Phylodynamic analysis of the spread of COVID-19 in the National Capital Region, Philippines during the early stages of the pandemic

Abstract

In epidemiological studies, key parameters could be incorrectly estimated when case data are underreported, as demonstrated during the early spread of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Phylodynamic models, which integrate viral genomic data, offer an alternative approach to understand SARS-CoV-2 transmission dynamics. Here we aimed to understand the early spread of SARS-CoV-2 in the National Capital Region of the Philippines (NCR) through phylogenetic and phylodynamic analysis of viral sequences. We investigated how government-imposed community quarantines influenced viral spread and compared these estimates with those from conventional compartmental models. We analyzed 75 SARS-CoV-2 genomes sampled from NCR from 2020/03/13 to 2020/07/27. We used the Birth-Death Skyline (BDSKY) model to estimate the effective reproduction number (Re), the Coalescent Skyline (COALSKY) model for the effective population size (Ne), and the Birth-Death Susceptible-Infected-Removed (BDSIR) model to estimate the basic reproduction number (R0), transmission rate, and the number of susceptible, infected, and removed individuals. The estimated R0 was 1.45 (95% Highest Posterior Density (HPD): 1.33–1.62). A major increase in Re was inferred around 2020/05/15 (95% HPD: 04/26 to 05/30), coinciding with the easing of quarantine measures. Comparison of phylodynamic estimates and reported cases revealed that only 3% of cases were detected daily. Our findings, derived from a relatively small number of viral genomes, provide insights into the early spread of COVID-19 in NCR and demonstrate the utility of phylodynamic models for informing public health responses in the Philippines.