Litcius/Paper detail

Baidu Index and COVID-19 Epidemic Forecast: Evidence From China

Jianchun Fang, Xinyi Zhang, Yang Tong, Yuxin Xia, Hui Liu, Keke Wu

2021Frontiers in Public Health44 citationsDOIOpen Access PDF

Abstract

With the global spread of the Coronavirus epidemic, search engine data can be a practical tool for decision-makers to understand the epidemic's trends. This article uses trend analysis data from the Baidu search engine, the most widely used in China, to analyze the public's attention to the epidemic and the demand for N95 masks and other anti-epidemic materials and information. This kind of analysis has become an important part of information epidemiology. We have analyzed the use of the keywords "Coronavirus epidemic," "N95 mask," and "Wuhan epidemic" to judge whether the introduction of real-time search data has improved the efficiency of the Coronavirus epidemic prediction model. In general, the introduction of the Baidu index, whether in-sample or out-of-sample, significantly improves the prediction efficiency of the model.

Topics & Concepts

Coronavirus disease 2019 (COVID-19)Index (typography)Sample (material)ChinaCoronavirusSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Computer scienceEpidemic model2019-20 coronavirus outbreakEnvironmental healthGeographyVirologyMedicineOutbreakPopulationWorld Wide WebInfectious disease (medical specialty)ChromatographyChemistryArchaeologyDiseasePathologyCOVID-19 epidemiological studiesCOVID-19 Pandemic ImpactsData-Driven Disease Surveillance