64 research outputs found

    Challenges in dengue research: A computational perspective

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    This is the final version of the article. Available from Wiley via the DOI in this record.The dengue virus is now the most widespread arbovirus affecting human populations, causing significant economic and social impact in South America and South-East Asia. Increasing urbanization and globalization, coupled with insufficient resources for control, misguided policies or lack of political will, and expansion of its mosquito vectors are some of the reasons why interventions have so far failed to curb this major public health problem. Computational approaches have elucidated on dengue's population dynamics with the aim to provide not only a better understanding of the evolution and epidemiology of the virus but also robust intervention strategies. It is clear, however, that these have been insufficient to address key aspects of dengue's biology, many of which will play a crucial role for the success of future control programmes, including vaccination. Within a multiscale perspective on this biological system, with the aim of linking evolutionary, ecological and epidemiological thinking, as well as to expand on classic modelling assumptions, we here propose, discuss and exemplify a few major computational avenues—real-time computational analysis of genetic data, phylodynamic modelling frameworks, within-host model frameworks and GPU-accelerated computing. We argue that these emerging approaches should offer valuable research opportunities over the coming years, as previously applied and demonstrated in the context of other pathogens.JL, AW and SG received funding from the European Research Council under the European Union's Seventh Framework Programme (FP7/2007-2013) / ERC grant agreement no. 268904 - DIVERSITY. MR was supported by a Royal Society University Research Fellowship. NRF by a Sir Henry Dale Fellowship jointly funded by the Wellcome Trust and the Royal Society (grant number 204311/Z/16/Z). WT has received funding from a doctoral scholarship from the Engineering and Physical Sciences Research Council (EPSRC) Doctoral Training Partnership

    Dengue in Madeira Island

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    This is a preprint of a paper whose final and definite form will be published in the volume Mathematics of Planet Earth that initiates the book series CIM Series in Mathematical Sciences (CIM-MS) published by Springer. Submitted Oct/2013; Revised 16/July/2014 and 20/Sept/2014; Accepted 28/Sept/2014.Dengue is a vector-borne disease and 40% of world population is at risk. Dengue transcends international borders and can be found in tropical and subtropical regions around the world, predominantly in urban and semi-urban areas. A model for dengue disease transmission, composed by mutually-exclusive compartments representing the human and vector dynamics, is presented in this study. The data is from Madeira, a Portuguese island, where an unprecedented outbreak was detected on October 2012. The aim of this work is to simulate the repercussions of the control measures in the fight of the disease

    The ATLAS SCT Optoelectronics and the Associated Electrical Services

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    The requirements for the optical links of the ATLAS SCT are described. From the individual detector modules to the first patch panel, the electrical services are integrated with the optical links to aid in mechanical design, construction and integration. The system architecture and critical elements of the system are described. The optical links for the ATLAS SCT have been assembled and mounted onto the carbon fibre support structures. The performance of the system as measured during QA is summarised and compared to the final performance obtained after mounting modules onto the support structures

    The molecular, functional and phylogenetic characterization of PGE2 receptors reveals their different roles in the immune response of the teleost fish gilthead seabream (Sparus aurata L.)

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    Prostaglandin E2 (PGE2) plays an important role in immune activities in teleost fish, including seabream. However, receptors involved in PGE2 signaling, as well as the pathways activated downstream, are largely unknown. In this study, one ortholog of mammalian PTGER1, PTGER3 and PTGER4, and two of PTGER2 (Ptger2a and Ptger2b) were identified and characterized in gilthead seabream. In silico analysis showed that all these receptors possessed the organization domain of G protein-coupled receptors, with the exception of Ptger2b. The corresponding in vivo studies revealed that they were expressed in all the tissues examined, the highest mRNA levels of ptger1 and ptger3 being observed in the spleen and of ptger2a and ptger4 in the blood. Bacterial infection induced higher mRNA levels of ptger2a, ptger3 and ptger4 in peritoneal exudate (the site of bacterial injection). In addition, head kidney acidophilic granulocytes and macrophages displayed different ptger1, ptger2a, ptger3 and ptger4 expression profiles. Furthermore, in macrophages the expression of the receptors was weakly affected by stimulation with bacterial DNA or with PGE2, while in acidophilic granulocytes stimulation resulted in the upregulation of ptger2a and ptger4. Taken together, these results suggest different roles for seabream PGE2 receptors in the regulation of the immune responses.Versión del editor3,26

    Climate change and the emergence of vector-borne diseases in Europe: Case study of dengue fever

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    Background: Dengue fever is the most prevalent mosquito-borne viral disease worldwide. Dengue transmission is critically dependent on climatic factors and there is much concern as to whether climate change would spread the disease to areas currently unaffected. The occurrence of autochthonous infections in Croatia and France in 2010 has raised concerns about a potential re-emergence of dengue in Europe. The objective of this study is to estimate dengue risk in Europe under climate change scenarios. Methods. We used a Generalized Additive Model (GAM) to estimate dengue fever risk as a function of climatic variables (maximum temperature, minimum temperature, precipitation, humidity) and socioeconomic factors (population density, urbanisation, GDP per capita and population size), under contemporary conditions (1985-2007) in Mexico. We then used our model estimates to project dengue incidence under baseline conditions (1961-1990) and three climate change scenarios: short-term 2011-2040, medium-term 2041-2070 and long-term 2071-2100 across Europe. The model was used to calculate average number of yearly dengue cases at a spatial resolution of 10 × 10 km grid covering all land surface of the currently 27 EU member states. To our knowledge, this is the first attempt to model dengue fever risk in Europe in terms of disease occurrence rather than mosquito presence. Results: The results were presented using Geographical Information System (GIS) and allowed identification of areas at high risk. Dengue fever hot spots were clustered around the coastal areas of the Mediterranean and Adriatic seas and the Po Valley in northern Italy. Conclusions: This risk assessment study is likely to be a valuable tool assisting effective and targeted adaptation responses to reduce the likely increased burden of dengue fever in a warmer world
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