tetano
Editor, Senior Moderator
Nat Commun
. 2023 Jul 28;14(1):4548.
doi: 10.1038/s41467-023-40305-x. Wastewater-based epidemiology predicts COVID-19-induced weekly new hospital admissions in over 150 USA counties
Xuan Li[SUP] 1 [/SUP], Huan Liu[SUP] 1 [/SUP], Li Gao[SUP] 2 [/SUP], Samendra P Sherchan[SUP] 3 4 [/SUP], Ting Zhou[SUP] 1 [/SUP], Stuart J Khan[SUP] 5 [/SUP], Mark C M van Loosdrecht[SUP] 6 [/SUP], Qilin Wang[SUP] 7 [/SUP]
Affiliations
Although the coronavirus disease (COVID-19) emergency status is easing, the COVID-19 pandemic continues to affect healthcare systems globally. It is crucial to have a reliable and population-wide prediction tool for estimating COVID-19-induced hospital admissions. We evaluated the feasibility of using wastewater-based epidemiology (WBE) to predict COVID-19-induced weekly new hospitalizations in 159 counties across 45 states in the United States of America (USA), covering a population of nearly 100 million. Using county-level weekly wastewater surveillance data (over 20 months), WBE-based models were established through the random forest algorithm. WBE-based models accurately predicted the county-level weekly new admissions, allowing a preparation window of 1-4 weeks. In real applications, periodically updated WBE-based models showed good accuracy and transferability, with mean absolute error within 4-6 patients/100k population for upcoming weekly new hospitalization numbers. Our study demonstrated the potential of using WBE as an effective method to provide early warnings for healthcare systems.
. 2023 Jul 28;14(1):4548.
doi: 10.1038/s41467-023-40305-x. Wastewater-based epidemiology predicts COVID-19-induced weekly new hospital admissions in over 150 USA counties
Xuan Li[SUP] 1 [/SUP], Huan Liu[SUP] 1 [/SUP], Li Gao[SUP] 2 [/SUP], Samendra P Sherchan[SUP] 3 4 [/SUP], Ting Zhou[SUP] 1 [/SUP], Stuart J Khan[SUP] 5 [/SUP], Mark C M van Loosdrecht[SUP] 6 [/SUP], Qilin Wang[SUP] 7 [/SUP]
Affiliations
- PMID: 37507407
- PMCID: PMC10382499
- DOI: 10.1038/s41467-023-40305-x
Although the coronavirus disease (COVID-19) emergency status is easing, the COVID-19 pandemic continues to affect healthcare systems globally. It is crucial to have a reliable and population-wide prediction tool for estimating COVID-19-induced hospital admissions. We evaluated the feasibility of using wastewater-based epidemiology (WBE) to predict COVID-19-induced weekly new hospitalizations in 159 counties across 45 states in the United States of America (USA), covering a population of nearly 100 million. Using county-level weekly wastewater surveillance data (over 20 months), WBE-based models were established through the random forest algorithm. WBE-based models accurately predicted the county-level weekly new admissions, allowing a preparation window of 1-4 weeks. In real applications, periodically updated WBE-based models showed good accuracy and transferability, with mean absolute error within 4-6 patients/100k population for upcoming weekly new hospitalization numbers. Our study demonstrated the potential of using WBE as an effective method to provide early warnings for healthcare systems.