Spatiotemporal Analysis for COVID-19 Delta Variant Using GIS-Based Air Parameter and Spatial Modeling

Area of Science:

• Environmental Science
• Epidemiology
• Public Health

Background:

• The COVID-19 pandemic presents a global challenge, necessitating studies on disease spread and influencing factors.
• Understanding the spatiotemporal dynamics of COVID-19 is crucial for effective control strategies.

Purpose of the Study:

• To determine the spatiotemporal spread pattern of COVID-19 in Surabaya.
• To investigate the relationship between air pollution parameters (CO, NO2, SO2, O3) and COVID-19 spread.
• To assess the impact of social restrictions on virus transmission and air quality.

Main Methods:

• Spatiotemporal analysis using weighted mean center, directional distribution, Getis-Ord Gi*, and Moran's I.
• Geographically weighted regression to identify spatial influence zones of COVID-19.
• Correlation analysis between COVID-19 cases, air pollutant levels, and social restriction policies.

Main Results:

• The COVID-19 epicenter location shifted randomly, but overall spread in Surabaya significantly decreased.
• High infection clusters were identified in the eastern and southern regions; cases showed clustering during spikes.
• Lockdown policies led to reduced levels of CO, NO2, SO2, and O3, with pollution increasing after 7 weeks.

Conclusions:

• Social restrictions and lockdowns effectively reduced COVID-19 transmission and air pollution in Surabaya.
• Air quality improved during lockdown periods, particularly near outbreak centers.
• Monitoring spatiotemporal patterns and environmental factors is vital for managing pandemics.