Alyssa Goodman's interview with Megan Murray, a leading epidemiologist, revealed interesting details about forms of data collection and changing predictions based on individual or governmental actions. Murray discusses the importance of considering individual risk factors when modeling disease prevalence in a population. She emphasizes the difference between population data and the individual factors that may play a role in altering the predictions drawn from this data. I found it particularly interesting that she mentions the harms associated with characterizing certain risk factors as being modifiable; this then shifts the blame for having a disease to the individual instead of taking into account the complex interplay between genetic factors and environmental causes within and beyond individual control.
The following image depicts the data collection to modeling process. Additional information about disease modeling and epidemiology can be found here: https://ccdd.hsph.harvard.edu/introduction-to-infectious-disease-modeling/
