Data science perspectives on pandemic management

Course Overview

This course provides an overview of data science perspectives on pandemic management. It is designed for decision makers, policy makers, public bodies, NGOs, and private organizations who are interested in learning about methods, tools, and experiences on the use of data for managing current and future pandemic scenarios.

The course covers topics such as policy making and technology governance, data collection from citizens, crowdsourcing, gamification, game with a purpose (GWAP), crowd monitoring and sensing, mobility and traffic analysis, disinformation and fake news impacts, and economical and financial impacts and sustainability models. Participants will gain a deeper understanding of motivations, perceptions, choices, and actions of individuals in a pandemic setting, and will be able to start defining appropriate mitigation actions.

This course was developed by a set of European research and education institutions as part of the research project 'Pan-European Response to the Impacts of the COVID-19 and future Pandemics and Epidemics' (PERISCOPE). It is funded by the European Commission Research Funding programme Horizon 2020 under the Grant Agreement number 101016233.

At the end of the course, participants will have a better understanding of the role of policy making and technology governance for managing pandemics, methods like crowdsourcing, gamification, sensing of crowds and built environments, and contact tracing for understanding the dynamics of the pandemic, the risk of disinformation and its impact on people perception and decisions, and financial models that describe the pandemic monetary impact on individuals and organizations, as well as the financial sustainability models that can be defined.

[Applications]
The application of this course can be seen in the development of data-driven policy making for pandemics. Participants can use the methods, tools, and analyses presented in the course to design better solutions to pandemics and world-wide critical events. The course can also help participants to gain a deeper understanding of motivations, perceptions, choices, and actions of individuals in a pandemic setting, and to start defining appropriate mitigation actions. Additionally, the course can be used to understand the risk of disinformation and its impact on people perception and decisions, as well as the financial models that describe the pandemic monetary impact on individuals and organizations.

[Career Paths]
1. Data Scientist: Data Scientists are responsible for collecting, analyzing, and interpreting large amounts of data to identify trends and patterns. They use their findings to develop strategies and solutions to improve the efficiency and effectiveness of organizations. Data Scientists are also responsible for developing predictive models and algorithms to help organizations make better decisions. As the demand for data-driven decision making increases, the demand for Data Scientists is expected to grow.

2. Data Analyst: Data Analysts are responsible for collecting, organizing, and analyzing data to identify trends and patterns. They use their findings to develop strategies and solutions to improve the efficiency and effectiveness of organizations. Data Analysts are also responsible for developing predictive models and algorithms to help organizations make better decisions. As the demand for data-driven decision making increases, the demand for Data Analysts is expected to grow.

3. Data Engineer: Data Engineers are responsible for designing, building, and maintaining data systems. They are responsible for creating data pipelines, data warehouses, and other data systems to store and process data. Data Engineers are also responsible for developing algorithms and models to help organizations make better decisions. As the demand for data-driven decision making increases, the demand for Data Engineers is expected to grow.

4. Machine Learning Engineer: Machine Learning Engineers are responsible for developing and deploying machine learning models and algorithms. They are responsible for designing, building, and maintaining machine learning systems. Machine Learning Engineers are also responsible for developing algorithms and models to help organizations make better decisions. As the demand for data-driven decision making increases, the demand for Machine Learning Engineers is expected to grow.

[Education Paths]
Recommended degree paths:
1. Master of Science in Data Science: This degree program focuses on the application of data science techniques to solve real-world problems. It covers topics such as data mining, machine learning, artificial intelligence, and predictive analytics. It also provides students with the skills to develop and deploy data-driven solutions for pandemic management. Developing trends in this field include the use of natural language processing, deep learning, and big data analytics.

2. Master of Science in Public Health: This degree program focuses on the application of public health principles to pandemic management. It covers topics such as epidemiology, biostatistics, health policy, and health economics. It also provides students with the skills to develop and implement public health strategies for pandemic management. Developing trends in this field include the use of digital health technologies, data-driven decision making, and public health informatics.

3. Master of Science in Health Informatics: This degree program focuses on the application of health informatics to pandemic management. It covers topics such as health information systems, health data analytics, and health information technology. It also provides students with the skills to develop and deploy health informatics solutions for pandemic management. Developing trends in this field include the use of artificial intelligence, machine learning, and natural language processing.

4. Master of Science in Disaster Management: This degree program focuses on the application of disaster management principles to pandemic management. It covers topics such as risk assessment, emergency response, and crisis communication. It also provides students with the skills to develop and implement disaster management strategies for pandemic management. Developing trends in this field include the use of digital technologies, data-driven decision making, and public health informatics.