Communicable Diseases: A Global Perspective (Modular Texts)

For example, NLP has been used to automatically classify electronic medical records EMR from emergency rooms into categories for syndromic biosurveillance [ 12 , 13 ], especially in cases where specific clinical definitions are scant e. In the realm of digital biosurveillance, efforts are underway to apply NLP to social media streams [ 15 ].

Using NLP to systematically create structured data from unstructured text may enable the monitoring of innumerable local sources of infectious disease information globally.

Digital biosurveillance methods that use NLP may lead to the accurate and rapid detection of infectious disease outbreaks in places where traditional biosurveillance systems are insufficient. GRITS uses natural language processing to determine which infectious diseases are most likely associated with an input text sample. Articles are processed using a combination of NLP methods to identify disease-related features from the text.

GRITS presently searches an index of over , infectious diseases related articles. Elasticsearch assigns relevance scores to individual terms using TF-IDF term frequency-inverse document frequency based models, which weight matches according to how common words are in a document divided by how rare they are across the corpus of documents. The algorithms are detailed in Supporting Information, and code samples are provided Supplemental 1 in Supplementary Material available online at http: Prior to analysis, non-English text is translated using Bing Translator.

Locations are matched with a custom algorithm that uses data from the GeoNames database in addition to a number of heuristics to reduce false positive matches. GRITS stores extracted features in JSON with information about their position in the text, so they can be viewed separately from the document or in their original context. OneVsRestClassifier to predict the disease referred to by a body of text. This uses an ensemble of logistic regression classifiers, one for each disease label approximately Multiple occurrences of features were not counted.

Classifier training and testing used a randomly selected corpus of approximately , articles from a 2 to 3-year period of the , article set and collected and assigned a single disease label each by analysts. Classifiers were trained on a subset of approximately 12, articles.

A confusion matrix was composed, from which the microaveraged F1 score was calculated across all classifiers. The microaveraged F1 score sums all true positives, false negatives, and false positives, evaluating classifier performance across all diseases in the GRITS ontology. To determine the relative contribution of features for a given diagnosis on a text, the regression coefficients for each classifier are rescaled to sum to 1 and then multiplied by the estimated probability of that disease for that text.

The overall F1 score is 0. These results included translations and were not skewed due to translation. GRITS provides a framework for classifying the infectious disease-related content in potentially arbitrary text. Monitoring digital disease signals for impending infectious disease threats means that biosurveillance capacity can be extended to areas where the healthcare and public health infrastructure is inadequate.

This is crucial since many emerging infectious disease threats occur in places where traditional biosurveillance infrastructure is scant.

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In the hands of the astute public health analyst, GRITS is a powerful tool for infectious disease biosurveillance that allows users to efficiently monitor nontraditional data sources for infectious disease threats. It can extend the capabilities of analysts to triage and monitor a wider range of textual sources, increasing coverage of nontraditional digital disease surveillance in areas where traditional systems do not exist and supplementing traditional methods where they do.

Both games engage users in investigating an infectious disease outbreak using science process skills and learning about the roles of epidemiologists, microbiologists, and veterinarians in an outbreak response.

Game play is largely story line based and punctuated with more game-like activities, some of which are more closely tied to learning than others. A strength of MedMyst is that it portrays career possibilities in an inclusive and accessible way. The MedMyst educator site includes worksheets, classroom activities, and assessment items, and ties the games and materials to science standards.

For delving into the biology of the pathogens themselves, a good starting point is the Microbe World website www. The home page includes microbiology news and research updates, many of which focus on microbes that are not pathogens. Although some pathogenic microbes cause devastating diseases, it is important for students to learn that there are many more benign or beneficial microbes. Content on the website is largely text based with accompanying images or illustrations.

To find information on a specific topic, use the keyword search in the top right corner; the search can be filtered by content type. Of particular relevance to infectious disease biology is a behind-the-scenes video Much of the information on the site is most appropriate for undergraduate students. At the bottom of the page, middle and high school students can find basic information about microbes and microbiology that would be appropriate for them. Vaccination is a powerful means of combating infectious disease. There is significant interest in vaccines but also considerable misinformation about them.

People are often curious about what vaccines are, how they work, and why we do not have a vaccine for every disease. To provide engaging and accessible information about vaccine science and public health, the College of Physicians of Philadelphia has created an interactive website called The History of Vaccines www. This website is easy to navigate, with tabs for timelines of vaccine history, activities, articles, and an image gallery. The Activities section contains interactives on how vaccines work, types of vaccines, and how vaccines are made.

It also includes the Illsville game Figure 4 , which combines the history of medicine with concepts about epidemiology, quarantine, vaccination, and herd immunity. Players respond to disease outbreaks in a population by employing quarantine, doctors, and educators. The game ends with a vaccinated population that has achieved herd immunity. The Articles section of the website contains more details, including information on the challenges of vaccine design, why some diseases are difficult to target with vaccines, viral evolution, and optimistic news about vaccines against Ebola and HIV.

The Educators link on the top right of the navigation bar links to the online activities and associated lesson plans. The website is available in English and Spanish. Images of pathogens and public health efforts will be useful for anyone doing outreach presentations. Clicking on an image provides a description and additional information. Many images can be found in their public Flickr account at www. For middle and high school teachers, several epidemiology modules with detailed lesson plans are available online.

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The National Institutes of Health Curriculum Supplement Series on Emerging and Re-emerging Infectious Diseases tackles infectious diseases, epidemiology, public health, and policy at http: Published in , these lessons include several online videos and contain five detailed activities targeted for the high school level.

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