JMIR Publications

ABSTRACT

Background:

Researchers have been increasingly using the internet as a major source of health-related information and infodemiological methods have provided new approaches for studying the impact of coronavirus disease (COVID-19).

Objective:

To verify whether frequent mask-wearing during the COVID-19 pandemic was associated with an increase in acne search popularity.

Methods:

Data for mask-wearing were obtained from a NYT survey, with 250,000 responses between July 2 and 14, 2020, and from Google COVID-19 symptoms dataset for weekly acne and anxiety search popularity. All data in the study were presented in relation to US county levels. Each county was classified in the frequent mask-wearing group if the proportion of frequent users was above the third quartile. To make search trends comparable from one week to another and from one county to another, search trends were normalized on a relative 100-point scale, with the maximum value corresponding to the highest search popularity for a particular term in a specific week and a specific county. Other sources of data included the US census bureau datasets. Acne search popularity outcome was analyzed using a logistic regression, with COVID-19 incidence, metropolitan status of the county and anxiety search popularity as covariates, and mask-wearing status as the exposure variable. 2019 data, no mask-wearing, was used as a calibration control for acne search weight.

Results:

The final dataset consisted of 2893 counties with complete cases. Frequent mask-wearing was associated with an important increase in acne search popularity (OR=1.69; 95% CI (1.30-2.21); P<.001). A high relative incidence of COVID-19 was associated with an even greater acne search popularity (OR=8.42; 95% CI (6.48-10.96); P<.001).

Conclusions:

Despite various biases, the use of infodemiology will keep increasing. Observational statistical methods need to be adapted to manage the large amounts of bias concerning web-based information more efficiently.