Forecasting of COVID-19 onset cases: a data-driven analysis in the early stage of delay.

ABSTRACT: The outbreak of COVID-19 has become a global public health event. Many researchers have proposed many epidemiological models to predict the outbreak trend of COVID-19, but all use confirmed cases to predict "onset cases." In this article, a total of 5434 cases were collected from National Health Commission and other provincial Health Commission in China, spanning from 1 December 2019 to 23 February 2020. We studied the delayed distribution of patients from onset to be confirmed. The delay is divided into two stages, which takes about 15 days or even longer. Therefore, considering the right truncation of the data, we proposed a "predict-in-advance" method, used the number of "visiting hospital cases" to predict the number of "onset cases." The results not only show that our prediction short

SUBMITTER: Wang X 

PROVIDER: S-EPMC7786867 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature