Background the current SARS-CoV-2 pandemic has emphasized the utility of viral whole genome sequencing in the surveillance and control of the pathogen . An unprecedented ongoing global initiative is increasingly producing hundreds of thousands of sequences worldwide . However, the complex circumstances in which viruses are sequenced, along with the demand of urgent results, causes a high rate of incomplete and therefore useless, sequences . However, viral sequences evolve in the context of a complex phylogeny and therefore different positions along the genome are in linkage disequilibrium . Therefore, an imputation method would be able to predict missing positions from the available sequencing data . Results We developed impuSARS, an application that includes Minimac, the most widely used strategy for genomic data imputation and, taking advantage of the enormous amount of SARS-CoV-2 whole genome sequences available, a reference panel containing 239,301 sequences was built . The impuSARS application was tested in a wide range of conditions (continuous fragments, amplicons or sparse individual positions missing) showing great fidelity when reconstructing the original sequences . The impuSARS application is also able to impute whole genomes from commercial kits covering less than 20% of the genome or only from the Spike protein with a precision of 0.96 . It also recovers the lineage with a 100% precision for almost all the lineages, even in very poorly covered genomes (< 20 %) Conclusions imputation can improve the pace of SARS-CoV-2 sequencing production by recovering many incomplete or low-quality sequences that would be otherwise discarded . impuSARS can be incorporated in any primary data processing pipeline for SARS-CoV-2 whole genome sequencing.