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Intro: The COVID-19 pandemic has triggered global collaborative efforts on response and research to detect SARS-CoV-2 particles not just in the human population but also in wastewater. While the examination of clinical samples from COVID-19 patients links SARS-CoV-2 to specific individuals, the analysis of an amalgam of human feces through environmental surveillance (ES) links SARSCoV-2 to populations and communities served by the wastewater system. Studies on SARS-CoV-2 in the environment were already done in high-resource countries. However, its epidemiology in wastewater bodies in the Philippines is limited. In this study, we used the National ES for Polio and Other Pathogens Network to investigate the molecular epidemiology and transmission dynamics of SARS-CoV-2 at the outset of the pandemic. Methods: This is a retrospective study of 250 wastewater samples collected from May 2020 to July 2021. Samples were processed using the two-phase concentration technique. Pepper mild mottle virus RNAs were quantified as the internal control. Real-time PCR was used to detect the N-gene of the SARS-CoV-2. Whole genomes were sequenced using the COVID-19 ARTIC v4.0. Phylogenetic and mutation analysis were done and lineage assignments were established using the PANGOLIN software. Findings: Forty-two percent (107/250) of the environmental samples detected SARS-CoV-2 particles. Fifty-nine samples with Ct values ≤38 were sequenced and the whole genome analysis revealed B.1.1 and B.6. lineages of SARS-CoV-2. When viral load were plotted with the weekly cases in the respective site, we observed that SARS-CoV2 can be detected in wastewater weeks before the spike of cases in the community. Conclusion: This is the first report on the detection of B.1.1 and B.6 SARS-CoV-2 particles in waste/surface waters in the Philippines. With the declining incidence of COVID-19 cases, this study provided data regarding the feasibility of establishing environmental surveillance for SARS-CoV-2 as a supplemental tool for human or case monitoring especially in resource-limited settings.