4.7 Article

Identification and genome sequencing of an influenza H3N2 variant in wastewater from elementary schools during a surge of influenza A cases in Las Vegas, Nevada

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SCIENCE OF THE TOTAL ENVIRONMENT
卷 872, 期 -, 页码 -

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ELSEVIER
DOI: 10.1016/j.scitotenv.2023.162058

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SARS-CoV-2; COVID-19; Influenza; Wastewater; Elementary schools; mutation

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Real-time surveillance of infectious diseases is often hindered by delays in reporting. This study demonstrates the utility of wastewater surveillance for the detection of local influenza transmission in schools. By incorporating quantitative PCR and genome sequencing, the researchers identified vaccine-resistant influenza A (H3N2) subclade in wastewater samples from elementary schools.
Real-time surveillance of infectious diseases at schools or in communities is often hampered by delays in reporting due to resource limitations and infrastructure issues. By incorporating quantitative PCR and genome sequencing, wastewa-ter surveillance has been an effective complement to public health surveillance at the community and building-scale for pathogens such as poliovirus, SARS-CoV-2, and even the monkeypox virus. In this study, we asked whether waste-water surveillance programs at elementary schools could be leveraged to detect RNA from influenza viruses shed in wastewater. We monitored for influenza A and B viral RNA in wastewater from six elementary schools from January to May 2022. Quantitative PCR led to the identification of influenza A viral RNA at three schools, which coincided with the lifting of COVID-19 restrictions and a surge in influenza A infections in Las Vegas, Nevada, USA. We performed genome sequencing of wastewater RNA, leading to the identification of a 2021-2022 vaccine-resistant influenza A (H3N2) 3C.2a1b.2a.2 subclade. We next tested wastewater samples from a treatment plant that serviced the elemen-tary schools, but we were unable to detect the presence of influenza A/B RNA. Together, our results demonstrate the utility of near-source wastewater surveillance for the detection of local influenza transmission in schools, which has the potential to be investigated further with paired school-level influenza incidence data.

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