COVID-19 pandemic research

Suspected close contacts as the pilot indicator of the growth trend of confirmed population during the COVID-19 pandemic: A simulation approach

Sisi Huang, Anding Zhu, Yan Wang, Yancong Xu, Lu Li, Dexing Kong

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7268865/

Abstract

Background:
Regarding to the actual situation of the new coronavirus disease 2019 epidemic, social factors should be taken into account and the increasing growth trend of confirmed populations needs to be explained. A proper model needs to be established, not only to simulate the epidemic, but also to evaluate the future epidemic situation and find a pilot indicator for the outbreak.

Methods:
The original susceptible-infectious-recover model is modified into the susceptible-infectious-quarantine-confirm-recover combined with social factors (SIDCRL) model, which combines the natural transmission with social factors such as external interventions and isolation. The numerical simulation method is used to imitate the change curve of the cumulative number of the confirmed cases and the number of cured patients. Furthermore, we investigate the relationship between the suspected close contacts (SCC) and the final outcome of the growth trend of confirmed cases with a simulation approach.

Results:
This article selects four representative countries, that is, China, South Korea, Italy, and the United States, and gives separate numerical simulations. The simulation results of the model fit the actual situation of the epidemic development and reasonable predictions are made. In addition, it is analyzed that the increasing number of SCC contributes to the epidemic outbreak and the prediction of the United States based on the population of the SCC highlights the importance of external intervention and active prevention measures.

Conclusions:
The simulation of the model verifies its reliability and stresses that observable variable SCC can be taken as a pilot indicator of the coronavirus disease 2019 pandemic.

**Keywords: ** COVID-19, SIR model, social factors, numerical simulation, suspected close contacts, confirmed case, temporary hospital

The numerical simulation of SIDCRL model shows it gives an excellent fit of the realistic data. Then it is derived from the simulation result that the increasing number of SCC contributes to the epidemic outbreak, which highlights the importance of external intervention and the active prevention measures in all countries. The paper is well-written and the new model and the corresponding simulation results are interesting both theoretically and practically and present a new direction to investigate the COVID-19 epidemic for the related scientists.