Longitudinal wastewater surveillance addressed public health priorities during the transition from "dynamic COVID-zero" to "opening up" in China: a population-based study
Li, Y.; Du, C.; Lv, Z.; Wang, F.; Zhou, L.; Peng, Y.; Li, W.; Fu, Y.; Song, J.; Jia, C.; Zhang, X.; Liu, M.; Wang, Z.; Liu, B.; Yan, S.; Yang, Y.; Li, X.; Zhang, Y.; Yuan, J.; Xu, S.; Chen, M.; Shi, X.; Peng, B.; Chen, Q.; Qiu, Y.; Wu, S.; Jiang, M.; Chen, M.; Tang, J.; Wang, L.; Hu, L.; Wan, C.; Lu, H.; Zhang, T.; Fu, S.; Zou, X.; Hu, Q.
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BackgroundWastewater surveillance provides real-time, cost-effective monitoring of SARS-CoV-2 transmission. We developed the first city-level wastewater warning system in mainland China, located in Shenzhen. Our study aimed to reveal cryptic transmissions under the "dynamic COVID-zero" policy and characterize the dynamics of the infected population and variant prevalence, and then guide the allocation of medical resources during the transition to "opening up" in China. MethodsIn this population-based study, a total of 1,204 COVID-19 cases were enrolled to evaluate the contribution of Omicron variant-specific faecal shedding rates in wastewater. After that, wastewater samples from up to 334 sites distributed in communities and port areas in two districts of Shenzhen covering 1{middle dot}74 million people were tested daily to evaluate the sensitivity and specificity of this approach, and were validated against daily SARS-CoV-2 screening. After the public health policy was switched to "opening up" in December 7, 2022, we conducted wastewater surveillance at wastewater treatment plants and pump stations covering 3{middle dot}55 million people to estimate infected populations using model prediction and detect the relative abundance of SARS-CoV-2 lineages using wastewater sequencing. FindingsIn total, 82{middle dot}4% of SARS-CoV-2 Omicron cases tested positive for faecal viral RNA within the first four days after the diagnosis, which was far more than the proportion of the ancestral variant. A total of 27,759 wastewater samples were detected from July 26 to November 30 in 2022, showing a sensitivity of 73{middle dot}8% and a specificity of 99{middle dot}8%. We further found that wastewater surveillance played roles in providing early warnings and revealing cryptic transmissions in two communities. Based on the above results, we employed a prediction model to monitor the daily number of infected individuals in Shenzhen during the transition to "opening up" in China, with over 80% of the population infected in both Futian District and Nanshan District. Notably, the prediction of the daily number of hospital admission was consistent with the actual number. Further sequencing revealed that the Omicron subvariant BA.5.2.48 accounted for the most abundant SARS-CoV-2 RNA in wastewater, and BF.7.14 and BA.5.2.49 ranked second and third, respectively, which was consistent with the clinical sequencing. InterpretationThis study provides a scalable solution for wastewater surveillance of SARS-CoV-2 to provide real-time monitoring of the new variants, infected populations and facilitate the precise prediction of hospital admission. This novel framework could be a One Health system for the surveillance of other infectious and emerging pathogens with faecal shedding and antibiotic resistance genes in the future. FundingSanming Project of Medicine in Shenzhen, Shenzhen Key Medical Discipline Construction Fund. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed for articles published from December 1, 2019, to February 28, 2023, without any language restrictions, using the search terms "wastewater surveillance", "SARS-CoV-2 shedding rate", and "China". After checking abstracts and full texts of the search results, we found that the field of wastewater-based epidemiology (WBE) has been considered as a powerful, rapid, and inexpensive tool to monitor SARS-CoV-2 transmission in recent years. Researchers realized that SARS-CoV-2 RNA in wastewater is mainly from the faecal virus shedding of infected individuals, and the number of infected individuals can be estimated using a prediction model based on the viral RNA load in wastewater and the faecal viral shedding rate. However, there are no published clinical data regarding the faecal shedding rates of the pandemic variant Omicron. In particular, no previous studies have reported the size of Chinas SARS-CoV-2 infection after the public health policy was switched to "opening up" in December 7, 2022. Added value of this studyThis study highlights pioneering work in the use of wastewater surveillance of SARS-CoV-2 conducted during the transition from "dynamic COVID-zero" to "opening up" in China. The study reported first about the high proportion of faecal viral shedding of SARS-CoV-2 Omicron cases, showcasing the generality of wastewater surveillance for tracking Omicron prevalence. On the one hand, wastewater surveillance can play roles in providing early warnings and revealing cryptic transmissions and has the potential to replace city-wide nucleic acid screening under stringent control measures. On the flip side, wastewater surveillance allows for robust predictions of the number of infected individuals, the relative abundance of SARS-CoV-2 lineages, and the rate of hospital admission after the public health policy was switched to relaxed COVID-19 restrictions. Implications of all the available evidenceGovernments are in urgent need of a paradigm to shorten the time lag observed between recognition of a new emerging pathogen with the potential to cause the next pandemic (e.g., SARS-CoV-2) and the development of public health response (e.g., early warning, management and control of the communities, allocation of medical resources). Our findings suggest that the system developed in this study is not only a valuable epidemiological tool to accurately monitor the infection trend but also transforms wastewater surveillance into a public health management framework, which could be a One Health system for the surveillance of other infectious and emerging pathogens with faecal shedding and antibiotic resistance genes.
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