Exploring the impact of under-reported cases on the COVID-19 spatiotemporal distributions using healthcare workers infection data.

ABSTRACT: A timely understanding of the spatiotemporal pattern and development trend of COVID-19 is critical for timely prevention and control. However, the under-reporting of casesis widespread in fields associated with public health. It is also possible to draw biased inferences and formulate inappropriate prevention and control policies if the phenomenon of under-reporting is not taken into account. Therefore, in this paper, a novel framework was proposed to explore the impact of under-reporting on COVID-19 spatiotemporal distributions, and empirical analysis was carried out using infection data of healthcare workers in Wuhan and Hubei (excluding Wuhan). The results show that (1) the lognormal distribution was the most suitable to describe the evolution of epidemic with time; (2) the estimated pe

SUBMITTER: Wang P 

PROVIDER: S-EPMC8761553 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature