Early warning and predicting of COVID-19 using zero-inflated negative binomial regression model and negative binomial regression model.

ABSTRACT:

Background

It is difficult to detect the outbreak of emergency infectious disease based on the exiting surveillance system. Here we investigate the utility of the Baidu Search Index, an indicator of how large of a keyword is in Baidu's search volume, in the early warning and predicting the epidemic trend of COVID-19.

Methods

The daily number of cases and the Baidu Search Index of 8 keywords (weighted by population) from December 1, 2019 to March 15, 2020 were collected and analyzed with times series and Spearman correlation with different time lag. To predict the daily number of COVID-19 cases using the Baidu Search Index, Zero-inflated negative binomial regression was used in phase 1 and negative binomial regression model was used in phase 2 and phase 3 based on the charact

SUBMITTER: Zhou W 

PROVIDER: S-EPMC11414173 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature