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Updated: Jul 5, 2025

Large-Scale SARS-CoV-2 Testing Utilizing Saliva and Transposition Sample Pooling
Published on: June 23, 2022
Rapidly scalable and low-cost public health surveillance reporting system for COVID-19
Vivek Jason Jayaraj1, Chiu-Wan Ng2, Victor Chee-Wai Hoe2
1Sector for Biostatistics & Data Repository, National Institutes of Health, Ministry of Health, Shah Alam, Malaysia.
Objective:
Data-driven innovations are essential in strengthening disease control. We developed a low-cost, open-source system for robust epidemiological intelligence in response to the COVID-19 crisis, prioritising scalability, reproducibility and dynamic reporting.
Methods:
A five-tiered workflow of data acquisition; processing; databasing, sharing, version control; visualisation; and monitoring was used. COVID-19 data were initially collated from press releases and then transitioned to official sources.
Results:
Key COVID-19 indicators were tabulated and visualised, deployed using open-source hosting in October 2022. The system demonstrated high performance, handling extensive data volumes, with a 92.5% user conversion rate, evidencing its value and adaptability.
Conclusion:
This cost-effective, scalable solution aids health specialists and authorities in tracking disease burden, particularly in low-resource settings. Such innovations are critical in health crises like COVID-19 and adaptable to diverse health scenarios.
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