lancet-header

Preprints with The Lancet is a collaboration between The Lancet Group of journals and SSRN to facilitate the open sharing of preprints for early engagement, community comment, and collaboration. Preprints available here are not Lancet publications or necessarily under review with a Lancet journal. These preprints are early-stage research papers that have not been peer-reviewed. The usual SSRN checks and a Lancet-specific check for appropriateness and transparency have been applied. The findings should not be used for clinical or public health decision-making or presented without highlighting these facts. For more information, please see the FAQs.

Wastewater Surveillance Provides Spatiotemporal Dynamics of SARS-CoV-2 Infections in a Megacity: Hong Kong's Case Study

17 Pages Posted: 24 Feb 2023

See all articles by Xia-wan Zheng

Xia-wan Zheng

The University of Hong Kong - Environmental Microbiome Engineering and Biotechnology Lab

Kathy Leung

The University of Hong Kong - School of Public Health; The University of Hong Kong - WHO Collaborating Centre for Infectious Disease Epidemiology and Control

Xiaoqing Xu

The University of Hong Kong - Environmental Microbiome Engineering and Biotechnology Lab

Yu Deng

The University of Hong Kong - Environmental Microbiome Engineering and Biotechnology Lab

Yulin Zhang

The University of Hong Kong - Environmental Microbiome Engineering and Biotechnology Lab

Xi Chen

The University of Hong Kong - Environmental Microbiome Engineering and Biotechnology Lab

Chung In Yau

The University of Hong Kong - School of Public Health

Kenny WK Hui

Government of the Hong Kong Special Administrative Region - Drainage Services Department

Kan-ming Pak

Government of the Hong Kong Special Administrative Region - Drainage Services Department

Ho-kwong Chui

Government of the Hong Kong Special Administrative Region - Environmental Protection Department

Ron Rong Yang

Government of the Hong Kong Special Administrative Region - Environmental Protection Department

Hein Min Tun

The Chinese University of Hong Kong - Department of Medicine & Therapeutics

Gabriel Leung

The University of Hong Kong - School of Public Health

Joseph T. Wu

The University of Hong Kong - WHO Collaborating Centre for Infectious Disease Epidemiology and Control

J.S. Malik Peiris

The University of Hong Kong - School of Public Health

Leo LM Poon

The University of Hong Kong - School of Public Health

Tong Zhang

The University of Hong Kong - Environmental Microbiome Engineering and Biotechnology Lab

More...

Abstract

Background: During the COVID-19 pandemic, obtaining timely and accurate pandemic trends is essential for carrying out effective control policies and targeted resource allocation. Wastewater surveillance can take advantage of its wide coverage, convenient sampling, and high monitoring frequency to capture a city-wide pandemic trend independently from clinical surveillance.

Methods: We conducted a 9-month SARS-CoV-2 wastewater surveillance from 12 wastewater treatment plants (WWTPs) to monitor infection dynamics from February 14, 2022, to November 1, 2022. Totally, 2887 wastewater samples were concentrated by polyethylene glycol (PEG) precipitation and quantified by RT-qPCR to determine SARS-CoV-2 virus concentration. In addition, daily number of reported cases from Centre for Health Protection (CHP) database, daily point-prevalence from online dashboard from independent community rapid antigen test (RAT) surveillance and city-wide sero-surveillance dataset were collected to compare with the prevalence/incidence rates estimated from wastewater measurements.

Findings: The wastewater virus concentration correlated with daily number of reported cases and reached the peak three days earlier for both the first and second peaks. Two different methods, based on virus shedding load and reported cases in low infection rate period, were established to estimate the prevalence/incidence rates from wastewater measurements, and the results were comparable to the community RAT surveillance and sero-surveillance but higher than the cases reported by CHP. In addition, the effective reproductive number (Rt) was estimated from wastewater surveillance to reflect the transmission dynamics at both the city-wide and regional levels.

Interpretation: Our findings demonstrate large-scale intensive wastewater surveillance from WWTPs provides cost-effective and timely public health information, especially when the clinical surveillance is inadequate and costly during the pandemic outbreak. This approach also helps reveal the spatiotemporal pandemic dynamic at higher spatiotemporal resolutions for targeted interventions.

Funding: Health and Medical Research Fund (HMRF) (COVID1903015), The Government of the Hong Kong Special Administrative Region (SAR), China.

Declaration of Interest: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Keywords: wastewater surveillance, SARS-CoV-2, prevalence rates, effective reproductive number

Suggested Citation

Zheng, Xia-wan and Leung, Kathy Sze Man and Xu, Xiaoqing and Deng, Yu and Zhang, Yulin and Chen, Xi and Yau, Chung In and Hui, Kenny WK and Pak, Kan-ming and Chui, Ho-kwong and Yang, Ron Rong and Tun, Hein Min and Leung, Gabriel and Wu, Joseph T. and Peiris, J.S. Malik and Poon, Leo LM and Zhang, Tong, Wastewater Surveillance Provides Spatiotemporal Dynamics of SARS-CoV-2 Infections in a Megacity: Hong Kong's Case Study. Available at SSRN: https://ssrn.com/abstract=4364895 or http://dx.doi.org/10.2139/ssrn.4364895

Xia-wan Zheng

The University of Hong Kong - Environmental Microbiome Engineering and Biotechnology Lab ( email )

Kathy Sze Man Leung

The University of Hong Kong - School of Public Health ( email )

The University of Hong Kong - WHO Collaborating Centre for Infectious Disease Epidemiology and Control ( email )

Xiaoqing Xu

The University of Hong Kong - Environmental Microbiome Engineering and Biotechnology Lab ( email )

Yu Deng

The University of Hong Kong - Environmental Microbiome Engineering and Biotechnology Lab ( email )

Yulin Zhang

The University of Hong Kong - Environmental Microbiome Engineering and Biotechnology Lab ( email )

Xi Chen

The University of Hong Kong - Environmental Microbiome Engineering and Biotechnology Lab ( email )

Chung In Yau

The University of Hong Kong - School of Public Health ( email )

Kenny WK Hui

Government of the Hong Kong Special Administrative Region - Drainage Services Department ( email )

Kan-ming Pak

Government of the Hong Kong Special Administrative Region - Drainage Services Department ( email )

Ho-kwong Chui

Government of the Hong Kong Special Administrative Region - Environmental Protection Department ( email )

Ron Rong Yang

Government of the Hong Kong Special Administrative Region - Environmental Protection Department ( email )

Hein Min Tun

The Chinese University of Hong Kong - Department of Medicine & Therapeutics ( email )

Gabriel Leung

The University of Hong Kong - School of Public Health ( email )

Joseph T. Wu

The University of Hong Kong - WHO Collaborating Centre for Infectious Disease Epidemiology and Control ( email )

J.S. Malik Peiris

The University of Hong Kong - School of Public Health ( email )

Hong Kong, Pokfulam
China

Leo LM Poon

The University of Hong Kong - School of Public Health ( email )

Hong Kong, Pokfulam
China

Tong Zhang (Contact Author)

The University of Hong Kong - Environmental Microbiome Engineering and Biotechnology Lab ( email )

Click here to go to TheLancet.com

Paper statistics

Downloads
138
Abstract Views
768
PlumX Metrics