A simple, SIR-like but individual-based epidemic model: Application in comparison of COVID-19 in New York City and Wuhan | Zendy

Xiaoping Liu | Zendy

Open Access

A simple, SIR-like but individual-based epidemic model: Application in comparison of COVID-19 in New York City and Wuhan

Author(s) -

Xiaoping Liu

Publication year - 2020

Publication title -

results in physics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.743

H-Index - 56

ISSN - 2211-3797

DOI - 10.1016/j.rinp.2020.103712

Subject(s) - covid-19 , epidemic model , transmission (telecommunications) , statistics , china , demography , mathematics , geography , econometrics , virology , computer science , medicine , infectious disease (medical specialty) , outbreak , telecommunications , population , sociology , disease , archaeology , pathology

In this study, an individual-based epidemic model, considering latent-infectious-recovery periods, is presented. The analytic solution of the model in the form of recursive formulae with a time-dependent transmission coefficient is derived and implanted in Excel. The simulated epidemic curves from the model fit very well with the daily reported cases of COVID-19 in Wuhan, China and New York City (NYC), USA. These simulations show that the transmission rate of NYC’s COVID-19 is nearly 30% greater than the transmission rate of Wuhan’s COVID-19, and that the actual number of cumulative infected people in NYC is around 9 times the reported number of cumulative COVID-19 cases in NYC. Results from this study also provide important information about latent period, infectious period and lockdown efficiency.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research