DatAC

DatAC integrates COVID-19 epidemiological data with meteorological and air quality variables for Spain to analyze spatial and temporal associations between environmental factors and COVID-19 dynamics.

Key Features:

• Data integration: Aggregates COVID-19 case data with meteorological variables and air quality parameters including nitrogen dioxide (NO₂), carbon monoxide (CO), particulate matter (PM₂.5 and PM₁₀), sulfur dioxide (SO₂), and ozone (O₃).
• Spatial and temporal analysis: Incorporates spatial and temporal information to examine regional differences and time-based changes in environmental factors relative to COVID-19 spread and survival.
• Statistical analysis: Provides statistical capabilities for assessing correlations and trends within integrated epidemiological and environmental datasets.

Scientific Applications:

• Assessment of lockdown impacts: Used to evaluate changes in air quality during the Spanish lockdown, showing significant reductions in NO₂, CO, PM₂.5, PM₁₀, and SO₂ and concurrent increases in O₃, with effects observed across urban and rural settings and more pronounced in urban areas.
• Climate–disease correlation analysis: Facilitated analysis of associations between ambient temperature and COVID-19 incidence, indicating that ambient temperature is not a primary driver of COVID-19 outbreaks and that warm weather alone is insufficient to curb pandemic growth without control measures.

Methodology:

Applies data fusion techniques to aggregate environmental (meteorological and air quality) and COVID-19 epidemiological datasets into a cohesive analytical framework and performs statistical analyses to assess correlations and temporal/spatial trends.