{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,16]],"date-time":"2026-09-16T00:57:07Z","timestamp":1789520227942,"version":"build-2803163510"},"reference-count":69,"publisher":"MDPI AG","issue":"20","license":[{"start":{"date-parts":[[2021,10,14]],"date-time":"2021-10-14T00:00:00Z","timestamp":1634169600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJERPH"],"abstract":"<jats:p>Wastewater-based epidemiology is a recognised source of information for pandemic management. In this study, we investigated the correlation between a SARS-CoV-2 signal derived from wastewater sampling and COVID-19 incidence values monitored by means of individual testing programs. The dataset used in the study is composed of timelines (duration approx. five months) of both signals at four wastewater treatment plants across Austria, two of which drain large communities and the other two drain smaller communities. Eight regression models were investigated to predict the viral incidence under varying data inputs and pre-processing methods. It was found that population-based normalisation and smoothing as a pre-processing of the viral load data significantly influence the fitness of the regression models. Moreover, the time latency lag between the wastewater data and the incidence derived from the testing program was found to vary between 2 and 7 days depending on the time period and site. It was found to be necessary to take such a time lag into account by means of multivariate modelling to boost the performance of the regression. Comparing the models, no outstanding one could be identified as all investigated models are revealing a sufficient correlation for the task. The pre-processing of data and a multivariate model formulation is more important than the model structure.<\/jats:p>","DOI":"10.3390\/ijerph182010778","type":"journal-article","created":{"date-parts":[[2021,10,14]],"date-time":"2021-10-14T09:10:49Z","timestamp":1634202649000},"page":"10778","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":39,"title":["Quest for Optimal Regression Models in SARS-CoV-2 Wastewater Based Epidemiology"],"prefix":"10.3390","volume":"18","author":[{"given":"Parisa","family":"Aberi","sequence":"first","affiliation":[{"name":"Department of Infrastructure, University Innsbruck, 6020 Innsbruck, Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rezgar","family":"Arabzadeh","sequence":"additional","affiliation":[{"name":"Department of Infrastructure, University Innsbruck, 6020 Innsbruck, Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5136-2752","authenticated-orcid":false,"given":"Heribert","family":"Insam","sequence":"additional","affiliation":[{"name":"Department of Microbiology, University Innsbruck, 6020 Innsbruck, Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0195-1249","authenticated-orcid":false,"given":"Rudolf","family":"Markt","sequence":"additional","affiliation":[{"name":"Department of Microbiology, University Innsbruck, 6020 Innsbruck, Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Markus","family":"Mayr","sequence":"additional","affiliation":[{"name":"Department of Microbiology, University Innsbruck, 6020 Innsbruck, Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6400-8218","authenticated-orcid":false,"given":"Norbert","family":"Kreuzinger","sequence":"additional","affiliation":[{"name":"Institute for Water Quality and Resource Management, Technology University Vienna, 1040 Vienna, Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6462-2832","authenticated-orcid":false,"given":"Wolfgang","family":"Rauch","sequence":"additional","affiliation":[{"name":"Department of Infrastructure, University Innsbruck, 6020 Innsbruck, Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,10,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"461","DOI":"10.1146\/annurev.mi.49.100195.002333","article-title":"Environmental Virology: From Detection of Virus in Sewage and Water by Isolation to Identification by Molecular Biology\u2014A Trip of over 50 Years","volume":"49","author":"Metcalf","year":"1995","journal-title":"Annu. Rev. Microbiol."},{"key":"ref_2","first-page":"41","article-title":"Detection of Poliovirus, Hepatitis A Virus and Rotavirus from Sewage and Water Samples","volume":"31","author":"Kittigul","year":"2000","journal-title":"Southeast Asian J. Trop. Med. Public Health"},{"key":"ref_3","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."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"434","DOI":"10.2166\/wh.2011.019","article-title":"Surveillance of Influenza A and the Pandemic Influenza A (H1N1) 2009 in Sewage and Surface Water in the Netherlands","volume":"9","author":"Heijnen","year":"2011","journal-title":"J. Water Health"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"116810","DOI":"10.1016\/j.watres.2021.116810","article-title":"Wastewater-Based Epidemiology as a Useful Tool to Track SARS-CoV-2 and Support Public Health Policies at Municipal Level in Brazil","volume":"191","author":"Prado","year":"2021","journal-title":"Water Res."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"105689","DOI":"10.1016\/j.envint.2020.105689","article-title":"Future Perspectives of Wastewater-Based Epidemiology: Monitoring Infectious Disease Spread and Resistance to the Community Level","volume":"139","author":"Sims","year":"2020","journal-title":"Environ. Int."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"138764","DOI":"10.1016\/j.scitotenv.2020.138764","article-title":"First confirmed detection of SARS-CoV-2 in untreated wastewater in Australia: A proof of concept for the wastewater surveillance of COVID-19 in the community","volume":"728","author":"Ahmed","year":"2020","journal-title":"Sci. Total Environ."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"176","DOI":"10.1038\/d41586-020-00973-x","article-title":"How Sewage Could Reveal True Scale of Coronavirus Outbreak","volume":"580","author":"Mallapaty","year":"2020","journal-title":"Nature"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Mlejnkova, H., Sovova, K., Vasickova, P., Ocenaskova, V., Jasikova, L., and Juranova, E. (2020). Preliminary Study of SARS-CoV-2 Occurrence in Wastewater in the Czech Republic. Int. J. Environ. Res. Public Health, 17.","DOI":"10.3390\/ijerph17155508"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"012016","DOI":"10.1088\/1742-6596\/1813\/1\/012016","article-title":"Predict and Analyze Exchange Rate Fluctuations Accordingly Based on Quantile Regression Model and K-Nearest Neighbor","volume":"1813","author":"Zhang","year":"2021","journal-title":"J. Phys. Conf. Ser."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"2823","DOI":"10.2166\/wst.2020.540","article-title":"Sewage surveillance for the presence of SARS-CoV-2 genome as a useful wastewater based epidemiology (WBE) tracking tool in India","volume":"82","author":"Arora","year":"2020","journal-title":"Water Sci. Technol."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"5311","DOI":"10.1021\/acs.est.0c02172","article-title":"Letter to the Editor: Wastewater-Based Epidemiology Can Overcome Representativeness and Stigma Issues Related to COVID-19","volume":"54","author":"Murakami","year":"2020","journal-title":"Environ. Sci. Technol."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Xagoraraki, I., and O\u2019Brien, E. (2020). Wastewater-Based Epidemiology for Early Detection of Viral Outbreaks. Women in Engineering and Science, Springer.","DOI":"10.1007\/978-3-030-17819-2_5"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"116296","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":"ref_15","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random Forests","volume":"45","author":"Breiman","year":"2001","journal-title":"Mach. Learn."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Wurtzer, S., Marechal, V., Mouchel, J.M., Maday, Y., Teyssou, R., Richard, E., Almayrac, J.L., and Moulin, L. (2020). Evaluation of Lockdown Impact on SARS-CoV-2 Dynamics Through Viral Genome Quantification in Paris Wastewaters. medRxiv.","DOI":"10.1101\/2020.04.12.20062679"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"141326","DOI":"10.1016\/j.scitotenv.2020.141326","article-title":"First Proof of the Capability of Wastewater Surveillance for COVID-19 in India through Detection of Genetic Material of SARS-CoV-2","volume":"746","author":"Kumar","year":"2020","journal-title":"Sci. Total Environ."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"e00614-20","DOI":"10.1128\/mSystems.00614-20","article-title":"SARS-CoV-2 Titers in Wastewater Are Higher than Expected from Clinically Confirmed Cases","volume":"5","author":"Wu","year":"2020","journal-title":"mSystems"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"145319","DOI":"10.1016\/j.scitotenv.2021.145319","article-title":"Catching a Resurgence: Increase in SARS-CoV-2 Viral RNA Identified in Wastewater 48 h before COVID-19 Clinical Tests and 96 h before Hospitalizations","volume":"770","author":"Graber","year":"2021","journal-title":"Sci. Total Environ."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"115942","DOI":"10.1016\/j.watres.2020.115942","article-title":"SARS-CoV-2 RNA in Wastewater Anticipated COVID-19 Occurrence in a Low Prevalence Area","volume":"181","author":"Randazzo","year":"2020","journal-title":"Water Res."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Markt, R., Bergthaler, A., Bock, C., B\u00fcchel-Marxer, M., Gr\u00fcnbacher, D., Mayr, M., Peer, E., Pedrazzini, M., Penz, T., and Rauch, W. (2021). First detection and abundance of SARS-CoV-2 in wastewater in Liechtenstein: A surveillance in estimation of prevalence and impact of the SARS-CoV-2 B. 1.1.7 variant., submitted.","DOI":"10.2166\/wh.2021.180"},{"key":"ref_22","first-page":"23","article-title":"Generalized Linear Models: Checking Assumptions and Strengthening Conclusions","volume":"8","author":"Breslow","year":"1996","journal-title":"Stat. Appl."},{"key":"ref_23","first-page":"2","article-title":"Four Assumptions of Multiple Regression That Researchers Should Always Test","volume":"8","author":"Osborne","year":"2002","journal-title":"Pract. Assess. Res. Eval."},{"key":"ref_24","unstructured":"Centers for Disease Control and Prevention (2020). Evaluating and Testing Persons for Coronavirus Disease 2019 (COVID-19), Centers for Disease Control and Prevention."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"e12634","DOI":"10.15252\/emmm.202012634","article-title":"\u201cAll In\u201d: A Pragmatic Framework for COVID-19 Testing and Action on a Global Scale","volume":"12","author":"Pettit","year":"2020","journal-title":"EMBO Mol. Med."},{"key":"ref_26","first-page":"13","article-title":"Diagnostic Performance of COVID-19 Serology Assays","volume":"42","author":"Rashid","year":"2020","journal-title":"Malays. J. Pathol."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"2302","DOI":"10.1056\/NEJMoa2006100","article-title":"Spread of SARS-CoV-2 in the Icelandic Population","volume":"382","author":"Gudbjartsson","year":"2020","journal-title":"N. Engl. J. Med."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"833","DOI":"10.1002\/jmv.25825","article-title":"The Presence of SARS-CoV-2 RNA in the Feces of COVID-19 Patients","volume":"92","author":"Chen","year":"2020","journal-title":"J. Med. Virol."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"e2010182","DOI":"10.1001\/jamanetworkopen.2020.10182","article-title":"Comparison of Clinical Characteristics of Patients with Asymptomatic vs. Symptomatic Coronavirus Disease 2019 in Wuhan, China","volume":"3","author":"Yang","year":"2020","journal-title":"JAMA Netw. Open"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"911","DOI":"10.1016\/S1473-3099(20)30287-5","article-title":"Epidemiology and transmission of COVID-19 in 391 cases and 1286 of their close contacts in Shenzhen, China: A retrospective cohort study","volume":"20","author":"Bi","year":"2020","journal-title":"Lancet Infect Dis."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1337","DOI":"10.3201\/eid2606.200301","article-title":"Detection of Novel Coronavirus by RT-PCR in Stool Specimen from Asymptomatic Child, China","volume":"26","author":"Tang","year":"2020","journal-title":"Emerg. Infect. Dis."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"530","DOI":"10.1002\/dta.2246","article-title":"Potential impact of the sewer system on the applicability of alcohol and tobacco biomarkers in wastewater-based epidemiology","volume":"10","author":"Banks","year":"2020","journal-title":"Drug Test. Anal."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1697","DOI":"10.1039\/D0EW00230E","article-title":"Factors Associated with Elevated Levels of Antibiotic Resistance Genes in Sewer Sediments and Wastewater","volume":"6","author":"Eramo","year":"2020","journal-title":"Environ. Sci. Water Res. Technol."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1467","DOI":"10.1016\/j.dsx.2020.07.045","article-title":"Prediction of New Active Cases of Coronavirus Disease (COVID-19) Pandemic Using Multiple Linear Regression Model","volume":"14","author":"Rath","year":"2020","journal-title":"Diabetes Metab. Syndr."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"206","DOI":"10.1007\/s42979-020-00216-w","article-title":"Predictive Data Mining Models for Novel Coronavirus (COVID-19) Infected Patients\u2019 Recovery","volume":"1","author":"Muhammad","year":"2020","journal-title":"SN Comput. Sci."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"959","DOI":"10.1007\/s00477-020-01827-8","article-title":"A Machine Learning Forecasting Model for COVID-19 Pandemic in India","volume":"34","author":"Sujath","year":"2020","journal-title":"Stoch. Environ. Res. Risk Assess."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"2703","DOI":"10.1007\/s10489-020-01942-7","article-title":"Forecasting COVID-19 Outbreak Progression Using Hybrid Polynomial-Bayesian Ridge Regression Model","volume":"51","author":"Saqib","year":"2021","journal-title":"Appl. Intell."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"109942","DOI":"10.1016\/j.chaos.2020.109942","article-title":"A Python Based Support Vector Regression Model for Prediction of COVID19 Cases in India","volume":"138","author":"Parbat","year":"2020","journal-title":"Chaos Solitons Fract."},{"key":"ref_39","first-page":"122","article-title":"Machine Learning and Statistical Modelling for Prediction of Novel COVID-19 Patients Case Study: Jordan","volume":"11","author":"Fayyoumi","year":"2020","journal-title":"IJACSA Int. J. Adv. Comput. Sci. Appl."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Vallejo, J.A., Rumbo-Feal, S., Conde-P\u00e9rez, K., L\u00f3pez-Oriona, \u00c1., Tarr\u00edo, J., Reif, R., Ladra, S., Rodi\u00f1o-Janeiro, B.K., Nasser, M., and Cid, \u00c1. (2020). Highly Predictive Regression Model of Active Cases of COVID-19 in a Population by Screening Wastewater Viral Load. medRxiv.","DOI":"10.1101\/2020.07.02.20144865"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"144704","DOI":"10.1016\/j.scitotenv.2020.144704","article-title":"Surveillance of SARS-CoV-2 Spread Using Wastewater-Based Epidemiology: Comprehensive Study","volume":"768","author":"Hemalatha","year":"2021","journal-title":"Sci. Total Environ."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"2586","DOI":"10.1109\/TAES.2016.150722","article-title":"Robust Student\u2019st Based Nonlinear Filter and Smoother","volume":"52","author":"Huang","year":"2016","journal-title":"IEEE Trans. Aerosp. Electron. Syst."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"8162","DOI":"10.1021\/es5008388","article-title":"Population normalization with ammonium in wastewater-based epidemiology: Application to illicit drug monitoring","volume":"48","author":"Been","year":"2014","journal-title":"Environ. Sci. Technol."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"10303","DOI":"10.1021\/acs.est.9b03447","article-title":"Harnessing the Power of the Census: Characterizing Wastewater Treatment Plant Catchment Populations for Wastewater-Based Epidemiology","volume":"53","author":"Tscharke","year":"2019","journal-title":"Environ. Sci. Technol."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"1324","DOI":"10.2166\/wst.2021.343","article-title":"Data filtering methods for SARS-CoV-2 wastewater surveillance","volume":"84","author":"Arabzadeh","year":"2021","journal-title":"Water Sci. Technol."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1007\/BF02162161","article-title":"Smoothing by Spline Functions","volume":"10","author":"Reinsch","year":"1967","journal-title":"Numer. Math."},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Sharma, P., and Singh, J. (2018, January 28\u201329). Machine Learning Based Effort Estimation Using Standardization. Proceedings of the 2018 International Conference on Computing, Power and Communication Technologies (GUCON), Greater Noida, India.","DOI":"10.1109\/GUCON.2018.8674908"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1111\/j.2517-6161.1977.tb01603.x","article-title":"An Asymptotic Equivalence of Choice of Model by Cross-Validation and Akaike\u2019s Criterion","volume":"39","author":"Stone","year":"1977","journal-title":"J. R. Stat. Soc. B"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"453","DOI":"10.1016\/j.trac.2018.06.004","article-title":"Wastewater-Based Epidemiology Biomarkers: Past, Present and Future","volume":"105","author":"Choi","year":"2018","journal-title":"TrAC Trends Anal. Chem."},{"key":"ref_50","unstructured":"Eubank, R.L. (1988). Spline Smoothing and Nonparametric Regression, Marcel Dekker Inc."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1111\/j.2517-6161.1985.tb01327.x","article-title":"Some Aspects of the Spline Smoothing Approach to Non-Parametric Regression Curve Fitting","volume":"47","author":"Silverman","year":"1985","journal-title":"J. R. Stat. Soc. B"},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"783","DOI":"10.3758\/s13428-015-0611-2","article-title":"Dangers and Uses of Cross-Correlation in Analyzing Time Series in Perception, Performance, Movement, and Neuroscience: The Importance of Constructing Transfer Function Autoregressive Models","volume":"48","author":"Dean","year":"2016","journal-title":"Behav. Res. Methods"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"716","DOI":"10.1109\/TAC.1974.1100705","article-title":"A new look at the statistical model identification","volume":"19","author":"Akaike","year":"1974","journal-title":"IEEE Trans. Automat. Contr."},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Yan, X., and Su, X. (2009). Linear Regression Analysis: Theory and Computing, World Scientific Publishing.","DOI":"10.1142\/6986"},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"431","DOI":"10.1016\/0315-0860(74)90033-0","article-title":"Gergonne\u2019s 1815 Paper on the Design and Analysis of Polynomial Regression Experiments","volume":"1","author":"Stigler","year":"1974","journal-title":"Hist. Math."},{"key":"ref_56","first-page":"622","article-title":"Prediction of the final size for COVID-19 epidemic using machine learning: A case study of Egypt","volume":"5","author":"Amar","year":"2020","journal-title":"Infect. Dis. Model."},{"key":"ref_57","first-page":"1","article-title":"Learning k for kNN Classification","volume":"8","author":"Zhang","year":"2017","journal-title":"ACM Trans. Intell. Syst. Technol."},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Pourhomayoun, M., and Shakibi, M. (2020). Predicting Mortality Risk in Patients with COVID-19 Using Artificial Intelligence to Help Medical Decision-Making. medRxiv.","DOI":"10.1101\/2020.03.30.20047308"},{"key":"ref_59","doi-asserted-by":"crossref","unstructured":"Hastie, T., Tibshirani, R., and Friedman, J. (2009). The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Springer.","DOI":"10.1007\/978-0-387-84858-7"},{"key":"ref_60","doi-asserted-by":"crossref","unstructured":"Awad, M., and Khanna, R. (2015). Support vector regression. Efficient Learning Machines, Apress.","DOI":"10.1007\/978-1-4302-5990-9"},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"109853","DOI":"10.1016\/j.chaos.2020.109853","article-title":"Short-Term Forecasting COVID-19 Cumulative Confirmed Cases: Perspectives for Brazil","volume":"135","author":"Ribeiro","year":"2020","journal-title":"Chaos Solitons Fract."},{"key":"ref_62","first-page":"297","article-title":"Generalized Additive Models","volume":"1","author":"Hastie","year":"1986","journal-title":"Stat. Sci."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"138862","DOI":"10.1016\/j.scitotenv.2020.138862","article-title":"Temperature Significantly Changes COVID-19 Transmission in (Sub) Tropical Cities of Brazil","volume":"729","author":"Prata","year":"2020","journal-title":"Sci. Total Environ."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1002\/widm.8","article-title":"Classification and Regression Trees","volume":"1","author":"Loh","year":"2011","journal-title":"WIREs Data Min. Knowl. Discov."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"329","DOI":"10.1007\/s40258-020-00581-w","article-title":"A Simple Decision Analysis of a Mandatory Lockdown Response to the COVID-19 Pandemic","volume":"18","author":"Karnon","year":"2020","journal-title":"Appl. Health Econ. Health Policy"},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"2199","DOI":"10.30534\/ijeter\/2020\/117852020","article-title":"Analysis, Prediction and Evaluation of COVID-19 Datasets Using Machine Learning Algorithms","volume":"5","author":"Prakash","year":"2020","journal-title":"Int. J. Emerg. Trends Eng. Res."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"575","DOI":"10.1080\/01621459.1984.10478083","article-title":"Cross-Validation of Regression Models","volume":"79","author":"Picard","year":"1984","journal-title":"J. Am. Stat. Assoc."},{"key":"ref_68","doi-asserted-by":"crossref","unstructured":"Benesty, J., Chen, J., Huang, Y., and Cohen, I. (2009). Pearson correlation coefficient. Noise Reduction in Speech Processing, Springer.","DOI":"10.1007\/978-3-642-00296-0_5"},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"7183","DOI":"10.1029\/2000JD900719","article-title":"Summarizing Multiple Aspects of Model Performance in a Single Diagram","volume":"106","author":"Taylor","year":"2001","journal-title":"J. Geophys. Res."}],"container-title":["International Journal of Environmental Research and Public Health"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1660-4601\/18\/20\/10778\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T07:14:25Z","timestamp":1760166865000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1660-4601\/18\/20\/10778"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,10,14]]},"references-count":69,"journal-issue":{"issue":"20","published-online":{"date-parts":[[2021,10]]}},"alternative-id":["ijerph182010778"],"URL":"https:\/\/doi.org\/10.3390\/ijerph182010778","relation":{},"ISSN":["1660-4601"],"issn-type":[{"value":"1660-4601","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,10,14]]}}}