scholarly journals Data Visualization for Epidemiological and Demographic Data for Malaria Surveillance in the Brazilian Amazon, 2007-2019

2021 ◽  
Author(s):  
Carlos Eduardo Beluzo ◽  
Natália Martins Arruda ◽  
Vinícius de Souza Maia ◽  
Luciana Correia Alves
Keyword(s):  
Data Visualization ◽  
Data Extraction ◽  
Demographic Data ◽  
Brazilian Amazon ◽  
Health Staff ◽  
Local Policy ◽  
Malaria Surveillance ◽  
Interactive Visualizations ◽  
Surveillance Programs ◽  
Visualization Techniques

Malaria represents one of the main public health problems world wide and continues to be a great challenge to Brazil which concentrates about 34.4% of the disease cases registered in the American continent. Approximately 99% of Malaria cases occur in Amazonia. In 2017, 194,000 cases were recorded. This increase in the number of cases may be a warning of a possible decline in the effectiveness of control and surveillance programs in the region. The objective of this study is to propose the design of interactive visualizations of data related to Malaria Surveillance in the Brazilian Amazon, between the years of 2007-2019. Data came from SIVEPMalaria. We used data visualization techniques to explore epidemiological and demographic aspects of Malaria Surveillance. We hope tools of this kind can reduce the burden of data extraction and analysis on health staff and local policy makers.

scholarly journals Combining Text Mining and Data Visualization Techniques to Understand Consumer Experiences of Electronic Cigarettes and Hookah in Online Forums

2015 ◽  
Vol 7 (1) ◽  
Author(s):  
Annie T. Chen ◽  
Shu-Hong Zhu ◽  
Mike Conway
Keyword(s):  
Text Mining ◽  
Data Visualization ◽  
Electronic Cigarettes ◽  
Discussion Forums ◽  
Online Forums ◽  
Textual Data ◽  
Consumer Experiences ◽  
Visualization Techniques

Our aim in this work is to apply text mining and novel visualization techniques to textual data derived from online health discussion forums in order to better understand consumers experiences and perceptions of electronic cigarettes and hookah.

scholarly journals Malaria Trigram: improving the visualization of recurrence data for malaria elimination

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Cleber Matos de Morais ◽  
Kayo Henrique de Carvalho Monteiro ◽  
Jose Diego Brito-Sousa ◽  
Wuelton Marcelo Monteiro ◽  
Vanderson Souza Sampaio ◽  
...  
Keyword(s):  
Malaria Elimination ◽  
Brazilian Amazon ◽  
Amazon Region ◽  
Primary Data ◽  
Malaria Surveillance ◽  
Historical Representation ◽  
Policy Makers ◽  
Individual Level ◽  
Public Health Professionals ◽  
Brazilian Amazon Region

Abstract Background Although considerable success in reducing the incidence of malaria has been achieved in Brazil in recent years, an increase in the proportion of cases caused by the harder-to-eliminate Plasmodium vivax parasite can be noted. Recurrences in P. vivax malaria cases are due to new mosquito-bite infections, drug resistance or especially from relapses arising from hypnozoites. As such, new innovative surveillance strategies are needed. The aim of this study was to develop an infographic visualization tool to improve individual-level malaria surveillance focused on malaria elimination in the Brazilian Amazon. Methods Action Research methodology was employed to deal with the complex malaria surveillance problem in the Amazon region. Iterative cycles were used, totalling four cycles with a formal validation of an operational version of the Malaria Trigram tool at the end of the process. Further probabilistic data linkage was carried out so that information on the same patients could be linked, allowing for follow-up analysis since the official system was not planned in such way that includes this purpose. Results An infographic user interface was developed for the Malaria Trigram that incorporates all the visual and descriptive power of the Trigram concept. It is a multidimensional and interactive historical representation of malaria cases per patient over time and provides visual input to decision-makers on recurrences of malaria. Conclusions The Malaria Trigram is aimed to help public health professionals and policy makers to recognise and analyse different types of patterns in malaria events, including recurrences and reinfections, based on the current Brazilian health surveillance system, the SIVEP-Malária system, with no additional primary data collection or change in the current process. By using the Malaria Trigram, it is possible to plan and coordinate interventions for malaria elimination that are integrated with other parallel actions in the Brazilian Amazon region, such as vector control management, effective drug and vaccine deployment strategies.

scholarly journals Prevalence of human immunodeficiency virus infection among primigravida, in Karnataka

2018 ◽  
Vol 5 (12) ◽  
pp. 5448
Author(s):  
Vani Srinivas ◽  
T. L. N. Prasad ◽  
Rajesh T. Patil ◽  
Sunil D. Khaparde
Keyword(s):  
Human Immunodeficiency Virus ◽  
General Population ◽  
Pregnant Women ◽  
Data Extraction ◽  
Demographic Data ◽  
Striking Difference ◽  
Hiv Status ◽  
Cross Sectional ◽  
Immunodeficiency Virus ◽  
The Difference

Background: Karnataka is one of the six high human immunodeficiency virus (HIV) prevalent states in India. We estimated prevalence among primigravida attending antenatal clinics in Karnataka, assuming this as a proxy for HIV incidence level in the general population.Methods: We tried estimating prevalence among primigravida using cross sectional samples. Data was collected in structured data extraction sheet for the month of September 2011, from all Integrated and Counselling tested Centres (ICTCs) of Karnataka. All the pregnant women were tested as per national protocol. We analysed the basic demographic data, geographical distribution including HIV status of spouse of primigravida.Results: In September 2011, 87580, pregnant women were tested and 238 (0.26%) were found HIV positive of which, 95 (40%) were primigravida. Prevalence among primigravida, was 0.3%. The prevalence among primigravida was highest in Bagalkot (1.6%) district. In Yadgir, Kodagu and Udupi the prevalence was zero. The high prevalent blocks were Jamakhandi, Mudhol, Gokak, Hospet and Muddebihal. 73.7% spouse of positive primigravida were tested for HIV and among those tested, 87.1% were found HIV positive.Conclusions: There is striking difference in the prevalence of HIV among primigravida in different districts of Karnataka probably indicates the difference in effectiveness of preventive interventions in these districts and within blocks. The preventive programs should be reached out to the labourer's and farmers in the general population to prevent the new infections in the general population.

Representing the Self Through the Visualization of Personal Data

2021 ◽  
Vol 12 (1) ◽  
pp. 1-12
Author(s):  
Catarina Sampaio ◽  
Luísa Ribas
Keyword(s):  
Digital Media ◽  
Data Visualization ◽  
Personal Data ◽  
Physical Reality ◽  
Digital Footprint ◽  
Identity Based ◽  
The Common ◽  
Project Data ◽  
Visualization Techniques

The representation of identity in digital media does not necessarily have to be conceived on the basis of criteria that mimic physical reality. This article presents a model for representing individual identity, based on the recording of human experience in the form of personal data, as an alternative to the common forms of mimetic portraiture. As such, the authors developed the project Data Self-Portrait that aims to explore the creative possibilities associated with the concept of data portrait. It can be described as a means of representing and expressing identity through the application of data visualization techniques to the domain of portraiture, according to an exploratory design approach, based on visualizing the digital footprint. It thus seeks to develop design proposals for representing identity that respond to the growing dematerialization of human activities and explores the representational and expressive role of data visualization, according to a creative use of computational technologies.

