A Narrative Review of High Throughput Wastewater Sample Processing for Infectious Disease Surveillance: Challenges, Progress, and Future Opportunities
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- Brenda L. Price & Peter B. Gilbert & Mark J. van der Laan, 2018. "Estimation of the optimal surrogate based on a randomized trial," Biometrics, The International Biometric Society, vol. 74(4), pages 1271-1281, December.
- Patrick T. Acer & Lauren M. Kelly & Andrew A. Lover & Caitlyn S. Butler, 2022. "Quantifying the Relationship between SARS-CoV-2 Wastewater Concentrations and Building-Level COVID-19 Prevalence at an Isolation Residence: A Passive Sampling Approach," IJERPH, MDPI, vol. 19(18), pages 1-15, September.
- Ribeiro, Matheus Henrique Dal Molin & da Silva, Ramon Gomes & Mariani, Viviana Cocco & Coelho, Leandro dos Santos, 2020. "Short-term forecasting COVID-19 cumulative confirmed cases: Perspectives for Brazil," Chaos, Solitons & Fractals, Elsevier, vol. 135(C).
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Keywords
wastewater-based epidemiology (WBE); operational challenges; disease surveillance; pandemic preparedness; automation; artificial intelligence;All these keywords.
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