{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T09:06:47Z","timestamp":1777626407479,"version":"3.51.4"},"reference-count":65,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2027,4,2]],"date-time":"2027-04-02T00:00:00Z","timestamp":1806624000000},"content-version":"am","delay-in-days":305,"URL":"http:\/\/www.elsevier.com\/open-access\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/100008545","name":"Georgia State University","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100008545","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["2125246"],"award-info":[{"award-number":["2125246"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["OISE-2412914"],"award-info":[{"award-number":["OISE-2412914"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Journal of Theoretical Biology"],"published-print":{"date-parts":[[2026,6]]},"DOI":"10.1016\/j.jtbi.2026.112449","type":"journal-article","created":{"date-parts":[[2026,3,28]],"date-time":"2026-03-28T07:26:06Z","timestamp":1774682766000},"page":"112449","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["COVID-19 forecasting from U.S. wastewater surveillance data: A retrospective multi-model study (2022\u20132024)"],"prefix":"10.1016","volume":"626","author":[{"given":"Faharudeen","family":"Alhassan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hamed","family":"Karami","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Amanda","family":"Bleichrodt","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5247-5794","authenticated-orcid":false,"given":"James M.","family":"Hyman","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5496-2529","authenticated-orcid":false,"given":"Isaac C.H.","family":"Fung","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ruiyan","family":"Luo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gerardo","family":"Chowell","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"78","reference":[{"key":"10.1016\/j.jtbi.2026.112449_bib0001","doi-asserted-by":"crossref","DOI":"10.1016\/j.scitotenv.2024.171566","article-title":"The national wastewater surveillance system (NWSS): from inception to widespread coverage, 2020\u20132022, United States","volume":"924","author":"Adams","year":"2024","journal-title":"Sci. Total Environ."},{"issue":"1","key":"10.1016\/j.jtbi.2026.112449_bib0002","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1186\/s12961-023-00963-1","article-title":"Limitations of COVID-19 testing and case data for evidence-informed health policy and practice","volume":"21","author":"Alvarez","year":"2023","journal-title":"Health Res. Policy Syst."},{"key":"10.1016\/j.jtbi.2026.112449_bib0003","series-title":"A Practical Handbook of Corpus Linguistics","first-page":"563","article-title":"An introduction to the generalized additive model","author":"Baayen","year":"2020"},{"issue":"5","key":"10.1016\/j.jtbi.2026.112449_bib0004","doi-asserted-by":"crossref","first-page":"280","DOI":"10.1002\/env.2391","article-title":"Censored and shifted gamma distribution based EMOS model for probabilistic quantitative precipitation forecasting","volume":"27","author":"Baran","year":"2016","journal-title":"Environmetrics"},{"key":"10.1016\/j.jtbi.2026.112449_bib0005","first-page":"2","article-title":"Forecasting of COVID-19 epidemic size in four high hitting nations (USA, Brazil, India and Russia) by fb-prophet machine learning model","volume":"21","author":"Battineni","year":"2025","journal-title":"Appl. Comput. Inf."},{"key":"10.1016\/j.jtbi.2026.112449_bib0006","doi-asserted-by":"crossref","DOI":"10.1016\/j.dib.2020.105340","article-title":"Application of the ARIMA model on the COVID-2019 epidemic dataset","volume":"29","author":"Benvenuto","year":"2020","journal-title":"Data brief"},{"key":"10.1016\/j.jtbi.2026.112449_bib0007","doi-asserted-by":"crossref","DOI":"10.1016\/j.scitotenv.2022.153290","article-title":"Factors influencing SARS-COV-2 RNA concentrations in wastewater up to the sampling stage: a systematic review","volume":"820","author":"Bertels","year":"2022","journal-title":"Sci. Total Environ."},{"issue":"1","key":"10.1016\/j.jtbi.2026.112449_bib0008","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1186\/s12916-022-02725-2","article-title":"Real-time forecasting the trajectory of monkeypox outbreaks at the national and global levels, July\u2013October 2022","volume":"21","author":"Bleichrodt","year":"2023","journal-title":"BMC Med."},{"issue":"7","key":"10.1016\/j.jtbi.2026.112449_bib0009","doi-asserted-by":"crossref","DOI":"10.1098\/rsos.240248","article-title":"Evaluating the forecasting performance of ensemble sub-epidemic frameworks and other time series models for the 2022\u20132023 mpox epidemic","volume":"11","author":"Bleichrodt","year":"2024","journal-title":"R. Soc. Open Sci."},{"key":"10.1016\/j.jtbi.2026.112449_bib0010","article-title":"Statmodpredict: a user-friendly r-shiny interface for fitting and forecasting with statistical models","author":"Bleichrodt","year":"2024","journal-title":"Available at SSRN 4849702"},{"issue":"2","key":"10.1016\/j.jtbi.2026.112449_bib0011","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pcbi.1008618","article-title":"Evaluating epidemic forecasts in an interval format","volume":"17","author":"Bracher","year":"2021","journal-title":"PLOS Comput. Biol."},{"issue":"10","key":"10.1016\/j.jtbi.2026.112449_bib0012","article-title":"A flexible modeling framework for seasonal and pandemic influenza forecasting","volume":"14","author":"Brooks","year":"2018","journal-title":"PLoS Comput. Biol."},{"key":"10.1016\/j.jtbi.2026.112449_bib0013","unstructured":"CDC, 2024a. National wastewater surveillance system (NWSS). https:\/\/www.cdc.gov\/nwss\/rv\/COVID19-nationaltrend.html."},{"key":"10.1016\/j.jtbi.2026.112449_bib0014","unstructured":"CDC, 2024b. National wastewater surveillance system (NWSS). https:\/\/www.cdc.gov\/nwss\/about-data.html#data-method."},{"issue":"2","key":"10.1016\/j.jtbi.2026.112449_bib0015","first-page":"411","article-title":"Subepipredict: a tutorial-based primer and toolbox for fitting and forecasting growth trajectories using the ensemble n-sub-epidemic modeling framework","volume":"9","author":"Chowell","year":"2024","journal-title":"Infect. Dis. Model."},{"issue":"10","key":"10.1016\/j.jtbi.2026.112449_bib0016","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pcbi.1010602","article-title":"An ensemble n-sub-epidemic modeling framework for short-term forecasting epidemic trajectories: Application to the COVID-19 pandemic in the USA","volume":"18","author":"Chowell","year":"2022","journal-title":"PLoS Comput. Biol."},{"issue":"10","key":"10.1016\/j.jtbi.2026.112449_bib0017","doi-asserted-by":"crossref","DOI":"10.1098\/rsos.220021","article-title":"A retrospective assessment of COVID-19 model performance in the USA","volume":"9","author":"Colonna","year":"2022","journal-title":"R. Soc. Open Sci."},{"issue":"15","key":"10.1016\/j.jtbi.2026.112449_bib0018","doi-asserted-by":"crossref","DOI":"10.1073\/pnas.2113561119","article-title":"Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the united states","volume":"119","author":"Cramer","year":"2022","journal-title":"Proc. Natl. Acad. Sci."},{"key":"10.1016\/j.jtbi.2026.112449_bib0019","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s12040-020-01408-x","article-title":"Time series analysis of climate variables using seasonal ARIMA approach","volume":"129","author":"Dimri","year":"2020","journal-title":"J. Earth Syst. Sci."},{"key":"10.1016\/j.jtbi.2026.112449_bib0020","doi-asserted-by":"crossref","DOI":"10.1016\/j.scitotenv.2021.150639","article-title":"Model-based ensembles: lessons learned from retrospective analysis of COVID-19 infection forecasts across 10 countries","volume":"806","author":"Drews","year":"2022","journal-title":"Sci. Total Environ."},{"key":"10.1016\/j.jtbi.2026.112449_bib0021","doi-asserted-by":"crossref","DOI":"10.1177\/1847979018808673","article-title":"Forecasting of demand using ARIMA model","volume":"10","author":"Fattah","year":"2018","journal-title":"Int. J. Eng. Bus. Manage."},{"issue":"2","key":"10.1016\/j.jtbi.2026.112449_bib0022","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pcbi.1006785","article-title":"Assessing the performance of real-time epidemic forecasts","volume":"15","author":"Funk","year":"2019","journal-title":"PLoS Comput. Biol."},{"issue":"477","key":"10.1016\/j.jtbi.2026.112449_bib0023","doi-asserted-by":"crossref","first-page":"359","DOI":"10.1198\/016214506000001437","article-title":"Strictly proper scoring rules, prediction, and estimation","volume":"102","author":"Gneiting","year":"2007","journal-title":"J. Am. Stat. Assoc."},{"key":"10.1016\/j.jtbi.2026.112449_bib0024","doi-asserted-by":"crossref","DOI":"10.1016\/j.watres.2020.116296","article-title":"Covid-19 surveillance in Southeastern Virginia using wastewater-based epidemiology","volume":"186","author":"Gonzalez","year":"2020","journal-title":"Water Res."},{"key":"10.1016\/j.jtbi.2026.112449_bib0025","series-title":"The Elements of Statistical Learning: Data Mining, Inference, and Prediction","author":"Hastie","year":"2009"},{"issue":"4","key":"10.1016\/j.jtbi.2026.112449_bib0026","first-page":"1138","article-title":"Wastewater surveillance provides 10-days forecasting of COVID-19 hospitalizations superior to cases and test positivity: a prediction study","volume":"8","author":"Hill","year":"2023","journal-title":"Infect. Dis. Model."},{"key":"10.1016\/j.jtbi.2026.112449_bib0027","doi-asserted-by":"crossref","first-page":"1","DOI":"10.18637\/jss.v027.i03","article-title":"Automatic time series forecasting: the forecast package for R","volume":"27","author":"Hyndman","year":"2008","journal-title":"J. Stat. Software"},{"issue":"11","key":"10.1016\/j.jtbi.2026.112449_bib0028","doi-asserted-by":"crossref","first-page":"1923","DOI":"10.3390\/diagnostics13111923","article-title":"Short-term forecasting of monkeypox cases using a novel filtering and combining technique","volume":"13","author":"Iftikhar","year":"2023","journal-title":"Diagnostics"},{"issue":"1","key":"10.1016\/j.jtbi.2026.112449_bib0029","doi-asserted-by":"crossref","DOI":"10.1038\/s41598-022-18518-9","article-title":"Assessing wastewater-based epidemiology for the prediction of SARS-COV-2 incidence in Catalonia","volume":"12","author":"Joseph-Duran","year":"2022","journal-title":"Sci. Rep."},{"key":"10.1016\/j.jtbi.2026.112449_bib0030","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/1471-2105-7-485","article-title":"Machine learning techniques in disease forecasting: a case study on rice blast prediction","volume":"7","author":"Kaundal","year":"2006","journal-title":"BMC Bioinf."},{"issue":"36","key":"10.1016\/j.jtbi.2026.112449_bib0031","doi-asserted-by":"crossref","first-page":"1242","DOI":"10.15585\/mmwr.mm7036a2","article-title":"Using wastewater surveillance data to support the COVID-19 response-United States, 2020\u20132021","volume":"70","author":"Kirby","year":"2021","journal-title":"Morbidity Mortality Weekly Rep."},{"issue":"1","key":"10.1016\/j.jtbi.2026.112449_bib0032","doi-asserted-by":"crossref","first-page":"5475","DOI":"10.1038\/s41598-022-09345-z","article-title":"Excess mortality in belarus during the COVID-19 pandemic as the case study of a country with limited non-pharmaceutical interventions and limited reporting","volume":"12","author":"Kirpich","year":"2022","journal-title":"Sci. Rep."},{"key":"10.1016\/j.jtbi.2026.112449_bib0033","doi-asserted-by":"crossref","DOI":"10.1016\/j.scitotenv.2020.139076","article-title":"SARS-COV-2 in wastewater: state of the knowledge and research needs","volume":"739","author":"Kitajima","year":"2020","journal-title":"Sci. Total Environ."},{"issue":"1","key":"10.1016\/j.jtbi.2026.112449_bib0034","doi-asserted-by":"crossref","first-page":"4548","DOI":"10.1038\/s41467-023-40305-x","article-title":"Wastewater-based epidemiology predicts COVID-19-induced weekly new hospital admissions in over 150 USA counties","volume":"14","author":"Li","year":"2023","journal-title":"Nat. Commun."},{"key":"10.1016\/j.jtbi.2026.112449_bib0035","doi-asserted-by":"crossref","DOI":"10.1016\/j.jhazmat.2022.129848","article-title":"Correlation between SARS-COV-2 RNA concentration in wastewater and COVID-19 cases in community: a systematic review and meta-analysis","volume":"441","author":"Li","year":"2023","journal-title":"J. Hazardous Mater."},{"issue":"1","key":"10.1016\/j.jtbi.2026.112449_bib0036","doi-asserted-by":"crossref","first-page":"127","DOI":"10.3390\/forecast5010005","article-title":"Forecasting the monkeypox outbreak using ARIMA, prophet, neuralprophet, and LSTM models in the United States","volume":"5","author":"Long","year":"2023","journal-title":"Forecasting"},{"issue":"5","key":"10.1016\/j.jtbi.2026.112449_bib0037","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pcbi.1011200","article-title":"Challenges of COVID-19 case forecasting in the US, 2020\u20132021","volume":"20","author":"Lopez","year":"2024","journal-title":"PLoS Comput. Biol."},{"key":"10.1016\/j.jtbi.2026.112449_bib0038","doi-asserted-by":"crossref","DOI":"10.1016\/j.watres.2024.122671","article-title":"Epidemiological model can forecast COVID-19 outbreaks from wastewater-based surveillance in rural communities","volume":"268","author":"Meadows","year":"2025","journal-title":"Water Res."},{"issue":"7","key":"10.1016\/j.jtbi.2026.112449_bib0039","doi-asserted-by":"crossref","first-page":"511","DOI":"10.1021\/acs.estlett.0c00357","article-title":"Presence of SARS-coronavirus-2 RNA in sewage and correlation with reported COVID-19 prevalence in the early stage of the epidemic in the netherlands","volume":"7","author":"Medema","year":"2020","journal-title":"Environ. Sci. Technol. Lett."},{"issue":"2","key":"10.1016\/j.jtbi.2026.112449_bib0040","first-page":"13","article-title":"Study of effectiveness of time series modeling (ARIMA) in forecasting stock prices","volume":"4","author":"Mondal","year":"2014","journal-title":"Int. J. Comput. Sci. Eng. Appl."},{"key":"10.1016\/j.jtbi.2026.112449_bib0041","series-title":"Introduction to Time Series Analysis and Forecasting","author":"Montgomery","year":"2015"},{"issue":"10","key":"10.1016\/j.jtbi.2026.112449_bib0042","doi-asserted-by":"crossref","first-page":"e699","DOI":"10.1016\/S2589-7500(22)00167-4","article-title":"Real-time COVID-19 forecasting: challenges and opportunities of model performance and translation","volume":"4","author":"Nixon","year":"2022","journal-title":"Lancet Digit. Health"},{"issue":"1","key":"10.1016\/j.jtbi.2026.112449_bib0043","doi-asserted-by":"crossref","first-page":"e00103","DOI":"10.1128\/cmr.00103-22","article-title":"Wastewater-based surveillance as a tool for public health action: SARS-COV-2 and beyond","volume":"37","author":"Parkins","year":"2024","journal-title":"Clin. Microbiol. Rev."},{"issue":"10","key":"10.1016\/j.jtbi.2026.112449_bib0044","doi-asserted-by":"crossref","first-page":"1164","DOI":"10.1038\/s41587-020-0684-z","article-title":"Measurement of SARS-COV-2 RNA in wastewater tracks community infection dynamics","volume":"38","author":"Peccia","year":"2020","journal-title":"Nat. Biotechnol."},{"key":"10.1016\/j.jtbi.2026.112449_bib0045","doi-asserted-by":"crossref","DOI":"10.1016\/j.watres.2023.120372","article-title":"Making waves: integrating wastewater surveillance with dynamic modeling to track and predict viral outbreaks","volume":"243","author":"Phan","year":"2023","journal-title":"Water Res."},{"key":"10.1016\/j.jtbi.2026.112449_bib0046","doi-asserted-by":"crossref","DOI":"10.1016\/j.scitotenv.2022.154235","article-title":"Model-based assessment of COVID-19 epidemic dynamics by wastewater analysis","volume":"827","author":"Proverbio","year":"2022","journal-title":"Sci. Total Environ."},{"issue":"9","key":"10.1016\/j.jtbi.2026.112449_bib0047","doi-asserted-by":"crossref","DOI":"10.1016\/j.heliyon.2024.e30600","article-title":"A scoping review of global SARS-COV-2 wastewater-based epidemiology in light of COVID-19 pandemic","volume":"10","author":"Rashid","year":"2024","journal-title":"Heliyon"},{"key":"10.1016\/j.jtbi.2026.112449_bib0048","unstructured":"RDocumentation, n.d.predict: model predictions. Accessed November 28, 2024. https:\/\/www.rdocumentation.org\/packages\/stats\/versions\/3.6.2\/topics\/predict."},{"key":"10.1016\/j.jtbi.2026.112449_bib0049","doi-asserted-by":"crossref","first-page":"524","DOI":"10.1016\/j.procs.2021.01.036","article-title":"Time series analysis and forecasting of coronavirus disease in indonesia using ARIMA model and PROPHET","volume":"179","author":"Satrio","year":"2021","journal-title":"Procedia Comput. Sci."},{"issue":"11","key":"10.1016\/j.jtbi.2026.112449_bib0050","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0313927","article-title":"SARS-CoV-2 surveillance in US wastewater: leading indicators and data variability analysis in 2023\u20132024","volume":"19","author":"Schenk","year":"2024","journal-title":"PLOS ONE"},{"key":"10.1016\/j.jtbi.2026.112449_bib0051","unstructured":"Shafi, A., 2021. Medium. What are generalized additive models?https:\/\/towardsdatascience.com\/generalised-additive-models-6dfbedf1350a."},{"issue":"1","key":"10.1016\/j.jtbi.2026.112449_bib0052","doi-asserted-by":"crossref","first-page":"2837","DOI":"10.1038\/ncomms3837","article-title":"Real-time influenza forecasts during the 2012\u20132013 season","volume":"4","author":"Shaman","year":"2013","journal-title":"Nature Communications"},{"key":"10.1016\/j.jtbi.2026.112449_bib0053","doi-asserted-by":"crossref","DOI":"10.7554\/eLife.81916","article-title":"Predictive performance of multi-model ensemble forecasts of COVID-19 across European nations","volume":"12","author":"Sherratt","year":"2023","journal-title":"eLife"},{"key":"10.1016\/j.jtbi.2026.112449_bib0054","unstructured":"Taylor, S., n.d.prophet: prophet forecaster. Accessed November 28, 2024. https:\/\/www.rdocumentation.org\/packages\/prophet\/versions\/1.0\/topics\/prophet."},{"issue":"1","key":"10.1016\/j.jtbi.2026.112449_bib0055","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1080\/00031305.2017.1380080","article-title":"Forecasting at scale","volume":"72","author":"Taylor","year":"2018","journal-title":"Am. Stat."},{"issue":"1","key":"10.1016\/j.jtbi.2026.112449_bib0056","doi-asserted-by":"crossref","first-page":"5","DOI":"10.5755\/j01.erem.51.1.58","article-title":"Weather forecasting using ANFIS and ARIMA models","volume":"51","author":"Tekta\u015f","year":"2010","journal-title":"Environ. Res. Eng. Manage."},{"issue":"1","key":"10.1016\/j.jtbi.2026.112449_bib0057","doi-asserted-by":"crossref","first-page":"8625","DOI":"10.1038\/s41467-024-52504-1","article-title":"An adaptive weight ensemble approach to forecast influenza activity in an irregular seasonality context","volume":"15","author":"Tsang","year":"2024","journal-title":"Nat. Commun."},{"key":"10.1016\/j.jtbi.2026.112449_bib0058","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1016\/j.epidem.2017.08.002","article-title":"The RAPIDD ebola forecasting challenge: synthesis and lessons learnt","volume":"22","author":"Viboud","year":"2018","journal-title":"Epidemics"},{"key":"10.1016\/j.jtbi.2026.112449_bib0059","doi-asserted-by":"crossref","DOI":"10.1016\/j.scitotenv.2021.145790","article-title":"Correlation of SARS-COV-2 RNA in wastewater with COVID-19 disease burden in Sewersheds","volume":"775","author":"Weidhaas","year":"2021","journal-title":"Sci. Total Environ."},{"issue":"1","key":"10.1016\/j.jtbi.2026.112449_bib0060","doi-asserted-by":"crossref","first-page":"79","DOI":"10.3354\/cr030079","article-title":"Advantages of the mean absolute error (MAE) over the root mean square error (RMSE) in assessing average model performance","volume":"30","author":"Willmott","year":"2005","journal-title":"Climate Res."},{"key":"10.1016\/j.jtbi.2026.112449_bib0061","series-title":"Generalized Additive Models: An Introduction with R","author":"Wood","year":"2017"},{"key":"10.1016\/j.jtbi.2026.112449_bib0062","unstructured":"Wood, S. N., n.d.Gam: generalized additive models with integrated smoothness estimation. Accessed November 28, 2024. https:\/\/www.rdocumentation.org\/packages\/mgcv\/versions\/1.9-1\/topics\/gam."},{"key":"10.1016\/j.jtbi.2026.112449_bib0063","doi-asserted-by":"crossref","DOI":"10.1016\/j.watres.2021.117400","article-title":"Wastewater surveillance of SARS-COV-2 across 40 US states from February to June 2020","volume":"202","author":"Wu","year":"2021","journal-title":"Water Res."},{"issue":"11","key":"10.1016\/j.jtbi.2026.112449_bib0064","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pcbi.1005801","article-title":"Individual versus superensemble forecasts of seasonal influenza outbreaks in the United States","volume":"13","author":"Yamana","year":"2017","journal-title":"PLoS Comput. Biol."},{"issue":"9","key":"10.1016\/j.jtbi.2026.112449_bib0065","doi-asserted-by":"crossref","first-page":"2849","DOI":"10.1021\/acsestwater.3c00032","article-title":"Correlative analysis of wastewater trends with clinical cases and hospitalizations through five dominant variant waves of COVID-19","volume":"3","author":"Zhan","year":"2023","journal-title":"ACS ES&T Water"}],"container-title":["Journal of Theoretical Biology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0022519326000743?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0022519326000743?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T00:31:19Z","timestamp":1777422679000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0022519326000743"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6]]},"references-count":65,"alternative-id":["S0022519326000743"],"URL":"https:\/\/doi.org\/10.1016\/j.jtbi.2026.112449","relation":{},"ISSN":["0022-5193"],"issn-type":[{"value":"0022-5193","type":"print"}],"subject":[],"published":{"date-parts":[[2026,6]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"COVID-19 forecasting from U.S. wastewater surveillance data: A retrospective multi-model study (2022\u20132024)","name":"articletitle","label":"Article Title"},{"value":"Journal of Theoretical Biology","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.jtbi.2026.112449","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"112449"}}