What are the Challenges in Using Data Science for Epidemiology?
Despite its potential, using data science in epidemiology comes with challenges:
Data Quality: Ensuring the accuracy, completeness, and reliability of data can be difficult. Data Integration: Combining data from diverse sources while maintaining consistency and privacy. Ethical Issues: Protecting patient privacy and ensuring ethical use of data. Computational Limitations: Managing and processing large datasets requires significant computational resources. Interdisciplinary Collaboration: Effective collaboration between data scientists, epidemiologists, and public health officials is essential but can be challenging.
