Epidemiology Software - Links. K4Health. Epidemiology Monitor - News Briefs. New York State Health Department Investigators Conclude Outbreak Of Tic Disorders Is Mass Psychogenic Illness In a new report issued at the end of January, the New Your State Department of Health and its collaborating co-investigator organizations found no environmental or infectious etiologies for the mystery illness affecting 12 cases of tic-like behaviors at LeRoy High School in upstate New York near Buffalo.
The investigators now consider the outbreak to be conversion disorder, a disease category characterized by physical symptoms without an identified cause other than psychological stress. The emergence of "nodding disease" : Aetiology. The emergence of “new” diseases is a complicated issue.
“New” diseases often just means “new to biomedical science.” Viruses like Ebola and HIV were certainly circulating in Africa in animal reservoirs for decades, and probably millenia, before they came to the attention of physicians via human infections. Hantavirus in the American southwest has likely infected many people, causing pneumonia of unknown origin, before the Four Corners outbreak led to the eventual identification of the Sin Nombre virus.
Encroachment of humans into new areas can bring them into contact with novel infectious agents acquired via their food or water, or by exposure to new disease vectors such as mosquitoes or ticks. Occasionally, emerging diseases may be truly “new”–such as recombinant influenza viruses that resulted from a mixture of viruses from different host species to form a unique variant, different from either parent virus. Testing for O. volvulus is relatively simple. Dr. Works cited. Stalking the next epidemic. It wasn't that long ago that most people believed infectious diseases originated in the will of the gods, or immoral behaviour.
For the ancients, malaria hailed from the “rage of the dog star”. For 19th-century sanitarians, cholera arose from foul gases. New model for epidemic contagion. Humans are considered the hosts for spreading epidemics.
The speed at which an epidemic spreads is now better understood thanks to a new model accounting for the provincial nature of human mobility, according to a study published in EPJ B. The research was conducted by a team lead by Vitaly Belik from the Massachusetts Institute of Technology, USA, who is also affiliated with the Max Planck Institute for Dynamics and Self-Organization, Germany. Establishing a web-based integrated surveillance system for early detection of infectious disease epidemic in rural China: a field experimental study. Www.epiwork.eu. WHO Flu activity reports. Toward an Open-Access Global Database for Mapping, Control, and Surveillance of Neglected Tropical Diseases. Abstract Background After many years of general neglect, interest has grown and efforts came under way for the mapping, control, surveillance, and eventual elimination of neglected tropical diseases (NTDs).
Disease risk estimates are a key feature to target control interventions, and serve as a benchmark for monitoring and evaluation. What is currently missing is a georeferenced global database for NTDs providing open-access to the available survey data that is constantly updated and can be utilized by researchers and disease control managers to support other relevant stakeholders. We describe the steps taken toward the development of such a database that can be employed for spatial disease risk modeling and control of NTDs. Methodology Principal Findings Conclusions An open-access, spatially explicit NTD database offers unique opportunities for disease risk modeling, targeting control interventions, disease monitoring, and surveillance. Author Summary Figures Editor: Charles H. Introduction. Global NTD Db. Scientists call for global neglected disease database. [ABUJA] A global database for neglected tropical diseases (NTDs) "is feasible and should be expanded without delay", the developers of a first 'proof of concept' for such a tool have said.
While efforts to eliminate NTDs have improved over the years, a georeferenced, global, open-access database is essential to boost the work, they said in a paper published last month (13 December) in PLoS Neglected Tropical Diseases. "There is a paucity of empirical estimates regarding the distribution of infection risk and burden of NTDs at the national, district or subdistrict level in most parts of the developing world," they wrote. Such information is essential for planning and implementing cost-effective, sustainable control interventions in areas where there is limited knowledge of disease distribution.
The European Physical Journal B - Condensed Matter and Complex Systems, Volume 84, Number 4. Human mobility is a key factor in spatial disease dynamics and related phenomena.
