tetano
Editor, Senior Moderator
BMC Infect Dis
. 2025 Oct 9;25(1):1256.
doi: 10.1186/s12879-025-11633-8. Association between SARS-CoV-2 levels in urban wastewater and reported COVID-19 cases in Changsha, Central China
Ling-Shuang Lv[SUP] 1 [/SUP], Xiu-Ying Liu[SUP] 1 [/SUP], Qian-Lai Sun[SUP] 1 [/SUP], Heng Zhang[SUP] 2 [/SUP], Jin-Fu Zhang[SUP] 2 [/SUP], Zhi-Wen Yang[SUP] 1 [/SUP], Ning-Yuan Guo[SUP] 1 [/SUP], Xin Xia[SUP] 3 [/SUP]
Affiliations
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 (R[SUP]2[/SUP] = 0.77, P < 0.05), 0.88 (R[SUP]2[/SUP] = 0.75, P < 0.05) and 0.90 (R[SUP]2[/SUP] = 0.77, P < 0.05), respectively.
Conclusions: Wastewater-based monitoring holds significant application value for trend prediction for COVID-19 cases.
Keywords: COVID-19; Linear regression model; Random forest model; SARS-CoV-2; Wastewater.
. 2025 Oct 9;25(1):1256.
doi: 10.1186/s12879-025-11633-8. Association between SARS-CoV-2 levels in urban wastewater and reported COVID-19 cases in Changsha, Central China
Ling-Shuang Lv[SUP] 1 [/SUP], Xiu-Ying Liu[SUP] 1 [/SUP], Qian-Lai Sun[SUP] 1 [/SUP], Heng Zhang[SUP] 2 [/SUP], Jin-Fu Zhang[SUP] 2 [/SUP], Zhi-Wen Yang[SUP] 1 [/SUP], Ning-Yuan Guo[SUP] 1 [/SUP], Xin Xia[SUP] 3 [/SUP]
Affiliations
- PMID: 41068694
- DOI: 10.1186/s12879-025-11633-8
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 (R[SUP]2[/SUP] = 0.77, P < 0.05), 0.88 (R[SUP]2[/SUP] = 0.75, P < 0.05) and 0.90 (R[SUP]2[/SUP] = 0.77, P < 0.05), respectively.
Conclusions: Wastewater-based monitoring holds significant application value for trend prediction for COVID-19 cases.
Keywords: COVID-19; Linear regression model; Random forest model; SARS-CoV-2; Wastewater.