Visualization of Big Data Sets Using Computer Graphics

2018 ◽  
pp. 578-603
Author(s):  
Anna Ursyn ◽  
Edoardo L'Astorina
Keyword(s):  
Big Data ◽  
Data Visualization ◽  
Visual Analysis ◽  
Data Sets ◽  
Arrival Times ◽  
Learning And Teaching ◽  
Knowledge Domains ◽  
Visualization Of Data ◽  
And Mathematics ◽  
Visualization Techniques

This chapter discusses some possible ways of how professionals, researchers and users representing various knowledge domains are collecting and visualizing big data sets. First it describes communication through senses as a basis for visualization techniques, computational solutions for enhancing senses and ways of enhancing senses by technology. The next part discusses ideas behind visualization of data sets and ponders what is and what not visualization is. Further discussion relates to data visualization through art as visual solutions of science and mathematics related problems, documentation objects and events, and a testimony to thoughts, knowledge and meaning. Learning and teaching through data visualization is the concluding theme of the chapter. Edoardo L'Astorina provides visual analysis of best practices in visualization: An overlay of Google Maps that showed all the arrival times - in real time - of all the buses in your area based on your location and visual representation of all the Tweets in the world about TfL (Transport for London) tube lines to predict disruptions.

Visualizing Sixteen Years of Data About Portuguese Leisure-Cultural Activities

2012 ◽  
Vol 3 (2) ◽  
pp. 8-22
Author(s):  
Clarissa Rodrigues ◽  
Elizabeth Carvalho
Keyword(s):  
Data Visualization ◽  
Visual Cues ◽  
Leisure Time ◽  
Visual Representations ◽  
End User ◽  
Cultural Activities ◽  
Interactive Data ◽  
Visualization Techniques ◽  
Visualization Application

This paper describes an interactive data visualization application that aims to show how the Portuguese people spent culturally their leisure time between 1994 and 2009. The leisure trend is displayed to the end-user through the use of different visualization techniques and visual cues. The authors developed the visual representations based on the use of simple and regular visual shapes that could be easily combined, interpreted, memorized and used. To better evaluate their results, the authors tested their prototype against a preselected group of subjects.

scholarly journals PostProcessing and Visualization Techniques for Convection-Allowing Ensembles

2019 ◽  
Vol 100 (7) ◽  
pp. 1245-1258 ◽  
Author(s):  
Brett Roberts ◽  
Israel L. Jirak ◽  
Adam J. Clark ◽  
Steven J. Weiss ◽  
John S. Kain
Keyword(s):  
Real Time ◽  
Data Extraction ◽  
Deep Convection ◽  
Weather Prediction ◽  
Ensemble Forecast ◽  
Ensemble Prediction ◽  
Data Volume ◽  
Explicit Simulation ◽  
Prediction Systems ◽  
Visualization Techniques

AbstractSince the early 2000s, growing computing resources for numerical weather prediction (NWP) and scientific advances enabled development and testing of experimental, real-time deterministic convection-allowing models (CAMs). By the late 2000s, continued advancements spurred development of CAM ensemble forecast systems, through which a broad range of successful forecasting applications have been demonstrated. This work has prepared the National Weather Service (NWS) for practical usage of the High Resolution Ensemble Forecast (HREF) system, which was implemented operationally in November 2017. Historically, methods for postprocessing and visualizing products from regional and global ensemble prediction systems (e.g., ensemble means and spaghetti plots) have been applied to fields that provide information on mesoscale to synoptic-scale processes. However, much of the value from CAMs is derived from the explicit simulation of deep convection and associated storm-attribute fields like updraft helicity and simulated reflectivity. Thus, fully exploiting CAM ensembles for forecasting applications has required the development of fundamentally new data extraction, postprocessing, and visualization strategies. In the process, challenges imposed by the immense data volume inherent to these systems required new approaches when considering diverse factors like forecaster interpretation and computational expense. In this article, we review the current state of postprocessing and visualization for CAM ensembles, with a particular focus on forecast applications for severe convective hazards that have been evaluated within NOAA’s Hazardous Weather Testbed. The HREF web viewer implemented at the NWS Storm Prediction Center (SPC) is presented as a prototype for deploying these techniques in real time on a flexible and widely accessible platform.

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