Harnessing Participatory Surveillance Cohorts and Proxy Indicators to Dynamically Track Epidemic Trends and Undiagnosed COVID-19 Infections in Singapore: Longitudinal Observational Study

Category	Detail
Condition
Key Mechanisms	Participatory surveillance and digital technology for near real-time data collection, emphasizing their role in addressing pandemic challenges.
Target Population
Care Setting

Participatory surveillance complements traditional syndromic surveillance by providing timely insights.
Integration of diverse data streams enhances estimates of undiagnosed COVID-19 cases.
Surveys effectively captured illness episodes and health care-seeking behaviors.
Methodology involved repeated digital surveys across multiple epidemic peaks, ensuring robust data collection.
Developed a framework for real-time incidence rate estimates, applicable to future epidemics.

Utilize both health care visits and self-testing data to improve accuracy of diagnosis rates.

Implement participatory surveillance to strengthen epidemic response strategies.

Combine participatory data with wastewater testing and health care staff surveillance for comprehensive monitoring.

Recognize that undiagnosed cases can lead to underreporting and inadequate public health responses.

Highlight the role of self-testing with antigen rapid tests (ARTs) in enhancing case detection.

Conduct regular digital surveys to monitor community health trends.
Integrate various surveillance data sources for a comprehensive approach to epidemic tracking.
Encourage symptomatic individuals to seek health care promptly.

Clinical Scorecard: Utilizing Participatory Surveillance Groups and Proxy Metrics to Monitor Epidemic Patterns and Undiagnosed COVID-19 Cases in Singapore: A Longitudinal Observational Analysis