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Wastewater-based prediction of COVID-19 cases using a random forest algorithm with strain prevalence data: A case study of five municipalities in Latvia

Brigita Dejus, Pāvels Cacivkins, Dita Gudrā, Sandis Dejus, Maija Ustinova, Ance Roga, Mārtiņš Strods, Juris Ķibilds, Guntis Boikmanis, Karīna Ortlova, Laura Krivko, Līga Birzniece, Edmunds Skinderskis, Aivars Bērziņš, Dāvids Frīdmanis, Tālis Juhna

2023The Science of The Total Environment22 citationsDOIOpen Access PDF

Topics & Concepts

WastewaterOutbreakCoronavirus disease 2019 (COVID-19)Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)VirologyFurinEnvironmental scienceStatisticsBiologyMedicineEnvironmental engineeringMathematicsInternal medicineInfectious disease (medical specialty)BiochemistryEnzymeDiseaseSARS-CoV-2 detection and testingSARS-CoV-2 and COVID-19 ResearchBiosensors and Analytical Detection
Wastewater-based prediction of COVID-19 cases using a random forest algorithm with strain prevalence data: A case study of five municipalities in Latvia | Litcius