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. Three of the twelve students had illness associated with tic symptoms before they attended the high school (three new students with possible tic symptoms were reported during the investigation and are currently under review). The details of the cases provided the investigators with clues. 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. 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. The authors modelled human mobility as recurrent trips centred around a home base. The model accounted for the bi-directional travels around a central node, representing their home location and forming a star-shaped network. Previous models were based on diffusion and would imply that people travel randomly in space, not necessarily returning to their home location.
The researchers found that older diffusion-based models overestimated the speed at which epidemics spread. Establishing a web-based integrated surveillance system for early detection of infectious disease epidemic in rural China: a field experimental study. 1 Division of Global Health (IHCAR), Department of Public Health Sciences, Karolinska Institutet, Nobelsvag 9, SE-17177, Stockholm, Sweden 2 Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College of Huazhong University of Science and Technology, Hangkong Road 13#, Wuhan, 430030, Hubei, China 3 Department of Epidemiology, School of Public Health, Fudan University, No 138 Yi Xue Yuan Road, Shanghai, 200032, China.
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. Global NTD Db. List of contributors.
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.
To investigate the feasibility of a database, the authors focused on schistosomiasis — a chronic disease that affects more than 700 million people worldwide, according to the WHO. 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. There are three goals for the Health Tracking Network: identify factors related to common illnesses; promote members' health by enabling them to track their personal health, fitness, and other outcomes easily; and generate donations to charities chosen by members.
For more information about what membership involves, see the tour and FAQs. The Health Tracking Network is a special project run by Interdisciplinary Scientific Research (ISR), a scientific research and consulting firm. ISR's research focuses on infectious diseases and survey research methods, among other topics. Much of ISR's past research has been funded by the U.S. National Institutes of Health and Centers for Disease Control and Prevention.
Several partners kindly promote 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 Data format: - CSV files are comma-separated text file. . - DTA files are Stata datasets. - MS Excel Format: These files can be loaded into Excel. Frequently Asked Questions. 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. The International Society of Travel Medicine (ISTM) has initiated EuroTravNet - the European Travel Medicine Network - to create a network of clinical experts in tropical and travel medicine to support detection, verification, assessment and communication of communicable diseases that can be associated with travelling and specifically with tropical diseases. The goal of EuroTravNet is to build, maintain and strengthen a multi-disciplinary network of highly qualified experts with demonstrated competence in diseases of interest, ideally in the field of travel advice, tropical medicine, clinical diagnosis of the returned traveller, and detection, identification and management of imported infections. EuroTravNet was initially funded by the European Centre for Disease Prevention and Control (ECDC). Supercourse - Epi. Supercourse is a repository of lectures on global health and prevention designed to improve the teaching of prevention.