In computational models host mobility is typically modeled by diffusion in space or on metapolulation networks. Alternatively, an effective force of infection across distance has been introduced to capture spatial dispersal implicitly. Both approaches do not account for important aspects of natural human mobility, diffusion does not capture the high degree of predictability in natural human mobility patters, e.g. the high percentage of return movements to individuals’ base location, the effective force of infection approach assumes immediate equilibrium with respect to dispersal.
These conditions are typically not met in natural scenarios. We investigate an epidemiological model that explicitly captures natural individual mobility patterns. New model for epidemic contagion. Ecdc.europa.eu/en/publications/Publications/111209_SUR_Influenza_surveillance_Europe _2010_2012.pdf. GeoPatterns - Flu Detector - Nowcasting flu in South England. About the Health Tracking Network. Twitter Tracks Spread of Disease in Real Time.
The Global Innovation Series is supported by BMW i, a new concept dedicated to providing mobility solutions for the urban environment.
It delivers more than purpose-built electric vehicles — it delivers smart mobility services. Visit bmw-i.com or follow @BMWi on Twitter. When the first cases of swine flu were detected in the spring of 2009, Twitter helped to inflame the panic that spread well ahead of the disease. The idea that anything useful could be mined from the flood of tweets reacting to the nascent threat was widely dismissed. "Unlike basic Internet search ... Researchers from Google and Yahoo had already found that certain search terms were good indicators of flu activity. Yet a multi-disciplinary team of researchers at the University of Iowa had hope that Twitter could not only track the reaction to H1N1, but also track the disease itself by using contextual information in tweets that isn't available in search terms.
GeoPatterns - Flu Detector - Tracking Epidemics on Twitter. EpiSPIDER AI Mashup 2.0. Epidemiologic Calculators. Community Discussions and Documents - phConnect. GIMD - Global Burden of Injuries. Last updated: Oct 3 2013 The Injury Mortality Data Collection of the GBD Injury Expert Group Summary description: Country-level injury mortality data tabulations disaggregated by year, age, sex, and external cause categories. Released on: Oct 3 2013 Caution: The datasets provided on this page are intended for research purposes. The injury death estimates presented here cannot be taken at face value. Please contact Kavi Bhalla (email@example.com) with questions. Download the mortality data collection. HS 20/20: Data Analysis. Institute for Health Metrics and Evaluation. Institute for Health Metrics and Evaluation.
GeoSentinel - Home Page. Epi Info™ What is Epi Info™?
Physicians, nurses, epidemiologists, and other public health workers lacking a background in information technology often have a need for simple tools that allow the rapid creation of data collection instruments and data analysis, visualization, and reporting using epidemiologic methods. Epi Info™, a suite of lightweight software tools, delivers core ad-hoc epidemiologic functionality without the complexity or expense of large, enterprise applications. Epi Info™ is easily used in places with limited network connectivity or limited resources for commercial software and professional IT support. Epi Info™ and Mesh4x Prototype Demonstration with US CDC. On Thursday, December 18th, 2008, we gave a joint theater-style demonstration of synchronizing Epi Info™ Data using Mesh4x with the Division of Integrated Surveillance Systems and Services (NCPHI/DISSS) at US CDC.
[The Epi Info™ team: David Nitschke (lead) (left), Roger Mir (middle) and Mark Berndt (right). According to our imaginary scenario (where we extended the sample Oswego outbreak from 1940), David is the NY State epidemiologist, Roger is the Oneida county Medical Officer, and Mark is the CDC epidemiologist] Here is a presentation and script scenario which walks you through the scenario step-by-step. You can download the latest Mesh4x tool from here, which also includes the sample data. Welcome to EuroTravNet. Supercourse - Epi. Supercourse is a repository of lectures and research methods materials on global health and other areas of science designed to improve the teaching of prevention and increase number of scientific publications. Supercourse has a network of about 2 million scientists in 174 countries who are sharing for free a library of about 165,000 lectures in 33 languages. The Supercourse has been produced at the WHO Collaborating Center University of Pittsburgh, with core developers Ronald LaPorte, Ph.D., Faina Linkov, Ph.D. and Eugene Shubnikov M.D.
Please contact us at firstname.lastname@example.org .