Estimating malaria transmission intensity from Plasmodium falciparum serological data using antibody density models.

BACKGROUND: Serological data are increasingly being used to monitor malaria transmission intensity and have been demonstrated to be particularly useful in areas of low transmission where traditional measures such as EIR and parasite prevalence are limited. The seroconversion rate (SCR) is usually estimated using catalytic models in which the measured antibody levels are used to categorize individuals as seropositive or seronegative. One limitation of this approach is the requirement to impose a fixed cut-off to distinguish seropositive and negative individuals. Furthermore, the continuous variation in antibody levels is ignored thereby potentially reducing the precision of the estimate. METHODS: An age-specific density model which mimics antibody acquisition and loss was developed to make full use of the information provided by serological measures of antibody levels. This was fitted to blood-stage antibody density data from 12 villages at varying transmission intensity in Northern Tanzania to estimate the exposure rate as an alternative measure of transmission intensity. RESULTS: The results show a high correlation between the exposure rate estimates obtained and the estimated SCR obtained from a catalytic model (r = 0.95) and with two derived measures of EIR (r = 0.74 and r = 0.81). Estimates of exposure rate obtained with the density model were also more precise than those derived from catalytic models. CONCLUSION: This approach, if validated across different epidemiological settings, could be a useful alternative framework for quantifying transmission intensity, which makes more complete use of serological data

Febrile illness diagnostics and the malaria-industrial complex: a socio-environmental perspective

Abstract Background Global prioritization of single-disease eradication programs over improvements to basic diagnostic capacity in the Global South have left the world unprepared for epidemics of chikungunya, Ebola, Zika, and whatever lies on the horizon. The medical establishment is slowly realizing that in many parts of sub-Saharan Africa (SSA), particularly urban areas, up to a third of patients suffering from acute fever do not receive a correct diagnosis of their infection. Main body Malaria is the most common diagnosis for febrile patients in low-resource health care settings, and malaria misdiagnosis has soared due to the institutionalization of malaria as the primary febrile illness of SSA by international development organizations and national malaria control programs. This has inadvertently created a “malaria-industrial complex” and historically obstructed our complete understanding of the continent’s complex communicable disease epidemiology, which is currently dominated by a mélange of undiagnosed febrile illnesses. We synthesize interdisciplinary literature from Ghana to highlight the complexity of communicable disease care in SSA from biomedical, social, and environmental perspectives, and suggest a way forward. Conclusion A socio-environmental approach to acute febrile illness etiology, diagnostics, and management would lead to substantial health gains in Africa, including more efficient malaria control. Such an approach would also improve global preparedness for future epidemics of emerging pathogens such as chikungunya, Ebola, and Zika, all of which originated in SSA with limited baseline understanding of their epidemiology despite clinical recognition of these viruses for many decades. Impending ACT resistance, new vaccine delays, and climate change all beckon our attention to proper diagnosis of fevers in order to maximize limited health care resources

Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe