JMIR Publications

ABSTRACT

Background:

As human society enters an era of vast and easily accessible social media, a growing number of people exploit the internet to search and exchange medical information. Internet search data could reflect population interest in health topics, it provides a new information channel to grasp the health concern of and the prevention of non-communicable diseases (NCDs).

Objective:

We aimed to explore the association of internet search data for NCDs with published diseases incidence and mortality rates in the United States and to grasp the health concern of NCDs.

Methods:

We tracked NCDs by examining the correlation among the incidence, mortality rates and internet searches in the United States from 2004 to 2017. And we established the forecast models based on the relationship between the disease rates and internet searches.

Results:

Incidence rates of 29 diseases were statistically significant correlated with RSVs of their search terms at the national level in the United States (P<0.05). The situation was same in the correlation between RSVs and the mortality rates (P<0.05). From the perspective of the goodness of fit of the multiple regression prediction models, the results were most closer to 1. For diabetes mellitus, stroke, atrial fibrillation and flutter, Hodgkin lymphoma and testicular cancer, the R² of their linear regression models for predicting incidence was 80%, 88%, 96%, 80%, 78% respectively. Meanwhile, the R² of their linear regression models for predicting mortality was 82%, 62%, 94%, 78%, 62% respectively.

Conclusions:

An advanced understanding of search behaviors could augment traditional epidemiologic surveillance, and can be used as a reference to conduct disease prediction and prevention.