Harnessing Google Health Trends Data for Epidemiologic Research

Area of Science:

• Digital epidemiology
• Public health surveillance
• Internet data analytics

Background:

• Growing interest in utilizing internet search data for public health research.
• Google Health Trends Application Programming Interface (GHT-API) provides accessible and timely search data.
• Need for a structured methodology to effectively use GHT-API for epidemiological studies.

Purpose of the Study:

• To detail a systematic 5-step method for measuring health constructs using GHT-API data.
• To refine search query sensitivity and specificity for improved data accuracy.
• To demonstrate the application of the method using a case study on child abuse searches during the COVID-19 pandemic.

Main Methods:

• Identify and refine relevant search phrases.
• Craft and test GHT-API search terms across geographic and temporal scales.
• Retrieve, average, and normalize multiple data samples for stable estimates.
• Utilize an optional normalization step to account for changes in total search volume.

Main Results:

• A repeatable 5-step methodology for leveraging GHT-API data was established.
• The method was successfully applied to analyze weekly state-level child abuse searches in the US (Jan 2018-Aug 2020).
• The study identified potential limitations associated with using internet search data for public health surveillance.

Conclusions:

• The proposed method provides a robust framework for using GHT-API data in public health research.
• Internet search data, when analyzed systematically, can offer valuable insights into population health trends.
• Further research is needed to address the limitations and enhance the application of digital data in epidemiology.