SARS-CoV-2 VARIANT PREVALENCE ESTIMATION USING WASTEWATER SAMPLES

The present work describes a statistical model to account for sequencing information of SARS-CoV-2 variants in wastewater samples. The model expresses the joint probability distribution of the number of genomic reads corresponding to mutations and non-mutations in every locus in terms of the variant proportions and the joint mutation distribution within every variant. Since the variant joint mutation distribution can be estimated using GISAID data, the only unknown parameters in the model are the variant proportions. These are estimated using maximum likelihood. The method is applied to monitor the evolution of variant proportions using genomic data coming from wastewater samples collected in A Coruña (NW Spain) in the period May 2021 – March 2022. Although the procedure is applied assuming independence among the number of reads along the genome, it is also extended to account for Markovian dependence of counts along loci in the aggregated information coming from wastewater samples. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This work was supported by EDAR Bens S.A., A Coruna, Spain [grant references INV04020, 506 INV12120, INV05921 and INV148721 to MP], by the National Plan for Scientific Research, Development and Technological Innovation funded by the ISCIII, Spain - General Subdirection of Assessment and Promotion of the Research-European Regional Development Fund (FEDER) "A way of making Europe" [grant references PI15/00860 to GB, PI17/01482 and PI20/00413 to MP], by the GAIN (Xunta de Galicia, Spain) [grant references IN607A 2016/22 to GB, ED431C- 2016/015 and ED431C-2020/14 to RC, ED431C 2021/53 to SL and ED431G 2019/01 and COV20/00604 to RC and SL, by MINECO, Spain [grant references MTM2017-82724-R to RC], by the Spanish Network for Research in Infectious Diseases [REIPI RD16/0016/0006 to GB], by the "Innova Saude" Program, (INNOVAMICROLAB project) co-founded by the Galician Healthcare Service (SERGAS) and the Spanish Ministry of Science and Innovation, and by the Spanish Network of Research in Infectious Diseases (CIBERINFEC, ISCIII), and by the European Virus Archive Global (EVA-GLOBAL) project that has received funding from the European Union's Horizon 2020 research and innovation program under grant agreement No 871029. SR-F was financially supported by REIPI RD16/0016/006, KC-P by IN607A 2016/22 and the Spanish Association against Cancer (AECC) and JAV by IN607A 2016/22. DP was funded by grant EPICOVIGAL FONDO SUPERA-COVID19 from Banco Santander-CSIC-CRUE, Spain and grant CT850A-2 from ACIS SERGAS from the Conselleria de Sanidade of Xunta de Galicia, Spain. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. Yes Data can be provided upon request.