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• W4311598752 abstract "Abstract With the ease of coronavirus disease (COVID-19) emergency status globally, a population-wide low-cost prediction for COVID-19-induced hospitalization and intensive care unit (ICU) admission numbers is essential for healthcare systems. For the first time, we evaluated the feasibility of using wastewater-based epidemiology (WBE) to predict COVID-19-induced hospitalization and ICU admission numbers in 102 counties across 42 states in the United States of America (USA), covering a population of nearly 60 million, through random forest models using the county-level weekly wastewater surveillance data (over 15 months). WBE-based models accurately predicted the admission numbers, allowing a preparation window of 5-28 days. In real applications, periodically updated WBE-based models showed good accuracy and transferability, with mean absolute error within 20 and 2 patients/100k population for upcoming hospitalization and ICU admission numbers in 28 days, respectively. Our study demonstrated the potential of using WBE as a cost-effective method to provide early warnings for healthcare systems." @default.
• W4311598752 created "2022-12-27" @default.
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• W4311598752 date "2022-12-15" @default.
• W4311598752 modified "2023-10-14" @default.
• W4311598752 title "Wastewater-based epidemiology predicts COVID-19-induced hospital and ICU admission numbers in over 100 USA counties" @default.
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• W4311598752 doi "https://doi.org/10.21203/rs.3.rs-2368434/v1" @default.
• W4311598752 hasPublicationYear "2022" @default.
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