Suchergebnisse

In earlier work, human immunodeficiency virus type 1 (HIV-1) sequences were analysed to estimate the timing of the ancestral sequence of the main group of HIV-1, the virus that is responsible for the acquired immune deficiency syndrome pandemic, yielding a best estimate of 1931 (95% confidence interval of 1915-1941). That work will be briefly reviewed, outlining how phylogenetic tools were extended to incorporate improved evolutionary models, how the molecular clock model was adapted to incorporate variable periods of latency, and how the approach was validated by correctly estimating the timing of two historically documented dates. The advantages, limitations, and assumptions of the approach will be summarized, with particular consideration of the implications of branch length uncertainty and recombination. We have recently undertaken new phylogenetic analysis of an extremely diverse set of human immunodeficiency virus envelope sequences from the Democratic Republic of the Congo (the DRC, formerly Zaire). This analysis both corroborates and extends the conclusions of our original study. Coalescent methods were used to infer the demographic history of the HIV-1 epidemic in the DRC, and the results suggest an increase in the exponential growth rate of the infected population through time.

The global plan to eradicate hepatitis C virus (HCV) led by the World Health Organization outlines the use of highly effective direct‐acting antiviral drugs (DAAs) to achieve elimination by 2030. Identifying individuals with active disease and investigation of the breadth of diversity of the virus in sub‐Saharan Africa (SSA) is essential as genotypes in this region (where very few clinical trials have been carried out) are distinct from those found in other parts of the world. We undertook a population‐based, nested case‐control study in Uganda and obtained additional samples from the Democratic Republic of Congo (DRC) to estimate the prevalence of HCV, assess strategies for disease detection using serological and molecular techniques, and characterize genetic diversity of the virus. Using next‐generation and Sanger sequencing, we aimed to identify strains circulating in East and Central Africa. A total of 7,751 Ugandan patients were initially screened for HCV, and 20 PCR‐positive samples were obtained for sequencing. Serological assays were found to vary significantly in specificity for HCV. HCV strains detected in Uganda included genotype (g) 4k, g4p, g4q, and g4s and a newly identified unassigned g7 HCV strain. Two additional unassigned g7 strains were identified in patients originating from DRC (one partial and one full open reading frame sequence). These g4 and g7 strains contain nonstructural (ns) protein 3 and 5A polymorphisms associated with resistance to DAAs in other genotypes. Clinical studies are therefore indicated to investigate treatment response in infected patients. Conclusion: Although HCV prevalence and genotypes have been well characterized in patients in well‐resourced countries, clinical trials are urgently required in SSA, where highly diverse g4 and g7 strains circulate.

Background: Since late 2015, an epidemic of Yellow fever virus (YFV) has caused over 6,554 suspected cases in Angola and the Democratic Republic of Congo, including 387 deaths. We sought to understand the spatial spread of this YFV outbreak to optimise the use of the limited available vaccine stock. Methods: We jointly analysed datasets describing the epidemic of YFV, vector suitability, human demography and mobility in Central Africa in order to understand and predict the expansion of YFV. We used a standard logistic model to infer the district YFV infection risk over the course of the epidemic in the region. Findings: Early spread of YFV was characterized by fast exponential growth (doubling time of 5-7 days) and fast spatial expansion (49 districts reporting cases after only three months) from Luanda, the capital of Angola. Early invasion was positively correlated with high population density (0·52, 95% CI: 0·34, 0·66). The further away locations were from Luanda the later the invasion date (0·60, 95% CI: 0·52, 0·66). Districts with higher population densities also featured higher risks of sustained transmission. A model that captured human mobility and vector suitability successfully discriminated districts with high risk of invasion from others. If at the start of the epidemic sufficient vaccines had been available to target 50 out of 313 districts in the area, our model would have correctly identified 27 (84%) of the 32 districts that were eventually affected. Interpretation: Our findings reveal the contributions of ecological and demographic factors to the ongoing spread of the YFV outbreak and provide estimates for where vaccines may be prioritised, although other constraints (e.g. vaccine supply and delivery) need to be accounted for before such insights may be translated into policy.