Discuss the potential biases that may exist in different public health datasets. Feel free to focus on specific datasets or types of data that you are familiar with, but you can also consider the following types of data:

• Infectious disease data from public schools
• Fall data from nursing homes
• Opioid overdose data from first responder reports
• Genetic risk profiles from rural regions in developing countries

Instructions:

1. Your discussion should include the types of explicit and implicit biases that may be in the data, as well as how both sampling and reporting biases may play a role in the data creation process
2. Finally, describe the ideal process for creating the data (as unrealistic and infeasible as it may well be), and
3. Identify steps to creating a feasible dataset on the topic that either reduces biases as much as possible or at least would allow public health experts to better understand the limitations of the data