Modifiable areal unit problem and environmental factors of COVID-19 outbreak

Highlights

• Modifiable areal unit problem (MAUP) arises when aggregating data into districts, leading to statistical bias.

• Real data of atmospheric NO₂ and COVID-19 outbreak in China is analyzed to illustrate the presence of MAUP.

• Atmospheric NO₂ shows different directions of association with COVID-19 mortality under different aggregation strategies.

Abstract

Several recent studies have explored the association between environmental factors, such as temperature, humidity, and air pollution, and the severity of the COVID-19 outbreak by analyzing the statistical association at the district level. However, we argue that the modifiable areal unit problem (MAUP) arises when aggregating disease and environmental data into districts, leading to bias in such studies. Therefore, in this study, we analyzed the association between environmental factors and the number of COVID-19 death cases under different aggregation strategies to illustrate the presence of MAUP. We used real-world COVID-19 outbreak data from the Hubei and Henan Provinces and studied their association with atmospheric NO₂ levels. By fitting linear regression models with penalized splines on NO₂, we found that the association between COVID-19 mortality and NO₂ varies when data were aggregated (1) at the city level, (2) under two different aggregation strategies, and (3) at the provincial level, indicating the presence of MAUP. Therefore, this study reminds researchers of the presence of MAUP and the necessity to minimize this problem while exploring the environmental determinants of the COVID-19 outbreak.