The effect of the modifiable areal unit problem (MAUP) on spatial aggregation of COVID-19 wastewater surveillance data

• Published in: The Science of the total environment Vol. 957; p. 177676
• Main Authors: Zhu, Yifan, Hill, Dustin T., Zhou, Yiquan, Larsen, David A.
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 20.12.2024
• Subjects: bias; COVID-19 - epidemiology; COVID-19 infection; environment; Environmental Monitoring - methods; Epidemic risk assessment; Humans; Modifiable areal unit problem; monitoring; New York; New York - epidemiology; risk perception; SARS-CoV-2; Severe acute respiratory syndrome coronavirus 2; spatial data; Spatial data aggregation; Statistical bias; viral load; wastewater; Wastewater - virology; Wastewater surveillance; wastewater treatment; Wastewater-Based Epidemiological Monitoring; Wastewater-based epidemiology; New York; Statistical bias; Epidemic risk assessment; Modifiable areal unit problem; Wastewater surveillance; Spatial data aggregation; Wastewater-based epidemiology
• ISSN: 0048-9697; 1879-1026; 1879-1026
• DOI: 10.1016/j.scitotenv.2024.177676

Large wastewater-based epidemiology (WBE) projects often have wide coverage and multiple sampling sites, necessitating spatial aggregation for data reporting and interpretation. However, the outcome may be impacted by a type of statistical bias called the modifiable areal unit problem (MAUP). In this study, we examined the presence and extent of the MAUP scaling effect on a New York State COVID-19 wastewater surveillance project. Specifically, we investigated three metrics: 1) the difference in wastewater SARS-CoV-2 concentrations between sampling at city-level site (i.e., city's primary wastewater treatment plant influent stream) and at upstream sampling sites; 2) the correlation between WBE data and clinical indicators at the WWTP-level and the more aggregated county-level; and 3) the proportion of population affected by misalignment of COVID-19 community risk levels at different spatial scales. The results showed that the MAUP can have a negative impact on risk perception by masking regions with high wastewater viral load or COVID-19 community risk level. On the other hand, the MAUP improved the correlation between wastewater surveillance and clinical measures by an average of 26.02 %. This is the first study to investigate the MAUP in the context of WBE and may encourage future WBE projects to consider the implications of the MAUP when interpreting and reporting spatial data, ultimately leading to better data representativeness and accuracy. [Display omitted] •Scaling effect of the modifiable areal unit problem (MAUP) was investigated.•Wastewater surveillance and clinical data were subject to risk masking.•The MAUP can affect risk perception and association identification.