Insufficient Data Collection: Often, data collection methods are not exhaustive, leading to
incomplete datasets. This can be due to logistical challenges, budget constraints, or lack of trained personnel.
Limited Access to Data: Even when data is collected, it may not be accessible to researchers and policymakers due to
privacy concerns, proprietary restrictions, or bureaucratic hurdles.
Technological Barriers: In many low-resource settings, the lack of advanced
technology and
infrastructure can impede data collection and analysis.
Variability in Data Quality: The quality of data can vary significantly, affecting the reliability of
epidemiological studies. Poor data quality can arise from inconsistent data collection methods or errors in data entry.
Gaps in Longitudinal Data: Long-term data is essential for understanding chronic diseases and their risk factors. However, maintaining consistent data collection over extended periods is often challenging.
