Communicating the High Susceptible Zone of COVID-19 and its Exposure to Population Number through a Web-GIS Dashboard for Indonesia Cases

Supriatna, Faris Zulkarnain, Ardiansyah, Nurrokhmah Rizqihandari, Jarot Mulyo Semedi, Satria Indratmoko, Nurul Sri Rahatiningtyas, Triarko Nurlambang, Muhammad Dimyati

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

The Medical Geographic Information System (Medical GIS) application during the COVID-19 pandemic crisis has become influential in communicating disease surveillance for health practitioners and society. The Johns Hopkins University has extensively used a well-known Web-GIS dashboard to track the COVID-19 cases since January 22 and illustrates the location and number of confirmed COVID-19 cases. Unfortunately, the dashboard particularly for Indonesian cases is only represented by one point (dot map) placed on the centroid of the Indonesian archipelago. Further research can fill the gap in downscaling the geographical location data of COVID-19 cases to the cities or even the village level in Indonesia and communicating the susceptible zoning to society. We uplift the point COVID-19 cases data to susceptible zoning gathered from official COVID-19 government websites, process it using Geographic Information System analysis, and communicate it to society through a Web-GIS dashboard. Five datasets, i.e., population data, administrative boundary, Landsat 8 OLI satellite imagery, COVID-19 cases geographic location, transportation infrastructure, and crowded places location, are used to analyze the susceptible area. Due to different standard data sources from each province in Indonesia, we only present provinces in Java Island with complete COVID-19 cases data on villages-scale. The technical challenges and future improvement in developing the national dashboard of Web-GIS-based susceptibility dashboard are also discussed. The dashboard information would further add some essential information for society to explore their zone status in adapting to the “New Normal” using the SICOVID-19 dashboard from their computers or gadgets during the pandemic crisis.

Original languageEnglish
Pages (from-to)706-716
Number of pages11
JournalInternational Journal of Technology
Volume13
Issue number4
DOIs
Publication statusPublished - 2022

Keywords

  • Covid-19
  • Population exposure
  • Susceptible area
  • Web-gis dashboard

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