The exciting potential and daunting challenge of using GPS human-mobility data for epidemic modeling

Area of Science:

• Epidemiology
• Data Science
• Public Health

Background:

• Large-scale GPS location datasets offer valuable insights into human mobility and contact patterns.
• These datasets are crucial for data-driven epidemiology and were widely used during the COVID-19 pandemic.
• However, significant challenges exist in their application, impacting data validity and robustness.

Purpose of the Study:

• To identify and outline key challenges associated with utilizing large-scale GPS location data for epidemiological studies.
• To propose research directions for overcoming these data access, processing, and quality issues.
• To enhance the reliability and robustness of human mobility data in public health research.

Main Methods:

• Review and categorization of challenges related to accessing and processing large-scale GPS data.
• Analysis of data quality issues inherent in GPS location datasets.
• Identification of research gaps and formulation of future research directions.

Main Results:

• Two primary categories of challenges were identified: data access/processing and data quality.
• Specific issues within these categories impact the accuracy and applicability of mobility data.
• The study highlights the need for methodological advancements to address these limitations.

Conclusions:

• Addressing the identified challenges in GPS data access, processing, and quality is essential for valid data-driven epidemiology.
• Further research is needed to develop robust methods for utilizing human mobility data.
• Overcoming these hurdles will improve the utility of GPS data for public health surveillance and interventions.