Imari Joy C. Borda¹, Sheryl Grace C. Buenaventura¹, Zython Paul T. Lachica¹, Ivy Grace M. Panogalinog^1,2, Ian Lorenzo Quibod³, Alexis Erich S. Almocera^1,2, Lyre Anni E. Murao^1,4, May Anne E. Mata^1,2*, Ricardo C.H. del Rosario⁵

Computational analysis of genomic viral sequences has the potential to inform public health responses and to manage the spread of SARS-CoV-2. We sought to determine if phylodynamic modeling could describe the early local spread of the virus in the Philippines, and if the model could reflect the government’s control interventions. We applied previously published phylodynamic modeling tools to analyze 19 publicly available SARS-CoV-2 genomes sampled from 03 April to 18 July 2020 in the National Capital Region (NCR) of the Philippines. We estimate the date of the virus introduction, the effective reproduction number (R_e), the basic reproduction number (R₀), and the effective population size (N_e). We found that the index case in NCR was on February 4, 2020 (95% Highest Posterior Density (HPD): November 18, 2019, to March 25, 2020) with R₀ of 2.20 (95% HPD: 1.74 to 2.80). Both the R_e and the N_e estimates suggest a progressive epidemic growth with an accelerated expansion on 20 May 2020 (95% HPD: 06 April 2020 – 08 June 2020), roughly the date of transition from enhanced community quarantine (ECQ) to the more relaxed modified enhanced community quarantine (MECQ). Additionally, we estimate that there was underreporting in the total cases with only about 5% of the total cases being detected. Finally, the insights from different phylodynamic models coincide with each other. This demonstrates that even with limited genomic data, phylodynamic modeling can still provide useful insights about SARS-CoV-2, a virus known to mutate rapidly whose evolution can be captured in just a short period. In summary, our results show a general view of the early stage spread of COVID-19 in NCR. Our study will serve as a conceptual framework for the use of SARS-CoV-2 genomic data in inferring epidemiological parameters to inform public health decisions in the Philippines.

• data: Contains the alignment of the sequences in FASTA format. The metadata was also included.
  • ncr.fasta: alignment used in the BEAST phylodynamic analysis.
  • ncr-global.fasta: alignment used in the creation of maximum likelihood tree.
  • metadata-gisaid.tsv: metadata of sequences downloaded from GISAID.
  • metadata-ncbi.csv: metadata of sequences downloaded fron NCBI.
• maximum-likelihood: Contains the IQTree output of the maximum likelihood phylogeny.
  • ncr-global.treefile: ML tree which includes the NCR and global samples.
• temporal-signal: Contains the scripts and output files for calculating the temporal signal and plotting the corresponding root-to-tip divergence plot.
  • ncr.treefile: ML tree of the NCR samples using IQTree.
  • genetic-distance.csv: Datafile from TempEst which contains the genetic distance, dates, and residuals of the sequences.
  • p-value.R: Calculates the p-value of the root-to-stip regression. Also uses the function in temsignalfunctions.R and the R scripts inside the functions folder. These scripts were adapted from the work of Murray et al.
  • p-value.RData: Oytput from the p-value.R.
  • regression-plot.R: Plots the root-to-tip regression.
  • temporal-signal.png: Output from the regression-plot.R.
• coalsky: Contains BEAST xml file, R scripts, and outputs associated with the coalescent model.
  • ncr-coalsky.xml: BEAST xml file for running the the coalescent skyline model.
  • ncr-coalsky.log: Output from the BEAST analysis.
  • ncr-coalsky.csv: Raw Ne estimates from the log file extracted using the Tracer tool.
  • ncr-coalsky.R: R script for plotting the Ne estimates.
  • ncr-coalsky.png: Output of the R script. This is the Ne plot.
• bdsky: Contains BEAST xml file, R scripts, and outputs associated with the birth-deat skyline (BDSKY) model.
  • ncr-bdsky-time-post.xml: BEAST xml file for running the BDSKY model (posterior) for estimating the R_e through time. The output of this is the ncr-bdsky-time-post.log. The corresponding prior run involves the xml file ncr-bdsky-time-prior.xml and its output is ncr-bdsky-time-prior.log.
  • ncr-bdsky-time.R: R script for plotting R_e through time. The output is ncr-bdsky-time.png.
  • ncr-bdsky-int-post.xml: BEAST xml file for running the BDSKY model (posterior) for estimating the R_e in relation to community quanrantine measures. The output of this is the ncr-bdsky-int-post.log. The corresponding prior runs involves the ncr-bdsky-int-prior.xml xml file and its output is ncr-bdsky-int-prior.log.
  • ncr-bdsky-int.R: R script for plotting R_e in relation to community quanrantine measures. The output is ncr-bdsky-int.png.
  • ncr-bdsky-maj-post.xml: BEAST xml file for running the BDSKY model (posterior) for estimating the date of major change in R_e. The output of this is the ncr-bdsky-maj-post.log. The corresponding prior runs involves the xml file ncr-bdsky-maj-prior.xml and its output is ncr-bdsky-maj-prior.log.
  • ncr-bdsky-maj.R: R script for plotting R_e before and after the date of its major change. The output is ncr-bdsky-maj.png.
• bdsir: Contains BEAST xml file, R scripts, and outputs associated with the birth-death SIR (BDSIR) model.
  • ncr-bdsir-post.xml: BEAST xml file for running the BDSIR model (posterior).
  • ncr-bdsir-post.log: Output from the BEAST analysis using ncr-bdsir-post.xml.
  • ncr-bdsir-prior.xml: BEAST xml file for running the BDSIR model (prior).
  • ncr-bdsir-post.log: Output from the BEAST analysis using ncr-bdsir-prior.xml.
  • ncr-cases.csv: Reported COVID-19 cases in the NCR, Philippines.
  • ncr-bdsir-signal.R: R script for plotting some of estimated parameters from the BDSIR model comparing the prior to the posterior.
  • ncr-bdsir-signal.png: Output from the ncr-bdsir-signal.R.
  • loglist.txt: List of log file (posterior only).
  • ncr-bdsir-traj.R: R script for plotting the SIR trajectories from the BDSIR model. Large part of this script was adapted form the work of Kühnert et al (2014).
  • ncr-bdsir-traj.png: Output from the ncr-bdsir-traj.R.