Comparative Performance of Wastewater, Clinical, and Digital Surveillance Indicators for COVID-19 Monitoring in...

Area of Science:

• Epidemiology
• Public Health
• Infectious Disease Surveillance

Background:

• Public health surveillance systems are essential for informed decision-making, particularly in monitoring infectious diseases.
• The COVID-19 pandemic highlighted the need for robust and timely surveillance mechanisms.

Purpose of the Study:

• To evaluate the effectiveness and timeliness of various surveillance systems in monitoring COVID-19 cases after the pandemic.
• To assess the utility of integrating hospital, wastewater, meteorological, and internet search engine data.

Main Methods:

• Collected COVID-19 case data from a southern Chinese city (April 2023-June 2024).
• Integrated data from four surveillance systems: hospital, wastewater, meteorological, and internet search engines.
• Employed Spearman correlation, moving window analyses, and time-series regression models to assess associations and lead effects.

Main Results:

• Nucleic acid amplification test (NAAT) positivity rate showed the strongest correlation (0.834) with reported cases.
• Wastewater surveillance demonstrated moderate correlations, with N gene positivity (0.776) and concentration (0.698).
• Time-series analysis revealed same-day associations for NAAT positivity and wastewater signals; meteorological factors influenced internet surveillance data.

Conclusions:

• An integrated, multi-channel surveillance strategy combining clinical, wastewater, and digital data is effective.
• Meteorological data contextualization can improve the interpretation of digital surveillance streams.
• This approach strengthens early warning capabilities and situational awareness for respiratory pathogen threats.