Global prediction model for COVID-19 pandemic with the characteristics of the multiple peaks and local fluctuations.

ABSTRACT:

Background

With the spread of COVID-19, the time-series prediction of COVID-19 has become a research hotspot. Unlike previous epidemics, COVID-19 has a new pattern of long-time series, large fluctuations, and multiple peaks. Traditional dynamical models are limited to curves with short-time series, single peak, smoothness, and symmetry. Secondly, most of these models have unknown parameters, which bring greater ambiguity and uncertainty. There are still major shortcomings in the integration of multiple factors, such as human interventions, environmental factors, and transmission mechanisms.

Methods

A dynamical model with only infected humans and removed humans was established. Then the process of COVID-19 spread was segmented using a local smoother. The change of infection r

SUBMITTER: Dai H 

PROVIDER: S-EPMC9100309 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature