortality difference explained. RESULTS RRs comparing VL with CD4 cell count monitoring were 0.94 (0.74-1.03) in scenario A, 0.94 (0.77-1.02) with delayed switching (scenario B) and 0.80 (0.44-1.07) when assuming a 3-times higher rate of failure (scenario C). The observed mortality at 3 years was 10.9% in Malawi and Zambia and 8.6% in South Africa (absolute difference 2.3%). The percentage of the mortality difference explained by VL monitoring ranged from 4% (scenario A) to 32% (scenarios B and C combined, assuming a 3-times higher failure rate). Eleven percent was explained by non-HIV related mortality. CONCLUSIONS VL monitoring reduces mortality moderately when assuming improved adherence and decreased failure rates.

The Chilean Experience in South-South Trade and Investment Agreements

This paper analyzes the main features of Chilean trade and investment treaties, examining if there is a Chilean pattern in the regulation of trade and investment flows or if it is influenced by agreements signed by Chile with developed countries. The article also examines if there are differences between the treaties signed by Chile and other “Southern” developing countries and those negotiated with “Northern” developed economies, and if sustainable development concerns are part of the negotiations of trade and investment agreements by Chile.