Optimisation of wastewater surveillance for COVID-19 after resumption of normalcy from the pandemic: A case of Hong Kong

Wastewater surveillance (WWS) was critical to Hong Kong's COVID-19 response, providing early warning indicators and enabling targeted measures to control the epidemic in the city during the pandemic. As the approach to COVID-19 transitioned from containment to long-term management, maintaining the WWS programme became challenging owing to financial limitations. This article chronicles our efforts to optimize the programme to guarantee its long-term sustainability while preserving its efficacy in tracking disease trends and detecting novel variants. Prior to optimization, our WWS programme gathered samples from 120 locations weekly, encompassing 80 % of the population. Drawing from our experience, we examined several optimization measures, such as decreasing frequency of sampling and altering testing procedures. Nonetheless, these methods were deemed impractical owing to operational and technical difficulties. Ultimately, we determined that a reduction in sampling sites was the most viable method. Statistical analyses utilizing data from April 2023 to March 2024 corroborated this methodology, indicating that despite an 85 % decrease in sample locations (from 120 to 18), the surveillance data retained a high degree of reliability (R² > 0.97) compared to the original model. This optimized methodology decreased expenses by about 80 % while maintaining data reliability. By disseminating our methodology and findings, we aim to provide useful information that may aid other jurisdictions in establishing cost-effective WWS systems as they confront analogous difficulties globally.

Authors

Institutions

Publication Details

Journal
Epidemics
Published
2025-09-09
DOI
https://doi.org/10.1016/j.epidem.2025.100853
Citations
1
Primary Topic
SARS-CoV-2 detection and testing
Type
article
Field-Weighted Citation Impact
1.40
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Optimisation of wastewater surveillance for COVID-19 after resumption of normalcy from the pandemic: A case of Hong Kong

Kam Ngai Kung, Shuk Kwan Chuang, Lucía Wong, Shirley Tsang et al.
1 citations
Epidemics
SARS-CoV-2 detection and testing
1.40
article

Optimisation of wastewater surveillance for COVID-19 after resumption of normalcy from the pandemic: A case of Hong Kong

Kam Ngai Kung, Shuk Kwan Chuang, Lucía Wong, Shirley Tsang, S K So, KS Chan, Kirran Nazesh Mohammad, Eugene Siu Kai Lo, Albert Ka-Wing Au, K. M. Law, LO Dawin
article en
1 citations

Abstract

Wastewater surveillance (WWS) was critical to Hong Kong's COVID-19 response, providing early warning indicators and enabling targeted measures to control the epidemic in the city during the pandemic. As the approach to COVID-19 transitioned from containment to long-term management, maintaining the WWS programme became challenging owing to financial limitations. This article chronicles our efforts to optimize the programme to guarantee its long-term sustainability while preserving its efficacy in tracking disease trends and detecting novel variants. Prior to optimization, our WWS programme gathered samples from 120 locations weekly, encompassing 80 % of the population. Drawing from our experience, we examined several optimization measures, such as decreasing frequency of sampling and altering testing procedures. Nonetheless, these methods were deemed impractical owing to operational and technical difficulties. Ultimately, we determined that a reduction in sampling sites was the most viable method. Statistical analyses utilizing data from April 2023 to March 2024 corroborated this methodology, indicating that despite an 85 % decrease in sample locations (from 120 to 18), the surveillance data retained a high degree of reliability (R² > 0.97) compared to the original model. This optimized methodology decreased expenses by about 80 % while maintaining data reliability. By disseminating our methodology and findings, we aim to provide useful information that may aid other jurisdictions in establishing cost-effective WWS systems as they confront analogous difficulties globally.

EpidemicsVol. 53
Department of Health (CN)
Openalex Percentile: Top 16%
SARS-CoV-2 detection and testing
1.40
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.