This open access book explores ways to leverage information technology and machine learning to combat disease and promote health, especially in resource-constrained settings. It focuses on digital disease surveillance through the application of machine learning to non-traditional data sources. Developing countries are uniquely prone to large-scale emerging infectious disease outbreaks due to disruption of ecosystems, civil unrest, and poor healthcare infrastructure – and without comprehensive surveillance, delays in outbreak identification, resource deployment, and case management can be catastrophic. In combination with context-informed analytics, students will learn how non-traditional digital disease data sources – including news media, social media, Google Trends, and Google Street View – can fill critical knowledge gaps and help inform on-the-ground decision-making when formal surveillance systems are insufficient.
Fish anatomical vertical dimensions are extracted from a time-of-flight analysis of fish echo shape using narrow-bandwidth echosounding of swimming individuals. These vertical dimensions fit a Gumbel distribution model and are successfully correlated with fish weight. The proposed method can be used to estimate the mean weight of fish in aquaculture cages as an alternative to target strength measurements. Full-waveform acquisition and signal correlation techniques permitted to increase the signal-to-noise ratio and to improve the performance against traditional envelope-based echosounding. ; This work was developed with the financial support of project ARM/1790/010 of the Tecnological Develoment Program of MAGRAMA, Spanish Government. E. Soliveres acknowledges support of Spanish Government grant AP2009-4459 FPU Subprogram.
We recently reported the rapid expansion of an HIV-1 subtype F cluster among men who have sex with men (MSM) in the region of Galicia, Northwest Spain. Here we update this outbreak, analyze near full-length genomes, determine phylogenetic relationships, and estimate its origin. For this study, we used sequences of HIV-1 protease-reverse transcriptase and env V3 region, and for 17 samples, near full-length genome sequences were obtained. Phylogenetic analyses were performed via maximum likelihood. Locations and times of most recent common ancestors were estimated using Bayesian inference. Among samples analyzed by us, 100 HIV-1 F1 subsubtype infections of monophyletic origin were diagnosed in Spain, including 88 in Galicia and 12 in four other regions. Most viruses (n = 90) grouped in a subcluster (Galician subcluster), while 7 from Valladolid (Central Spain) grouped in another subcluster. At least 94 individuals were sexually-infected males and at least 71 were MSM. Seventeen near full-length genomes were uniformly of F1 subsubtype. Through similarity searches and phylogenetic analyses, we identified 18 viruses from four other Western European countries [Switzerland (n = 8), Belgium (n = 5), France (n = 3), and United Kingdom (n = 2)] and one from Brazil, from samples collected in 2005-2011, which branched within the subtype F cluster, outside of both Spanish subclusters, most of them corresponding to recently infected individuals. The most probable geographic origin and age of the Galician subcluster was Ferrol, Northwest Galicia, around 2007, while the Western European cluster probably emerged in Switzerland around 2002. In conclusion, a recently expanded HIV-1 subtype F cluster, the largest non-subtype B cluster reported in Western Europe, continues to spread among MSM in Spain; this cluster is part of a larger cluster with a wide geographic circulation in diverse Western European countries. ; This work received support from the Dirección General de Farmacia, Ministerio de Sanidad, Servicios Sociales e Igualdad, Government of Spain, grant EC11-272; European Network of Excellence EUROPRISE (Rational Design of HIV Vaccines and Microbicides), grant LSHP-CT-2006-037611; European Research Infrastructures for Poverty Related Diseases (EURIPRED). Seventh Framework Programme: FP7-Capacities-infrastructures-2012-1, grant agreement 312661; Instituto de Salud Carlos III, Subdirección General de Evaluación, and Fondo Europeo de Desarrollo Regional (FEDER), Plan Nacional I + D + I, through project RD12/0017/0026; Consellería de Sanidade, Government of Galicia, Spain (MVI 1291/08); and the Osakidetza-Servicio Vasco de Salud, Basque Country, Spain (MVI-1255-08). Marcos Pérez-Losada was supported by a DC D-CFAR Research Award from the District of Columbia Developmental Center for AIDS Research (P30AI087714) and by an University Facilitating Fund award from George Washington University. Aurora Fernández-García is supported by CIBER in Epidemiology and Public Health, Instituto de Salud Carlos III, Madrid, Spain. ; Sí
