Augmentation of wastewater-based epidemiology with machine learning to support global health surveillance

Augmentation of wastewater-based epidemiology with machine learning to support global health surveillance

  • Kilaru, P. et al. Wastewater surveillance for infectious disease: a systematic review. Am. J. Epidemiol. 192, 305–322 (2023).

    Article 
    PubMed 

    Google Scholar 

  • Adhikari, S. & Halden, R. U. Opportunities and limits of wastewater-based epidemiology for tracking global health and attainment of UN sustainable development goals. Environ. Int. 163, 107217 (2022).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Kasprzyk-Hordern, B. et al. Wastewater-based epidemiology for the assessment of population exposure to chemicals: the need for integration with human biomonitoring for global One Health actions. J. Hazard. Mater. 450, 131009 (2023).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Wilson, W. J. Isolation of enteric bacilli from sewage and water and its bearing on epidemiology. Br. Med. J. 2, 560–562 (1933).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Paul, J. R., Trask, J. D. & Culotta, C. S. Poliomyelitic virus in sewage. Science (1939).

    Article 
    PubMed 

    Google Scholar 

  • Singer, A. C. et al. A world of wastewater-based epidemiology. Nat. Water 1, 408–415 (2023).

    Article 

    Google Scholar 

  • Hendriksen, R. S. et al. Global monitoring of antimicrobial resistance based on metagenomics analyses of urban sewage. Nat. Commun. 10, 1124 (2019).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Fouz, N. et al. The contribution of wastewater to the transmission of antimicrobial resistance in the environment: implications of mass gathering settings. Trop. Med. Infect. Dis. 5, 33 (2020).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Agrawal, S. et al. Prevalence and circulation patterns of SARS-CoV-2 variants in European sewage mirror clinical data of 54 European cities. Water Res. 214, 118162 (2022).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Koureas, M. et al. Wastewater levels of respiratory syncytial virus associated with influenza-like illness rates in children—a case study in Larissa, Greece (October 2022–January 2023). Int. J. Environ. Res. Public. Health 20, 5219 (2023).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Link-Gelles, R. Public Health response to a case of paralytic poliomyelitis in an unvaccinated person and detection of Poliovirus in wastewater—New York, June–August 2022. MMWR Morb. Mortal. Wkly Rep. 71, 1065–1068 (2022).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Boehm, A. B. et al. Human norovirus (HuNoV) GII RNA in wastewater solids at 145 United States wastewater treatment plants: comparison to positivity rates of clinical specimens and modeled estimates of HuNoV GII shedders. J. Expo. Sci. Environ. Epidemiol. 34, 440–447 (2024).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Wastewater Analysis and Drugs—a European Multi-city Study (European Union Drug Agency, 2025); https://www.emcdda.europa.eu/publications/html/pods/waste-water-analysis_en

  • Bade, R., Ghetia, M., White, J. M. & Gerber, C. Determination of prescribed and designer benzodiazepines and metabolites in influent wastewater. Anal. Methods Adv. Methods Appl. 12, 3637–3644 (2020).

    CAS 

    Google Scholar 

  • Yao, Y. et al. Investigating alcohol consumption in China via wastewater-based epidemiology. Environ. Geochem. Health 46, 24 (2024).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Zhong, Y. et al. Application of wastewater-based epidemiology to estimate the usage of beta-agonists in 31 cities in China. Sci. Total Environ. 894, 164956 (2023).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Bowes, D. A. et al. Integrated multiomic wastewater-based epidemiology can elucidate population-level dietary behaviour and inform public health nutrition assessments. Nat. Food 4, 257–266 (2023).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Munk, P. et al. Genomic analysis of sewage from 101 countries reveals global landscape of antimicrobial resistance. Nat. Commun. 13, 7251 (2022).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Adisasmito, W. B. et al. One Health: a new definition for a sustainable and healthy future. PLoS Pathog. 18, e1010537 (2022).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Rodriguez-Mozaz, S. et al. Antibiotic residues in final effluents of European wastewater treatment plants and their impact on the aquatic environment. Environ. Int. 140, 105733 (2020).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Irrgang, C. et al. Anwendungsbereiche von künstlicher Intelligenz im Kontext von One Health mit Fokus auf antimikrobielle Resistenzen. Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz (2023).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Groussin, M. et al. Elevated rates of horizontal gene transfer in the industrialized human microbiome. Cell 184, 2053–2067.e18 (2021).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Fang, G.-Y., Liu, X.-Q., Jiang, Y.-J., Mu, X.-J. & Huang, B.-W. Horizontal gene transfer in activated sludge enhances microbial antimicrobial resistance and virulence. Sci. Total Environ. 912, 168908 (2024).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Buelow, E. et al. Hospital discharges in urban sanitation systems: long-term monitoring of wastewater resistome and microbiota in relationship to their eco-exposome. Water Res. X 7, 100045 (2020).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Chen, H. et al. Source identification of antibiotic resistance genes in a peri-urban river using novel crAssphage marker genes and metagenomic signatures. Water Res. 167, 115098 (2019).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Kasprzyk-Hordern, B. et al. Wastewater-based epidemiology for comprehensive community health diagnostics in a national surveillance study: mining biochemical markers in wastewater. J. Hazard. Mater. 450, 130989 (2023).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Barcellos, D. S., Barquilha, C. E. R., Oliveira, P. E., Prokopiuk, M. & Etchepare, R. G. How has the COVID-19 pandemic impacted wastewater-based epidemiology? Sci. Total Environ. 892, 164561 (2023).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Ciannella, S., González-Fernández, C. & Gomez-Pastora, J. Recent progress on wastewater-based epidemiology for COVID-19 surveillance: a systematic review of analytical procedures and epidemiological modeling. Sci. Total Environ. 878, 162953 (2023).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Rauch, W., Schenk, H., Insam, H., Markt, R. & Kreuzinger, N. Data modelling recipes for SARS-CoV-2 wastewater-based epidemiology. Environ. Res. 214, 113809 (2022).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Sweetapple, C. et al. Dynamic population normalisation in wastewater-based epidemiology for improved understanding of the SARS-CoV-2 prevalence: a multi-site study. J. Water Health 21, 625–642 (2023).

    Article 
    PubMed 

    Google Scholar 

  • Zhan, Q. et al. Relationships between SARS-CoV-2 in wastewater and COVID-19 clinical cases and hospitalizations, with and without normalization against indicators of human waste. ACS EST Water 2, 1992–2003 (2022).

    Article 
    CAS 

    Google Scholar 

  • Jiang, G. et al. Moving forward with COVID-19: future research prospects of wastewater-based epidemiology methodologies and applications. Curr. Opin. Environ. Sci. Health 33, 100458 (2023).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Ai, Y., He, F., Lancaster, E. & Lee, J. Application of machine learning for multi-community COVID-19 outbreak predictions with wastewater surveillance. PLoS ONE 17, e0277154 (2022).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Li, X. et al. Data-driven estimation of COVID-19 community prevalence through wastewater-based epidemiology. Sci. Total Environ. 789, 147947 (2021).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Lai, M., Wulff, S. S., Cao, Y., Robinson, T. J. & Rajapaksha, R. An interpretable time series machine learning method for varying forecast and nowcast lengths in wastewater-based epidemiology. MethodsX 11, 102382 (2023).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Wade, M. J. et al. Understanding and managing uncertainty and variability for wastewater monitoring beyond the pandemic: lessons learned from the United Kingdom national COVID-19 surveillance programmes. J. Hazard. Mater. 424, 127456 (2022).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Morvan, M. et al. An analysis of 45 large-scale wastewater sites in England to estimate SARS-CoV-2 community prevalence. Nat. Commun. 13, 4313 (2022).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Schmitz, B. W. et al. Enumerating asymptomatic COVID-19 cases and estimating SARS-CoV-2 fecal shedding rates via wastewater-based epidemiology. Sci. Total Environ. 801, 149794 (2021).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Feng, S. et al. Intensity of sample processing methods impacts wastewater SARS-CoV-2 whole genome amplicon sequencing outcomes. Sci. Total Environ. 876, 162572 (2023).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Mello, M. M., Meschke, J. S. & Palmer, G. H. Mainstreaming wastewater surveillance for infectious disease. N. Engl. J. Med. 388, 1441–1444 (2023).

