ORIGINAL RESEARCH published: 03 May 2021 doi: 10.3389/fpubh.2021.604455 Estimating the Instantaneous Asymptomatic Proportion With a Simple Approach: Exemplified With the Publicly Available COVID-19 Surveillance Data in Hong Kong Chunyu Li 1†, Shi Zhao 2,3*†, Biao Tang 4,5, Yuchen Zhu 1, Jinjun Ran 6, Xiujun Li 1*‡ and Daihai He 7*‡ 1 2 Edited by: Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China, JC 3 Catherine Ropert, School of Public Health and Primary Care, Chinese University of Hong Kong, Hong Kong, China, Chinese University of 4 Federal University of Minas Hong Kong (CUHK) Shenzhen Research Institute, Shenzhen, China, School of Mathematics and Statistics, Xi’an Jiaotong 5 Gerais, Brazil University, Xi’an, China, Laboratory for Industrial and Applied Mathematics, Department of Mathematics and Statistics, York University, Toronto, ON, Canada, 6 School of Public Health, Li Ka Shing Faculty of Medicine, University of Hong Kong, Reviewed by: Hong Kong, China, 7 Department of Applied Mathematics, Hong Kong Polytechnic University, Hong Kong, China Mohammad Javanbakht, Baqiyatallah University of Medical Sciences, Iran Background: The asymptomatic proportion is a critical epidemiological characteristic Changjing Zhuge, that modulates the pandemic potential of emerging respiratory virus, which may vary Beijing University of Technology, China *Correspondence: depending on the nature of the disease source, population characteristics, source–host Daihai He interaction, and environmental factors.
[email protected] Xiujun Li Methods: We developed a simple likelihood-based framework to estimate the
[email protected] instantaneous asymptomatic proportion of infectious diseases. Taking the COVID-19 Shi Zhao epidemics in Hong Kong as a case study, we applied the estimation framework
[email protected] to estimate the reported asymptomatic proportion (rAP) using the publicly available † These authors share first authorship surveillance data.