Epidemiological research on rare diseases using large-scale online search queries and reported case data

Area of Science:

• Public Health
• Epidemiology
• Digital Health

Background:

• Rare diseases pose a significant global health challenge.
• Detailed epidemiological data for rare diseases are often scarce.
• Internet search queries are emerging as valuable tools for disease surveillance.

Purpose of the Study:

• To explore a novel method for rare disease epidemiological research.
• To utilize large-scale online search queries and national rare disease case data.
• To assess the utility of search query data for rare disease surveillance.

Main Methods:

• Collected nationwide rare disease search logs from 2016 to 2019.
• Obtained rare disease case data from China's national database (2016-2019).
• Analyzed and compared disease rankings derived from search data and case data.

Main Results:

• Included 120 rare diseases in the study.
• Both search data and case data indicated an increasing trend in rare diseases from 2016-2019.
• Disease rankings between search and reported case data were generally stable and consistent, with over 50% showing a ranking difference of -20 to 20.
• Rare diseases could be classified into two categories based on the relationship between search and case data rankings.

Conclusions:

• Online search queries represent a valuable new resource for rare disease detection and surveillance.
• Classifying rare diseases into two categories can inform distinct epidemiological research strategies.