COVID-19 pandemic in Baguio city, Philippines: A spatio-temporal analysis

Abstract

This article explores the clustering of COVID-19 incidences in the City of Baguio using spatio-temporal analysis. The GIS maps of the cumulative incidence rates of 129 barangays of the city were investigated in the span of ten months from March 2020 to December 2020. A thorough investigation of the CIR in the city may contribute to proper formulation and or implementation of policies to lessen the growing number of COVID-19 cases in the city. The Moran's index was used to determine significant spatial autocorrelations on the CIR before undergoing hotspot analysis. The Getis-Ord Gi∗ and Local Moran's I of QGIS were used to determine hotspots and coldspots, confirmed through the cluster and outlier analysis, respectively. The months of October and November registered clustering patterns and hotspots. The increasing number of test kits available were also considered in the analysis of the increasing COVID-19 cases in the city. Moreover, results showed that most of the incidences occurred at the center of city, that is, the business districts where most people go. It was found that cluster distribution of COVID-19 with high CIR has less than 1% likelihood to be random for the months of October 2020 and November 2020. This implies that the barangays with high CIR are significantly clustered. Hence COVID-19 protocols such as social distancing must be strictly implemented. © 2022 Author(s).