    Article 
    PubMed 

    Google Scholar 

  • Hoar, C. et al. Looking forward: the role of academic researchers in building sustainable wastewater surveillance programs. Environ. Health Perspect. 130, 125002 (2022).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Sanyal, A., Agarwal, S., Ramakrishnan, U., Garg, K. M. & Chattopadhyay, B. Using environmental sampling to enable zoonotic pandemic preparedness. J. Indian Inst. Sci. 102, 711–730 (2022).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Xagoraraki, I. & O’Brien, E. in Women in Water Quality: Investigations by Prominent Female Engineers (ed. O’Bannon, D. J.) 75–97 (Springer, 2020); https://doi.org/10.1007/978-3-030-17819-2_5

  • Barber, C. et al. Community-scale wastewater surveillance of Candida auris during an ongoing outbreak in southern Nevada. Environ. Sci. Technol. 57, 1755–1763 (2023).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Cai, L. & Zhang, T. Detecting human bacterial pathogens in wastewater treatment plants by a high-throughput shotgun sequencing technique. Environ. Sci. Technol. 47, 5433–5441 (2013).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Shah, S. et al. Wastewater surveillance to infer COVID-19 transmission: a systematic review. Sci. Total Environ. 804, 150060 (2022).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • EU-WISH: EU4 Health Project 11/2023–10/2026 (Statens Serum Institut, 2024); https://en.ssi.dk/surveillance-and-preparedness/international-coorporation/eu-wish

  • Health Emergency Preparedness and Response Authority. The European Commission Lays the Foundations for a Global System for Wastewater Surveillance for Public Health (European Commission, 2023); https://health.ec.europa.eu/latest-updates/european-commission-lays-foundations-global-system-wastewater-surveillance-public-health-2023-11-14_en

  • Keshaviah, A. et al. Wastewater monitoring can anchor global disease surveillance systems. Lancet Glob. Health 11, e976–e981 (2023).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Directive (EU) 2024/3019 of the European Parliament and of the Council of 27 November 2024 Concerning Urban Wastewater Treatment (recast) (Text with EEA relevance) (European Commission, 2024); https://eur-lex.europa.eu/eli/dir/2024/3019/oj

  • Gholizadeh, A., Khiadani, M., Foroughi, M., Alizade Siuki, H. & Mehrfar, H. Wastewater treatment plants: the missing link in global One-Health surveillance and management of antibiotic resistance. J. Infect. Public Health 16, 217–224 (2023).

    Article 
    PubMed 

    Google Scholar 

  • Miłobedzka, A. et al. Monitoring antibiotic resistance genes in wastewater environments: the challenges of filling a gap in the One-Health cycle. J. Hazard. Mater. 424, 127407 (2022).

    Article 
    PubMed 

    Google Scholar 

  • Xiao, K. & Zhang, L. Wastewater pathogen surveillance based on One Health approach. Lancet Microbe 4, e297 (2023).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Grassly, N. C., Shaw, A. G. & Owusu, M. Global wastewater surveillance for pathogens with pandemic potential: opportunities and challenges. Lancet Microbe 6, 100939 (2024).

    Article 
    PubMed 

    Google Scholar 

  • Ahmed, W. et al. Leveraging wastewater surveillance to detect viral diseases in livestock settings. Sci. Total Environ. 931, 172593 (2024).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Plowright, R. K. et al. Pathways to zoonotic spillover. Nat. Rev. Microbiol. 15, 502–510 (2017).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Costa, F. et al. Patterns in Leptospira shedding in Norway rats (Rattus norvegicus) from Brazilian slum communities at high risk of disease transmission. PLoS Negl. Trop. Dis. 9, e0003819 (2015).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Wolfe, M. K. et al. Wastewater detection of emerging Arbovirus infections: case study of Dengue in the United States. Environ. Sci. Technol. Lett. 11, 9–15 (2024).

    Article 
    CAS 

    Google Scholar 

  • Foyle, L. et al. Prevalence and distribution of antimicrobial resistance in effluent wastewater from animal slaughter facilities: a systematic review. Environ. Pollut. 318, 120848 (2023).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Risely, A. et al. Host–plasmid network structure in wastewater is linked to antimicrobial resistance genes. Nat. Commun. 15, 555 (2024).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Monteiro, S., Pimenta, R., Nunes, F., Cunha, M. V. & Santos, R. Detection of dengue virus and chikungunya virus in wastewater in Portugal: an exploratory surveillance study. Lancet Microbe 5, 100911 (2024).

    Article 
    PubMed 

    Google Scholar 

  • Fanok, S., Monis, P. T., Keegan, A. R. & King, B. J. The detection of Japanese encephalitis virus in municipal wastewater during an acute disease outbreak. J. Appl. Microbiol. 134, lxad275 (2023).

    Article 
    PubMed 

    Google Scholar 

  • Chen, W. & Bibby, K. A model-based framework to assess the feasibility of monitoring Zika virus with wastewater-based epidemiology. ACS EST Water 3, 1071–1081 (2023).

    Article 
    CAS 

    Google Scholar 

  • Ansari, N. et al. Environmental surveillance for COVID-19 using SARS-CoV-2 RNA concentration in wastewater—a study in District East, Karachi, Pakistan. Lancet Reg. Health – Southeast Asia 20, 100299 (2024).

    Article 
    PubMed 

    Google Scholar 

  • Barnes, K. G. et al. Utilizing river and wastewater as a SARS-CoV-2 surveillance tool in settings with limited formal sewage systems. Nat. Commun. 14, 7883 (2023).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Diamond, M. B., Yee, E., Bhinge, M. & Scarpino, S. V. Wastewater surveillance facilitates climate change-resilient pathogen monitoring. Sci. Transl. Med. 15, eadi7831 (2023).

    Article 
    PubMed 

    Google Scholar 

  • Ishtiaq, F. Wastewater-based surveillance of vector-borne pathogens: a cautionary note. Trends Parasitol. 40, 93–95 (2024).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Li, J. et al. In situ calibration of passive samplers for viruses in wastewater. ACS EST Water 2, 1881–1890 (2022).

    Article 
    CAS 

    Google Scholar 

  • Hillebrand, O., Musallam, S., Scherer, L., Nödler, K. & Licha, T. The challenge of sample-stabilisation in the era of multi-residue analytical methods: a practical guideline for the stabilisation of 46 organic micropollutants in aqueous samples. Sci. Total Environ. 454–455, 289–298 (2013).

    Article 
    PubMed 

    Google Scholar 

  • Markt, R. et al. Detection and stability of SARS-CoV-2 fragments in wastewater: impact of storage temperature. Pathogens 10, 1215 (2021).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Karthikeyan, S. et al. Wastewater sequencing reveals early cryptic SARS-CoV-2 variant transmission. Nature 609, 101–108 (2022).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Bognich, G., Howell, N. & Butler, E. Fate-and-transport modeling of SARS-CoV-2 for rural wastewater-based epidemiology application benefit. Heliyon 10, e25927 (2024).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Tiwari, A. et al. Wastewater surveillance of antibiotic-resistant bacterial pathogens: a systematic review. Front. Microbiol. 13, 977106 (2022).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Abdeldayem, O. M. et al. Viral outbreaks detection and surveillance using wastewater-based epidemiology, viral air sampling and machine learning techniques: a comprehensive review and outlook. Sci. Total Environ. 803, 149834 (2022).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Kanneganti, D., Reinersman, L. E., Holm, R. H. & Smith, T. Estimating sewage flow rate in Jefferson County, Kentucky, using machine learning for wastewater-based epidemiology applications. Water Supply 22, 8434–8439 (2022).

