A1037
Title: Utilizing Google trends data to enhance forecasts and monitor long COVID prevalence
Authors: Shun Hin Chan - The Hong Kong University of Science and Technology (Hong Kong) [presenting]
Mike So - The Hong Kong University of Science and Technology (Hong Kong)
Amanda Chu - The Education University of Hong Kong (China)
Jenny Tsang - Tung Wah College (Hong Kong)
Sophia Chan - The University of Hong Kong (Hong Kong)
Abstract: Long COVID is a persistent illness that follows COVID-19 infection. It has emerged as a significant public health concern since the outbreak of the pandemic. Effective disease surveillance is crucial for policy-making and resource allocation. The potential of using the number of searches of long COVID symptoms in Google to enhance surveillance and improve the predictability of long COVID prevalence is investigated. Searches found for several specific symptoms increased both before and after searches for long COVID, demonstrating that the number of searches can predict long COVID prevalence. Google search results could, therefore, be used to monitor disease prevalence.
