BMC infectious diseases · 2025
Association between SARS-CoV-2 levels in urban wastewater and reported COVID-19 cases in Changsha, Central China.
СтатьяНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Lv Ling-Shuang, Liu Xiu-Ying, Sun Qian-Lai, Zhang Heng, Zhang Jin-Fu, Yang Zhi-Wen, Guo Ning-Yuan, Xia Xin
Аннотация
OBJECTIVE: To analyze the monitoring results of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) in urban wastewater, and explore the association between SARS-CoV-2 levels in urban wastewater and human Coronavirus disease 2019 (COVID-19) infection.
METHODS: The concentrations of SARS-CoV-2 RNA in urban wastewater and the number of reported COVID-19 cases were collected in Changsha, Central China, between March 22, 2023 and December 31, 2024. Correlation analysis was used to explore the correlation between the SARS-CoV-2 RNA levels in wastewater and the number of reported COVID-19 cases. Linear regression and random forest models were used to analyze the predictive function of SARS-CoV-2 in wastewater on human COVID-19 cases.
RESULTS: A total of 2,026 wastewater samples were collected. The positive rate of SARS-CoV-2 in wastewater was 82.0%. The positive rates of target Genes ORFlab and N were 71.7% and 81.4%, respectively. In the same period, 70,525 cases of COVID-19 were reported. The concentrations of target genes ORFlab and N in wastewater exhibited consistent trends (r = 0.95, 95% CI: 0.93-0.97) and were positively correlated with the number of reported COVID-19 cases (r = 0.79, 95% CI: 0.70-0.86; r = 0.77, 95% CI: 0.67-0.84). The linear regression model showed that the coefficients of determination between the number of reported COVID-19 cases and the levels of SARS-CoV-2 RNA (ORFlab, N) in wastewater were 0.63 and 0.59, respectively. In the test set, the random forest model indicated that the correlation coefficients between the number of reported COVID-19 cases and the predicted cases based on the concentration of target Gene ORFlab, target gene N and their combined concentration in wastewater were 0.89 (R2 = 0.77, P < 0.05), 0.88 (R2 = 0.75, P < 0.05) and 0.90 (R2 = 0.77, P < 0.05), respectively.
CONCLUSIONS: Wastewater-based monitoring holds significant application value for trend prediction for COVID-19 cases.
METHODS: The concentrations of SARS-CoV-2 RNA in urban wastewater and the number of reported COVID-19 cases were collected in Changsha, Central China, between March 22, 2023 and December 31, 2024. Correlation analysis was used to explore the correlation between the SARS-CoV-2 RNA levels in wastewater and the number of reported COVID-19 cases. Linear regression and random forest models were used to analyze the predictive function of SARS-CoV-2 in wastewater on human COVID-19 cases.
RESULTS: A total of 2,026 wastewater samples were collected. The positive rate of SARS-CoV-2 in wastewater was 82.0%. The positive rates of target Genes ORFlab and N were 71.7% and 81.4%, respectively. In the same period, 70,525 cases of COVID-19 were reported. The concentrations of target genes ORFlab and N in wastewater exhibited consistent trends (r = 0.95, 95% CI: 0.93-0.97) and were positively correlated with the number of reported COVID-19 cases (r = 0.79, 95% CI: 0.70-0.86; r = 0.77, 95% CI: 0.67-0.84). The linear regression model showed that the coefficients of determination between the number of reported COVID-19 cases and the levels of SARS-CoV-2 RNA (ORFlab, N) in wastewater were 0.63 and 0.59, respectively. In the test set, the random forest model indicated that the correlation coefficients between the number of reported COVID-19 cases and the predicted cases based on the concentration of target Gene ORFlab, target gene N and their combined concentration in wastewater were 0.89 (R2 = 0.77, P < 0.05), 0.88 (R2 = 0.75, P < 0.05) and 0.90 (R2 = 0.77, P < 0.05), respectively.
CONCLUSIONS: Wastewater-based monitoring holds significant application value for trend prediction for COVID-19 cases.