    Article 

    Google Scholar 

  • Matheri, A. N., Belaid, M., Njenga, C. K. & Ngila, J. C. Water and wastewater digital surveillance for monitoring and early detection of the COVID-19 hotspot: industry 4.0. Int. J. Environ. Sci. Technol. 20, 1095–1112 (2023).

    Article 
    CAS 

    Google Scholar 

  • Bertels, X. et al. Factors influencing SARS-CoV-2 RNA concentrations in wastewater up to the sampling stage: a systematic review. Sci. Total Environ. 820, 153290 (2022).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Wiesner-Friedman, C. et al. Characterizing spatial information loss for wastewater surveillance using crAssphage: effect of decay, temperature and population mobility. Environ. Sci. Technol. 57, 20802–20812 (2023).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Wyler, E. et al. Pathogen dynamics and discovery of novel viruses and enzymes by deep nucleic acid sequencing of wastewater. Environ. Int. 190, 108875 (2024).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Rabe, A. et al. Correlation between wastewater and COVID-19 case incidence rates in major California sewersheds across three variant periods. J. Water Health 21, 1303–1317 (2023).

    Article 
    PubMed 

    Google Scholar 

  • Schill, R., Nelson, K. L., Harris-Lovett, S. & Kantor, R. S. The dynamic relationship between COVID-19 cases and SARS-CoV-2 wastewater concentrations across time and space: considerations for model training data sets. Sci. Total Environ. 871, 162069 (2023).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Sakarovitch, C. et al. Monitoring of SARS-CoV-2 in wastewater: what normalisation for improved understanding of epidemic trends? J. Water Health 20, 712–726 (2022).

    Article 
    PubMed 

    Google Scholar 

  • Al-Faliti, M. et al. Comparing rates of change in SARS-CoV-2 wastewater load and clinical cases in 19 sewersheds across four major metropolitan areas in the United States. ACS EST Water 2, 2233–2242 (2022).

    Article 
    CAS 

    Google Scholar 

  • Isaksson, F., Lundy, L., Hedström, A., Székely, A. J. & Mohamed, N. Evaluating the use of alternative normalization approaches on SARS-CoV-2 concentrations in wastewater: experiences from two catchments in northern Sweden. Environments 9, 39 (2022).

    Article 

    Google Scholar 

  • Hsu, S.-Y. et al. Biomarkers selection for population normalization in SARS-CoV-2 wastewater-based epidemiology. Water Res. 223, 118985 (2022).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • McClary-Gutierrez, J. S. et al. Standardizing data reporting in the research community to enhance the utility of open data for SARS-CoV-2 wastewater surveillance. Environ. Sci. Water Res. Technol. 7, 1545–1551 (2021).

    Article 
    CAS 

    Google Scholar 

  • Data Structures Working Group (2020).

  • Manuel, D. et al. Public Health Environmental Surveillance Open Data Model (PHES-ODM) (OSFHOME, 2021); https://doi.org/10.17605/OSF.IO/49Z2B

  • Amman, F. et al. Viral variant-resolved wastewater surveillance of SARS-CoV-2 at national scale. Nat. Biotechnol. 40, 1814–1822 (2022).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Kayikcioglu, T. et al. Performance of methods for SARS-CoV-2 variant detection and abundance estimation within mixed population samples. PeerJ 11, e14596 (2023).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Smyth, D. S. et al. Tracking cryptic SARS-CoV-2 lineages detected in NYC wastewater. Nat. Commun. 13, 635 (2022).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Cao, Y. & Francis, R. On forecasting the community-level COVID-19 cases from the concentration of SARS-CoV-2 in wastewater. Sci. Total Environ. 786, 147451 (2021).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Schenk, H. et al. Prediction of hospitalisations based on wastewater-based SARS-CoV-2 epidemiology. Sci. Total Environ. 873, 162149 (2023).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Soller, J. et al. Modeling infection from SARS-CoV-2 wastewater concentrations: promise, limitations and future directions. J. Water Health 20, 1197–1211 (2022).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Jiang, G. et al. Artificial neural network-based estimation of COVID-19 case numbers and effective reproduction rate using wastewater-based epidemiology. Water Res. 218, 118451 (2022).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Senaratna, K. Y. K. et al. Estimating COVID-19 cases on a university campus based on Wastewater Surveillance using machine learning regression models. Sci. Total Environ. 906, 167709 (2024).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Lin, T. et al. Optimizing campus-wide COVID-19 test notifications with interpretable wastewater time-series features using machine learning models. Sci. Rep. 13, 20670 (2023).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Vaughan, L. et al. An exploration of challenges associated with machine learning for time series forecasting of COVID-19 community spread using wastewater-based epidemiological data. Sci. Total Environ. 858, 159748 (2023).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Fazli, M. & Shakeri, H. Leveraging deep learning to improve COVID-19 forecasting using wastewater vira load. In Proceedings of 2023 IEEE International Conference on Big Data (BigData), 2705–2713 (IEEE, 2023).

  • Zehnder, C. et al. Machine learning for detecting virus infection hotspots via wastewater-based epidemiology: the case of SARS-CoV-2 RNA. GeoHealth 7, e2023GH000866 (2023).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Nourbakhsh, S. et al. A wastewater-based epidemic model for SARS-CoV-2 with application to three Canadian cities. Epidemics 39, 100560 (2022).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Torabi, F. et al. Wastewater-based surveillance models for COVID-19: a focused review on spatio-temporal models. Heliyon 9, e21734 (2023).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Baaijens, J. A. et al. Lineage abundance estimation for SARS-CoV-2 in wastewater using transcriptome quantification techniques. Genome Biol. 23, 236 (2022).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Aßmann, E. et al. Impact of reference design on estimating SARS-CoV-2 lineage abundances from wastewater sequencing data. GigaScience 13, giae051 (2024).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Mathieu, A., Leclercq, M., Sanabria, M., Perin, O. & Droit, A. Machine learning and deep learning applications in metagenomic taxonomy and functional annotation. Front. Microbiol. 13, 811495 (2022).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Férez, J. A. et al. Wastewater-based epidemiology to describe the evolution of SARS-CoV-2 in the south-east of Spain, and application of phylogenetic analysis and a machine learning approach. Viruses 15, 1499 (2023).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Chen, H. et al. Environmental risk characterization and ecological process determination of bacterial antibiotic resistome in lake sediments. Environ. Int. 147, 106345 (2021).

    Article 
    PubMed 

    Google Scholar 

  • Oh, M. et al. MetaCompare: a computational pipeline for prioritizing environmental resistome risk. FEMS Microbiol. Ecol. 94, fiy079 (2018).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Zahra, Q., Gul, J., Shah, A. R., Yasir, M. & Karim, A. M. Antibiotic resistance genes prevalence prediction and interpretation in beaches affected by urban wastewater discharge. One Health Amst. Neth. 17, 100642 (2023).

    Article 
    CAS 

    Google Scholar 

  • Arango-Argoty, G. et al. DeepARG: a deep learning approach for predicting antibiotic resistance genes from metagenomic data. Microbiome 6, 23 (2018).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Newton, R. J. & McClary, J. S. The flux and impact of wastewater infrastructure microorganisms on human and ecosystem health. Curr. Opin. Biotechnol. 57, 145–150 (2019).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Zhi, W., Appling, A. P., Golden, H. E., Podgorski, J. & Li, L. Deep learning for water quality. Nat. Water 2, 228–241 (2024).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Rashed, E. A. & Hirata, A. One-year lesson: machine learning prediction of COVID-19 positive cases with meteorological data and mobility estimate in Japan. Int. J. Environ. Res. Public Health 18, 5736 (2021).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Ramchandani, A., Fan, C. & Mostafavi, A. DeepCOVIDNet: an interpretable deep learning model for predictive surveillance of COVID-19 using heterogeneous features and their interactions. IEEE Access 8, 159915–159930 (2020).

    Article 
    PubMed 

    Google Scholar 

  • Fritz, C., Dorigatti, E. & Rügamer, D. Combining graph neural networks and spatio-temporal disease models to improve the prediction of weekly COVID-19 cases in Germany. Sci. Rep. 12, 3930 (2022).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Mwanga, M. J., Obura, H. O., Evans, M. & Awe, O. I. Enhanced deep convolutional neural network for SARS-CoV-2 variants classification. Preprint at bioRxiv (2023).

  • Jahshan, Z. & Yavits, L. ViTAL: Vision TrAnsformer based Low coverage SARS-CoV-2 lineage assignment. Bioinformatics 40, btae093 (2024).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Jahn, K. et al. Early detection and surveillance of SARS-CoV-2 genomic variants in wastewater using COJAC. Nat. Microbiol. 7, 1151–1160 (2022).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Schumann, V.-F. et al. SARS-CoV-2 infection dynamics revealed by wastewater sequencing analysis and deconvolution. Sci. Total Environ. 853, 158931 (2022).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Raharinirina, N. et al. SARS-CoV-2 evolution on a dynamic immune landscape. Nature 639, 196–204 (2025).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Sutcliffe, S. G. et al. Tracking SARS-CoV-2 variants of concern in wastewater: an assessment of nine computational tools using simulated genomic data. Microb. Genomics 10, 001249 (2024).

    Article 
    CAS 

    Google Scholar 

  • Meyer, F. et al. Critical assessment of metagenome interpretation: the second round of challenges. Nat. Methods 19, 429–440 (2022).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Perez-Zabaleta, M. et al. Long-term SARS-CoV-2 surveillance in the wastewater of Stockholm: what lessons can be learned from the Swedish perspective? Sci. Total Environ. 858, 160023 (2023).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • WHO to Identify Pathogens that Could Cause Future Outbreaks and Pandemics (World Health Organization, 2022); https://www.who.int/news/item/21-11-2022-who-to-identify-pathogens-that-could-cause-future-outbreaks-and-pandemics

  • Urban, L. et al. Real‐time genomics for One Health. Mol. Syst. Biol. 19, e11686 (2023).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Jones, D. T. Setting the standards for machine learning in biology. Nat. Rev. Mol. Cell Biol. 20, 659–660 (2019).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Walsh, I. et al. DOME: recommendations for supervised machine learning validation in biology. Nat. Methods 18, 1122–1127 (2021).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Galani, A. et al. SARS-CoV-2 wastewater surveillance data can predict hospitalizations and ICU admissions. Sci. Total Environ. 804, 150151 (2022).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Dejus, B. et al. Wastewater-based prediction of COVID-19 cases using a random forest algorithm with strain prevalence data: a case study of five municipalities in Latvia. Sci. Total Environ. 891, 164519 (2023).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Naughton, C. C. et al. Show us the data: global COVID-19 wastewater monitoring efforts, equity and gaps. FEMS Microbes 4, xtad003 (2023).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • EL Bilali, A., Taleb, A., Bahlaoui, M. A. & Brouziyne, Y. An integrated approach based on Gaussian noises-based data augmentation method and AdaBoost model to predict faecal coliforms in rivers with small dataset. J. Hydrol. 599, 126510 (2021).

    Article 

    Google Scholar 

  • Gupta, P., Malhotra, P., Narwariya, J., Vig, L. & Shroff, G. Transfer learning for clinical time series analysis using deep neural networks. J. Healthc. Inform. Res. 4, 112–137 (2020).

    Article 
    PubMed 

    Google Scholar 

  • link

    Leave a Reply

    Your email address will not be published. Required fields are marked *