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 NO2levels. By fitting linear regression models with penalized splines on NO2, we found that the association between COVID-19 mortality and NO2varies 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.
The modifiable areal unit problem causes unreliable analytical results and encourages false conclusions regarding the dependence of transmission on certain factors, unnecessary control measures, or the unrealistic hope that warm weather or the BCG vaccine will impede COVID-19 transmission. Solutions for minimizing MAUP and achieving reliable analytical results include: (1) Conducting epidemiological studies at the individual level with decent exposure assessment and case-control or cohort study designs; although the finest data in this article was at the city level, MAUP still exists when aggregating individual data to the city level. Therefore, the Center for Disease Control and other institutions with individual tracking data may wish to try the preferred individual analysis method. (2) Combining epidemiological evidence with biological evidence; lab results on virus stability under different temperature and humidity conditions (van Doremalen et al., 2020) would be a good supplement for epidemiological findings. (3) Attempting to conduct the study at the finest spatial scale possible and listing this as a possible limitation if (1) is not possible.
We hope this short correspondence can help other researchers working on this topic to find substantial evidence on environmental contributors and other influential factors of the COVID-19 pandemic.
Reference & source information: https://www.sciencedirect.com/
Read More on :