A Simple, SIR-like but Individual-Based l-i AIR Model: Application in Comparison of COVID-19 in New York City and Wuhan

Abstract COVID-19 has spread around the world with nearly 360,000 deaths from the virus as of today (5/28/2020). Mathematical models have played an important role in many key policy discussions about COVID-19. SIR or SIR-derived models are a common modeling technique. However, the application of these models needs to solve complicated differential equations, enabling use of these models only by professional researchers. In this study, a simple, SIR-like but individual-based model, the l-i AIR model, is presented. The parameters l and i represent the length of the latent period and the infectious period, respectively. The variable A stands for the number of the infected people in the active infectious period, I for the number of cumulative infected people, and R for the number of the people in recovery or death. The nth terms of the three variables are derived, which can be easily calculated in Microsoft Excel, making the program easy to be used in most offices. A transmission coefficient k and a transient incidence rate a of the infected people are induced in the model to examine the effect of social distancing and the testing capacity of coronavirus on the epidemic curves. The simulated daily new cases from this l-i AIR model can fit very well with the reported daily new cases of COVID-19 in Wuhan, China and in New York City, USA, providing important information about latent period, infectious period and lockdown efficiency, and calculating the number of actual infected people who are positive in antibodies..

Medienart:	Preprint

Erscheinungsjahr:	2020
Erschienen:	2020

Enthalten in:	bioRxiv.org - (2020) vom: 29. Dez. Zur Gesamtaufnahme - year:2020

Sprache:	Englisch

Beteiligte Personen:	Liu, Xiaoping [VerfasserIn]

Links:	Volltext [kostenfrei]

doi:	10.1101/2020.05.28.20115121

funding:
Förderinstitution / Projekttitel:

PPN (Katalog-ID):	XBI01806955X