Using Data Science and Epidemiology to Track Public Health Concerns

Anna Rousos

Data science within epidemiology uses statistics, data, machine learning, and coding to track diseases and study public health in different populations. An example of current research using data science and epidemiology explains how algorithms that predict and model Covid-19 cases in multiple countries were created by researchers. The researchers used past algorithms, as models for the algorithms they created. An additional example of current research using data science and epidemiology studies the noncompliance with Covid-19 restrictions among young adults in Switzerland. The researchers found that a lack of trust in the government was one cause of noncompliance. One last example of current research using data science and epidemiology studied how sleep affects social contact. The researchers found that sleepiness was a likely factor in non-voluntary social contact. The findings presented in my research can impact our lives because it provides ways that data science is being used alongside public health to predict and model the development of current and future health concerns. I will continue with the Ingenuity Innovation Practicum and Dr. Jeffrey Gray, from the Department of Chemical and Biomolecular Engineering at Johns Hopkins University, will be my mentor.