Orginal Research
2023 December
Volume : 11 Issue : 4


An interesting parameter deduced from confirmed infection number in COVID-19 epidemic

Chow CL, Cheng CH, Chow WK

Pdf Page Numbers :- 267-269

Chow CL1, Cheng CH1 and Chow WK2*

 

1Department of Architecture and Civil Engineering, City University of Hong Kong, Hong Kong, China

2Department of Building Environment and Energy Engineering, The Hong Kong Polytechnic University, Hong Kong, China

 

*Corresponding author: Prof. Chow WK, Department of Building Environment and Energy Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China. Email: wan-ki.chow@polyu.edu.hk

 

Received 2 August 2023; Revised 11 September 2023; Accepted 20 September 2023; Published 29 September 2023

 

Citation: Chow CL, Cheng CH, Chow WK. An interesting parameter deduced from confirmed infection number in COVID-19 epidemic. J Med Sci Res. 2023; 11(4):267-269. DOI: http://dx.doi.org/10.17727/JMSR.2023/11-49

 

Copyright: © 2023 Chow CL et al. Published by KIMS Foundation and Research Center. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

View Full Text | PDF

Abstract

In controlling outbreaks of COVID-19, the number of daily confirmed infected cases is useful in deducing parameters to determine emergency management actions such as locking down the cities. However, complicated mathematical models with ordinary differential equations are involved. Resources including manpower and data accessibility are needed. The parameters deduced are always challenged by stakeholders, particularly those from servicing and tourist industry. A simple parameter is proposed to describe the extent of infection by estimating the transient daily infection number divided by the time. The daily infection number in Hong Kong is used to illustrate the approach. This will not require large-scale long-term observation and mathematical modeling or computation.

 

Keywords: COVID-19; infection number; parameter

Subscription