Data

High-quality data is crucial for building and validating epidemiological models, serving as the foundation for accurate and meaningful insights. Ensuring data quality involves addressing aspects such as accuracy, completeness, consistency, and timeliness, which are essential for reliable model outcomes. Adhering to the FAIR principles, making data Findable, Accessible, Interoperable, and Reusable, enhances data management and sharing, enabling seamless integration from diverse sources and facilitating collaborative research efforts. This encompasses diverse data types, including surveillance data, genetic information, environmental factors, and host demographics. Challenges include data availability, accuracy, integration from multiple sources, and maintaining FAIR compliance.