Pandem Data is a classroom-based Grades 9-12 project that will improve science education using highly engaging approaches to teaching and learning that include a focus on mathematics and computer science in an epidemiology and infectious disease context. The project aims to achieve the four major goals described below.
To introduce students to big data concepts and its relevance to their everyday lives.
Big Data, although a prevalent and invasive part of everyday life, is not a topic that is routinely addressed in high school settings. Students take computer courses which may focus on applications and use of computer technology and depending on the course, may also include programming code. Big data concepts are not directly addressed in mathematics or computer science standards and are not usually addressed by mathematics or computer science textbooks.
This educational setting, however, resides in a world immersed in a continuing flood of information called big data. From FaceBook to fitness watches to Twitter, billions of people send massive amounts of data to various servers and networks. Biomedical advances use big data in every aspect of medical research. Big data mechanisms have become an essential part of everyday life. Students need to be aware of the impact these systems have in their lives.
To increase understanding of epidemiology and infectious disease within the context of data science.
Although students study microorganisms and disease-causing pathogens in a variety of biology, health, and anatomy & physiology classes, less emphasis is placed on the details of the epidemiology surrounding the organisms or the investigations that in many cases stop deadly outbreaks.
The recent outbreaks of Ebola hemorrhagic disease, the appearance of the Zika virus and its eventual spread throughout South and Central America and into the United States, and the deadly New World screw worm infestation of the endangered key deer highlight the importance of increasing student awareness of disease-related topics.
A more complete understanding of the pathogenicity and complexity of some transmission mechanisms impacting human populations will allow students to more fully understand the need for the epidemiological approach to disease investigations. They will gain an understanding of the spread of disease, how they can avoid disease in some cases, and the control measures that are used to prevent disease spread.
To increase the understanding of data and Big Data as it relates to infectious disease.
Big data concepts and capabilities are being applied to infectious disease outbreaks to help track the outbreaks, to better understand the mutations which cause different strains of pathogens to emerge, and to make predictions that can not only make control measures more effective, but impact the possible response to the next outbreak.
Pandem Data allows students to use professional software to model the spread of infectious diseases and to evaluate the efficacy of strategies to reduce the impact of an outbreak. The software relies on big data that characterizes populations, travel mobility, and/or vaccination effects within a community. Students learn how big data works in real-world problems to predict infectious disease conditions.
To promote awareness of careers in data science.
Given the growing prevalence and importance of big data in the economy, commerce, politics, science, and medicine, experts are predicting a significant increase in the numbers of new professionals needed to supply the expertise to extract and analyze the data gathered.
Teams of bioscientists, mathematicians, statisticians and computer scientists are needed, but an education pipeline has yet to be developed to fulfill those needs. Students should be aware of the careers available in biomedicine and data science, but most often are not exposed to the potential for careers in this rapidly developing field. Will all your students become biostatisticians? Are all your students capable of becoming data scientists? Of course not. But, there is a wide range of careers within bioscience and computer science that your students could explore if they became engaged in the possibilities.
Pandem Data has a careers component that will allow your students to explore careers related to bioscience and/or data science and with the related Pandem Disease Center site, they will be able to search for information on a variety of careers.
To accomplish the above goals, Pandem-Data has the following specific objectives:
- To create a curriculum package of lessons and activities that explores and uses big data within the context of infectious disease.
- To design user-friendly guides for building infectious disease models using big data modeling software which target high school audiences.
- To create a suite of classroom modules which incorporate big datasets and realistic models of infectious disease to foster critical thinking skills for data science, mathematics, and infectious disease.
- To provide a resource for students exploring bioscience and data science careers.
- To create a teacher professional development package to help teachers introduce big data concepts and implement simulation modeling activities with students.
Overview of the Modules
Pandem Data has three modules: What is Big Data?, Infectious Disease, and Epidemic Modeling with Big Data. The modules work together to provide students with the knowledge they need to more fully understand Big Data and infectious disease processes and the importance of both in their lives. Students can then apply their new knowledge and abilities to creating models of disease outbreaks and epidemics using modeling software.
What is Big Data?
The “What is Big Data?” module explores the concept of Big Data and how it impacts our everyday lives. It stresses the importance of Big Data in different facets of our society and introduces students to aspects of Big Data such as volume, velocity, veracity, variability, variety, value and visualization. It reviews units of data so that students are more aware of the vast amounts of data that are involved in Big Data. Lessons in for this module also discuss the vulnerabilities that are inherent in the lack of privacy of the internet.
Depending on how deeply you want your students to explore Big Data, you may choose which lessons you want them to review. As long as they have a good understanding of what Big Data is-and isn’t-and they understand the processes of infectious disease, they will be more than ready to progress to using the modeling software.
The optional information contained in the Big Data module will enrich students’ understanding of data science and increase their appreciation of the significance of it in their lives, but if you have a limited amount of time for this curriculum, you may want to plan the lessons so that students have as much time as possible for investigating epidemic modeling and building disease outbreak simulations. Students will most likely cover Big Data in computer science or computer/technology courses, but they will probably not be exposed to infectious disease modeling in another class.
It is imperative that your students understand the infectious disease process in order to use the modeling software in Pandem Data. If they have studied microorganisms and have been introduced to pathogens, they are already well on their way. This section reviews the types of pathogens (more than just the microorganisms) and reviews the immune responses that allow us to fight off pathogens.
The optional/supplemental material included in this module of Pandem Data helps to support the material covered in the epidemic modeling module. When students build infectious disease simulations and have to specify compartments, they will better understand how to do this if they understand disease and epidemiological investigation processes.
Information on vaccines is included in case your students go beyond the SIR model and want to extend their modeling to include vaccinated population effects.
However you choose to have your students to experience Pandem Data, understanding the disease process will make their work with modeling easier to grasp.
Epidemic Modeling with Big Data
Although you can use the materials in Pandem Data to supplement your curriculum in whatever way you choose or need, the first two sections lead up to having the students actually use Big Data within professional software programs for modeling infectious disease. The lesson plans included in this section detail how the programs use Big Data and it is important that students realize they are actually using Big Data and a professional program when they use GLEAMviz.
The Using GLEAMviz guide details how to build an epidemic simulation step-by-step. By following the guide, students will be able to learn how to build an SIR infectious disease model, set parameters for the disease, and analyze the epidemic using the Visualization Dashboard. Infectious Disease Modeling with GLEAMviz is a companion guide which takes them through each interface of the program while providing more information on modeling by the compartmentalization process. Using both guides, students can vary rates of infection, spread, transportation restrictions, and other factors to critically think through an analysis of the effects of both characteristics of the disease and strategies used to control the outbreak.
A PowerPoint that details the compartmental approach to SIR (Susceptible-Infected-Recovered) modeling of infectious disease epidemics is included in the optional materials. Teachers can use this PPT to introduce the topic to students; its easy-to-understand, simplified description of building compartments will help the students when they build their own models.
Invite your county or district public health officer or an epidemiologist (or both) from a local university to talk to your classes about how public health is monitored in your area.
Have your students complete one of the problem-based learning modules in the Pandem Disease Center that focuses on an outbreak. In both the Outbreak! and the Ruzizi Virus Fever modules, students use methods of epidemiological investigation to critically think their way through solving an outbreak. The Outbreak! module uses an interrupted case study approach; the Ruzizi Virus Fever is a problem-based learning module.
Watch the Frontline PBS documentary “Outbreak” which details the 2014-2015 Ebola epidemic in West Africa. The video describes how it may have started, what caused it to spread through several West African countries, and how mishandling of key epidemiological practices resulted in thousands of deaths. It also details the epidemiologic investigative process used in the outbreak.
NOTE: Be sure to watch this video before showing it to your class. At times, this video is difficult to watch. It shows people who have contracted Ebola and present desperate conditions in medical camps built to deal with Ebola cases. It is an excellent video that highlights the different factors, including social, cultural, political, and economic issues, that influence the efforts of dedicated medical professionals in trying to stop the epidemic, but it may not be suitable for all classes.
Access the Frontline Outbreak! video at: http://www.pbs.org/wgbh/frontline/film/outbreak. You can also access the teacher and student Study Guide for this video from the Pandem Disease Center.
For a more personal perspective on disease investigations, have your students watch the NOVA 14:40 minute “Zika: The Untold Story”. This interesting and well-narrated video describes the discovery of the Zika virus in 1947 in Uganda by Alexander Haddock and the subsequent study of the virus by his grandson, Andrew Haddock. The video describes Zika’s recent re-emergence as a dangerous viral infection. Access the video at http://www.pbs.org/video/2365909836/