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In this paper the examination of the modifiable areal unit problem is extended into multivariate statistical analysis. In an investigation of the parameter estimates from a multiple linear regression model and a multiple logit regression model, conclusions are drawn about the sensitivity of such estimates to variations in scale and zoning systems. The modifiable areal unit problem is shown to be essentially unpredictable in its intensity and effects in multivariate statistical analysis and is therefore a much greater problem than in univariate or bivariate analysis. The results of this analysis are rather depressing in that they provide strong evidence of the unreliability of any multivariate analysis undertaken with data from areal units. Given that such analyses can only be expected to increase with the imminent availability of new census data both in the United Kingdom and in the USA, and the current proliferation of GIS (geographical information system) technology which permits even more access to aggregated data, this paper serves as a topical warning.

In this paper, we propose a methodology to study the scale effect and zoning effect of the modifiable areal unit problem (MAUP). Instead of aggregating basic spatial units by the neighborhood criterion, we suggest placing a square lattice over the centroids representing the enumeration units in the study area. Areal units are aggregated if their centroids are in the same square. By changing the size of the square in the lattice, we can study the scale effect. By randomly placing the lattice, we can study the zoning effect. This methodology links the MAUP effects to specific scale reflected by the size of grids. We use this method to study the MAUP effects on the segregation index D. Among the thirty selected cities in the USA, values of D respond to the MAUP in a diverse pattern. We assess the scale effect on D by examining the changes of averaged values of D over the range of scale levels. We also borrow concepts from fractal analysis to assess the scale effect on D and to measure how sensitive the D values of these cities are to different zonal patterns.

To establish the prevalence, risk factors and implications of suspected or confirmed coronavirus disease 2019 (COVID-19) infection among healthcare workers in the United Kingdom (UK). Cross-sectional observational study. UK-based primary and secondary care. Healthcare workers aged ≥18 years working between 1 February and 25 May 2020. A composite endpoint of laboratory-confirmed diagnosis of SARS-CoV-2, or self-isolation or hospitalisation due to suspected or confirmed COVID-19. Of 6,152 eligible responses, the composite endpoint was present in 1,806 (29.4%) healthcare workers, of whom 49 (0.8%) were hospitalised, 459 (7.5%) tested positive for SARS-CoV-2, and 1,776 (28.9%) reported self-isolation. Overall, between 11,870 and 21,158 days of self-isolation were required by the cohort, equalling approximately 71 to 127 working days lost per 1,000 working days. The strongest risk factor associated with the presence of the primary composite endpoint was increasing frequency of contact with suspected or confirmed COVID-19 cases without adequate personal protective equipment (PPE): 'Never' (reference), 'Rarely' (adjusted odds ratio 1.06, (95% confidence interval: [0.87-1.29])), 'Sometimes' (1.7 [1.37-2.10]), 'Often' (1.84 [1.28-2.63]), 'Always' (2.93, [1.75-5.06]). Additionally, several comorbidities (cancer, respiratory disease, and obesity); working in a 'doctors' role; using public transportation for work; regular contact with suspected or confirmed COVID-19 patients; and lack of PPE were also associated with the presence of the primary endpoint. A total of 1,382 (22.5%) healthcare workers reported lacking access to PPE items while having clinical contact with suspected or confirmed COVID-19 cases. Suspected or confirmed COVID-19 was more common in healthcare workers than in the general population and is associated with significant workforce implications. Risk factors included inadequate PPE, which was reported by nearly a quarter of healthcare workers. Governments and policymakers must ensure adequate PPE is available as well as developing strategies to mitigate risk for high-risk healthcare workers during future COVID-19 waves. [Abstract copyright: © 2021 Kua et al.]