Community-level wastewater surveillance with machine learning methods to assess underreporting of COVID-19 case counts

Nathan Szeto , Jianfeng Wu , Yili Wang , Xin Li , Zheshi Zheng , Leyao Zhang , Richard Neitzel , Marisa Eisenberg , J. Tim Dvonch , Alfred Franzblau , Peter X. K. Song , Chuanwu Xi

mLife ›› 2025, Vol. 4 ›› Issue (6) : 715 -718.

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mLife ›› 2025, Vol. 4 ›› Issue (6) :715 -718. DOI: 10.1002/mlf2.70055
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Community-level wastewater surveillance with machine learning methods to assess underreporting of COVID-19 case counts
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Nathan Szeto, Jianfeng Wu, Yili Wang, Xin Li, Zheshi Zheng, Leyao Zhang, Richard Neitzel, Marisa Eisenberg, J. Tim Dvonch, Alfred Franzblau, Peter X. K. Song, Chuanwu Xi. Community-level wastewater surveillance with machine learning methods to assess underreporting of COVID-19 case counts. mLife, 2025, 4(6): 715-718 DOI:10.1002/mlf2.70055

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References

[1]

Mathieu E, Ritchie H, Rodés-Guirao L, Appel C, Giattino C, Hasell J, et al. Coronavirus pandemic (COVID-19). Our World in Data. 2020. https://ourworldindata.org/coronavirus

[2]

Su W, Choy KT, Gu H, Sia SF, Cheng KM, Nizami SIN, et al. Reduced pathogenicity and transmission potential of Omicron BA.1 and BA.2 sublineages compared with the early severe acute respiratory syndrome coronavirus 2 D614G variant in Syrian hamsters. J Infect Dis. 2023; 227: 1143–1152.

[3]

Uraki R, Kiso M, Iwatsuki-Horimoto K, Yamayoshi S, Ito M, Chiba S, et al. Characterization of an EG.5.1 clinical isolate in vitro and in vivo. bioRxiv. 2023. Cell Reports. 2023; 42:113580.

[4]

McCarthy Z, Athar S, Alavinejad M, Chow C, Moyles I, Nah K, et al. Quantifying the annual incidence and underestimation of seasonal influenza: a modelling approach. Theor Biol Med Modell. 2020; 17: 11.

[5]

Wang P, Hu T, Liu H, Zhu X. Exploring the impact of under-reported cases on the COVID-19 spatiotemporal distributions using healthcare workers infection data. Cities. 2022; 123:103593.

[6]

Gibbons CL, Mangen MJJ, Plass D, Havelaar AH, Brooke RJ, Kramarz P, et al. Measuring underreporting and under-ascertainment in infectious disease datasets: a comparison of methods. BMC Public Health. 2014; 14:147.

[7]

Rader B, Gertz A, Iuliano AD, Gilmer M, Wronski L, Astley CM, et al. Use of at-home COVID-19 tests—United States, August 23, 2021–March 12, 2022. MMWR Morb Mortal Wkly Rep. 2022; 71: 489–494.

[8]

Zhu Y, Oishi W, Maruo C, Saito M, Chen R, Kitajima M, et al. Early warning of COVID-19 via wastewater-based epidemiology: potential and bottlenecks. Sci Total Environ. 2021; 767:145124.

[9]

Olesen SW, Imakaev M, Duvallet C. Making waves: defining the lead time of wastewater-based epidemiology for COVID-19. Water Res. 2021; 202:117433.

[10]

Phan T, Brozak S, Pell B, Oghuan J, Gitter A, Hu T, et al. Making waves: integrating wastewater surveillance with dynamic modeling to track and predict viral outbreaks. Water Res. 2023; 243:120372.

[11]

Bivins A, North D, Ahmad A, Ahmed W, Alm E, Been F, et al. Wastewater-based epidemiology: global collaborative to maximize contributions in the fight against COVID-19. Environ Sci Technol. 2020; 54: 7754–7757.

[12]

Ghafouri-Fard S, Mohammad-Rahimi H, Motie P, Minabi MAS, Taheri M, Nateghinia S. Application of machine learning in the prediction of COVID-19 daily new cases: a scoping review. Heliyon. 2021; 7:e08143.

[13]

Lau H, Khosrawipour T, Kocbach P, Ichii H, Bania J, Khosrawipour V. Evaluating the massive underreporting and undertesting of COVID-19 cases in multiple global epicenters. Pulmonology. 2021; 27: 110–115.

[14]

Li R, Pei S, Chen B, Song Y, Zhang T, Yang W, et al. Substantial undocumented infection facilitates the rapid dissemination of novel coronavirus (SARS-CoV-2). Science. 2020; 368: 489–493.

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2025 The Author(s). mLife published by John Wiley & Sons Australia, Ltd on behalf of Institute of Microbiology, Chinese Academy of Sciences.

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