COVID-19 Outbreak Forecasting Based on Vaccine Rates and Tweets Classification.

ABSTRACT: The spread of COVID-19 has affected more than 200 countries and has caused serious public health concerns. The infected cases are on the increase despite the effectiveness of the vaccines. An efficient and quick surveillance system for COVID-19 can help healthcare decision-makers to contain the virus spread. In this study, we developed a novel framework using machine learning (ML) models capable of detecting COVID-19 accurately at an early stage. To estimate the risks, many models use social networking sites (SNSs) in tracking the disease outbreak. Twitter is one of the SNSs that is widely used to create an efficient resource for disease real-time analysis and can provide an early warning for health officials. We introduced a pipeline framework of outbreak prediction that incorporates a fi

SUBMITTER: Didi Y 

PROVIDER: S-EPMC9633186 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature