A Real-Time Infodemiology Study on Public Interest in Mpox (Monkeypox) following the World Health Organization Global Public Health Emergency Declaration

• Published in: Information (Basel) 2023-01, Vol.14 (1), p.5
• Main Authors: Bhagavathula, Akshaya Srikanth, Raubenheimer, Jacques E.
• Format: Article
• Language: English
• Subjects: Coronaviruses; COVID-19; Data search; Disease transmission; Emergency management; Epidemics; Forecasting; Google health trends API; Google trends; Infectious diseases; infodemiology; Machine learning; monkeypox; Mpox; Probability; Public health; Real time; Search engines; Software; Surveillance; Trends
• ISSN: 2078-2489; 2078-2489
• DOI: 10.3390/info14010005

Google Trends (GT) is a useful real-time surveillance tool for epidemic outbreaks such as monkeypox (Mpox). GT provides hour-by-hour (real-time) data for the last seven days of Google searches. Non-real-time data are a random sample that encompasses search trends from 2004 and up to 72 h. Google Health Trends (GHT) API extracts daily raw search probabilities relative to the time period and size of the underlying population. However, little is known about the utility of GT real-time surveillance and GHT API following the public health announcements. Thus, this study aimed to analyzed Mpox GT real-time, non-real-time, and GHT API data 72 h before and after the WHO declared Mpox a public health emergency of international concern (PHEIC) in the top five Mpox-affected countries. Joinpoint regression was used to measure hourly percentage changes (HPC) in search volume. The WHO PHEIC statement on Mpox generated 18,225.6 per 10 million Google searches in the U.S. and Germany (946.8), and in 0–4 h, the HPC increased by an average of 103% (95% CI: 37.4–200.0). This study showed the benefits of real-time surveillance and the GHT API for monitoring online demand for information on emerging infectious diseases such as Mpox.